yomi
OfficialYomi is a local MCP server that lets an AI agent fully interact with your LINE account by acting as a secondary device using LINE's native protocol — no official API or browser required. It handles E2EE (Letter-Sealing) decryption natively.
Authentication & Session
Passwordless secondary-device login (PIN-based)
Reading Messages
Fetch all unread conversations (
get_unread_digest), list all chats/groups with previews, paginate messages from any conversation, and download/decrypt image, video, audio, or file attachments
Sending Messages & Media
Send E2EE text (with @mentions and reply-quoting), images, files, audio, video, location pins, contact cards, and stickers
Stickers
List, search, and preview owned sticker packages before sending
Reactions & Message Actions
Add/cancel reactions, unsend your own messages, and mark conversations as read
Contacts & Groups
Find/list contacts, get group members, create/rename groups, invite/kick members, leave groups, add/block/unblock friends, and accept invitations
Local Cross-Conversation Search
Bulk-index messages into a local SQLite database with semantic embeddings, then run hybrid keyword (FTS5) + semantic search across all indexed conversations — fully local, nothing uploaded
Privacy & Scope Control
Exclude sensitive chats from indexing (and purge their existing data), include them again later, and view the current privacy denylist
Provides tools for reading LINE messages (unread digests, chat messages, media), sending messages and images, searching conversations locally, managing login sessions, and controlling privacy scope, all by connecting as a secondary device on your LINE account.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@yomiSummarize my unread LINE and tell me who's waiting on a reply."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Yomi (読み) — the personal LINE MCP server
Yomi is an open-source LINE MCP server for your personal account. Read, reply, send images, and search every conversation from Claude or any local AI agent — without a browser, bot account, or LINE's own client.
The name reads more than one way. 読み (yomi) — a reading: not just parsing your messages, but reading the situation, the way you do. 詠み (yomi) — to recite: it doesn't read in silence, it reads things back to you. And 黄泉 (yomi) — the unreachable realm; the very yomi in 黄泉帰り (yomigaeri), "returning from Yomi." Like a messenger moving between two realms, Yomi passes through sealing and silence to bring messages still readable deep inside your conversations back into the light. It does not summon history already lost; it helps what has not disappeared be seen again.
Unlike LINE's official Bot MCP server, which connects AI agents to a LINE Official Account through the Messaging API, Yomi connects to your existing personal LINE account and conversations as a secondary device.
Yomi speaks LINE's TCompact-over-HTTPS protocol directly, decrypts Letter-Sealing
(E2EE) messages and media, and exposes the result to any AI agent through a small
stdio MCP server. Point Claude Desktop (or any
MCP client) at it and the agent can catch up on your LINE the way you do — read,
reply, send an image, mention someone, and search your whole history locally — and,
with get_insight, read the situation: which conversations are waiting on your
reply, who ties your world together, and what has gone overdue.
No official API, no bot account, no webhook. Yomi logs in as a secondary device on your own account.
Guides: What is a LINE MCP server? · LINE MCP 是什麼?Yomi、官方 Bot 與桌面自動化的差異.
Unofficial. Yomi is an independent personal project, not affiliated with or endorsed by LINE. Using it may be against LINE's Terms of Service, and running an additional client on your account carries a risk of rate-limiting or suspension. It is intended for reading your own account. Use it at your own risk. See Disclaimer.
Getting started
Native Desktop preview
Yomi Desktop puts the LINE inbox and local agent workspace in one native app.
It bundles its own runtime: users do not install Node, open Terminal, clone
this repository, or configure YOMI_RUN_MJS. Native Desktop is separate from
the Claude Desktop MCPB extension described below.
Platform | General-user package | Signing status | Install experience |
macOS 14+, Apple Silicon |
| Developer ID signed and Apple notarized | Open DMG → drag Yomi to Applications → open Yomi |
Windows 10/11 x64 |
| Trusted OSS signing application in progress | Download remains unavailable until signing and installer smoke pass |
The macOS package has been tested through the real downloaded-app path:
quarantined DMG, install to /Applications, Gatekeeper assessment, first
launch, bundled-runtime message refresh, and no-terminal LINE login form. The
Windows installer contains the equivalent in-app phone/PIN login flow and is
tested on a native Windows runner before release.
Desktop builds are experimental and unofficial. LINE changes may break them, and running an additional client may put an account at risk. Prefer a test account and keep a current backup. Preview installers are published as GitHub pre-releases only after platform signing is available.
See the desktop release process, code-signing policy, and privacy policy.
MCP server and Desktop Extension
You need Node.js and a LINE account. Yomi runs locally
through npx; you do not need to clone this repository, install Bun, or build
anything. Run node --version first, and install the current LTS if the command
is missing or the version is unsupported.
Yomi's local search index uses Node's built-in node:sqlite, so it needs
v22.13 or newer — except v23.0–v23.3, which are newer than v22.13 yet still
lack that module (it was unflagged in both 22.13.0 and
23.4.0). Any current LTS is fine.
This is engines.node in package.json; the rest of Yomi runs on older Node,
but search, scope and capture do not.
⚠️ Yomi needs a client that runs it on your own machine. Cloud-only tools (ChatGPT, Claude.ai web) cannot run Yomi. Configure Yomi in Claude Desktop or Claude Code and it works in both chat and Cowork, because Desktop starts Yomi on your machine and Cowork's local sessions load it. Do not ask Cowork to install Yomi for you: Cowork's shell runs inside a throwaway VM, not on your machine, so anything it installs there is gone when the session ends. Follow the steps below yourself, in your own terminal.
Choose the client you actually use and follow only that section. Claude Code and Claude Desktop have separate MCP settings; configuring one does not configure the other.
The easiest path, and the only one that needs no command line at all. Claude Desktop ships its own Node runtime, so nothing else has to be installed.
Download the bundle for your machine from the latest release:
Machine
File
Windows (Intel/AMD)
yomi-win32-x64.mcpbMac (Apple Silicon)
yomi-darwin-arm64.mcpbLinux (x64)
yomi-linux-x64.mcpbIn Claude Desktop, open Settings → Extensions, and drag the downloaded file onto that page (or just double-click the file).
Review what it asks for, click Install.
Start a conversation and say "log in to LINE". Yomi shows a form, you enter your phone number, and you confirm on your phone. No terminal at any point.
This skips the config file entirely, which also sidesteps the Windows MSIX bug described below.
Note for Cowork users: do not ask Cowork to install Yomi for you. Cowork's shell runs inside a throwaway VM — not on your machine — and it will not type into your real terminal. Install the bundle yourself with the three clicks above; once installed, Cowork's local sessions can use Yomi like any other tool.
Find the full path to
npx:macOS / Linux: which npx Windows: where npxOpen the Claude Desktop config file:
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json⚠️ Windows: the documented path may not be the one Claude actually reads. Claude Desktop ships as an MSIX package, whose filesystem is virtualized. The app reads its config from
%LOCALAPPDATA%\Packages\Claude_pzs8sxrjxfjjc\LocalCache\Roaming\Claude\claude_desktop_config.jsonwhile Settings → Developer → Edit Config opens the unvirtualized
%APPDATA%\Claude\file. They are two different files that never sync, so a correct Yomi config written to the documented path is **silently ignored** — no error, no log, Yomi simply never appears. This is claude-code#26073, still open. If Yomi does not show up after a restart, write the same config to theLocalCachepath above as well. (Not applicable to Claude Code, or to Desktop installed outside MSIX.)Add Yomi under
mcpServers, replacing the examplecommandwith the full path printed in step 1. On Windows, JSON requires each\in the path to be written as\\:
{
"mcpServers": {
"yomi": {
"command": "/opt/homebrew/bin/npx",
"args": ["@rikaidev/yomi"]
}
}
} For example, a Windows path may look like
"C:\\Program Files\\nodejs\\npx.cmd". Use the path reported on your own
machine rather than copying either example blindly.
⚠️ The
npxyou name here does not decide which Node runs Yomi. On macOS and Linuxnpxis a script beginning with#!/usr/bin/env node, so it runs whichevernodecomes first on Claude Desktop'sPATH— not the Node installed beside thenpxyou just pointed at. Desktop inherits itsPATHfrom the desktop session, which is often not your terminal's, and version managers (nvm, fnm, asdf, volta, …) put their ownnodeahead of everything else. Sowhich npxcan report a perfectly modern install while Yomi still starts on an old Node.The symptom is specific: logging in, reading and sending all work, but search, scope and capture fail, and the log says
No such built-in module: node:sqlite. Yomi prints the runtime it actually got in that error — read it rather than assuming.The fix is to give the server a
PATHwhose first entry holds a supportednode:"yomi": { "command": "<the npx path from step 1>", "args": ["-y", "@rikaidev/yomi"], "env": { "PATH": "<dir holding a supported node><sep><a base PATH>" } }Separator:
:on macOS/Linux,;on Windows. Keep a usable base after it (/usr/local/bin:/usr/bin:/binor your platform's equivalent) — this replaces the server'sPATHrather than prepending to it, andnpxneeds the ordinary tools.Naming an absolute
nodeincommanddoes not work, however plausible it looks:npxspawns the package's own bin as a child process and resolvesnodefromPATHagain for it, socommandonly picks who runsnpx, not who runs Yomi. SettingPATHis what actually reaches the server.
Configuring this with an AI agent? MCP configs are mostly written by agents
now rather than by hand, so the steps above are stated for a human reading their
own machine. An agent should resolve the values instead of emitting placeholders,
and this setup has one trap worth stating outright: naming npx in command
does not pin the runtime. Procedure:
Find a Node that actually has the module Yomi's index needs — do not infer it from a version number:
node -e 'require("node:sqlite")' && command -v node # POSIX node -e "require('node:sqlite')" && where node # WindowsIf it throws, that Node is unusable for search/scope/capture. Try the other installs (
which -a node,nvm ls,fnm list, …) until one passes; only then continue.Write that Node's directory into
env.PATH, per the JSON above, and keep a basePATHafter it. Resolve the directory on the target machine (dirnameof the path from step 1); do not copy an example out of this README — they are Apple Silicon Homebrew paths and wrong nearly everywhere.Do not instead put an absolute
nodeincommand. It reads like the stronger fix and is not one:npxspawns the package's bin as a child and re-resolvesnodefromPATHfor it, socommandonly decides who runsnpx. This was measured, not assumed — with a Node 20 first onPATH,command-pinning still gave the server Node 20.command -vmay also hand back a wrapper rather than a real binary — heap shims, local-firstnpxwrappers and version-manager stubs are all common, and some behave differently depending on the client's working directory. Do not try to reason your way to the "real" one. Step 3 settles it.Verify with a tool that touches the index.
yomi versionis not a verification — it prints a string without opening SQLite, so it succeeds on a Node that cannot run search. Callget_scope_policy: it needs SQLite and no LINE login. If it returns the policy text, the runtime is right. If it fails, the error names the Node that actually ran and what it needed.Fully quit and reopen Claude Desktop. Confirm Yomi is loaded under Settings → Developer before anything else: if Yomi is not listed there, Claude never read your config — on Windows, see the MSIX warning in step 2. Once it is listed, the tools are available in chat and in Cowork's local sessions alike.
You do not need to install Claude Code for this setup.
claude mcp add yomi -- npx @rikaidev/yomiStart a new claude session. The Yomi tools should appear automatically. This
command configures Claude Code only; it does not configure Claude Desktop.
This form leaves the runtime to PATH, which is fine as long as the node your
claude session resolves is a supported one — it is the same PATH you can see,
unlike Claude Desktop's. Check with node -e 'require("node:sqlite")'. If it
throws, or you would rather not depend on PATH at all, name the Node
explicitly:
claude mcp add yomi -e PATH="$(dirname "$(command -v node)"):$PATH" -- npx -y @rikaidev/yomiEither way, verify with get_scope_policy rather than yomi version: the
version command prints a string without opening SQLite, so it passes on a Node
that cannot run search.
Running Claude Code inside a clone of this repo? Spell the spec
@rikaidev/yomi@latest. Without a tag,npxlooks for a local bin first, and in this repopackage.jsondeclares"bin": {"yomi": ...}while nothing links it intonode_modules/.bin— sonpxskips the install and dies withsh: yomi: command not found. An explicit tag makes it fetch the published package. Only affects working copies of Yomi itself; everywhere else the untagged form is fine.
This standard config works in most MCP clients:
{
"mcpServers": {
"yomi": {
"command": "npx",
"args": ["@rikaidev/yomi"]
}
}
}Cursor Settings → MCP → Add new MCP Server → name it yomi, command type, value: npx @rikaidev/yomi
Or add to .cursor/mcp.json in your project root.
Add to .vscode/mcp.json:
{
"servers": {
"yomi": {
"command": "npx",
"args": ["@rikaidev/yomi"]
}
}
}Add to ~/.config/opencode/opencode.json:
{
"mcp": {
"yomi": {
"type": "local",
"command": ["npx", "@rikaidev/yomi"],
"enabled": true
}
}
}codex mcp add yomi npx @rikaidev/yomiOr add to ~/.codex/config.toml:
[mcp_servers.yomi]
command = "npx"
args = ["@rikaidev/yomi"]Add to cline_mcp_settings.json:
{
"mcpServers": {
"yomi": {
"type": "stdio",
"command": "npx",
"args": ["-y", "@rikaidev/yomi"]
}
}
}Add to ~/.codeium/windsurf/mcp_config.json — same JSON as standard config.
amp mcp add yomi -- npx @rikaidev/yomiAdvanced settings → Extensions → Add custom extension → name yomi, type STDIO, command: npx @rikaidev/yomi
grok mcp add yomi -- npx @rikaidev/yomiFirst login
Once connected, tell the agent:
"Log into LINE — my number is +8869XXXXXXXX."
Approve the device on your phone (see Logging in), and:
"Summarize my unread LINE and tell me who's waiting on a reply."
Related MCP server: LINE Bot MCP Server (SSE Support)
What you can do
Yomi exposes 20 tools over MCP (the ones worth naming; see the tables). Large
read results use token-efficient TOON;
small status and write results use compact JSON. Errors remain plain text and media
uses native MCP image/audio/resource content.
"Honest error" below means an explicit failure naming the problem (e.g.
missing_decrypt_material) — Yomi never fabricates a fallback, a placeholder, or a
fake success.
Reading
Tool | Does |
| One-shot: every conversation with unread messages, each with its latest messages, E2EE-decrypted, sender names resolved. Built for "summarize my unread and suggest next steps." Read-only — never marks anything read. |
| Chats/groups/rooms with unread counts and a decrypted last-message preview. Newest-active first. |
| One conversation, decrypted. Paginate deeper with a |
| Any decrypted attachment (image/video/audio/file). Honest error on non-media. |
| Friend-list lookup by name substring, or the full list. Raw LINE data — no fuzzy scoring, no affinity ranking. |
| Members of a persistent group. Ad-hoc rooms without a group record fail honestly rather than returning a fake empty list. |
Insight (read the situation, not just the messages)
Tool | Does |
| A compact context network over your local index — structure the agent reasons over, not a message dump. Returns |
Writing (these really send — not drafts)
Tool | Does |
| Sends an E2EE text message now (pairwise key for 1:1, group key for groups/rooms). Optional |
| Encrypts, uploads to LINE OBS, and sends an E2EE image now. Works for 1:1, groups, and rooms. One send per call. Honest failure if the key can't be resolved or the upload is rejected. |
| Sends a read receipt the other party can see. Explicit only — reading messages and background capture never mark anything read. |
Search (local, cross-conversation — LINE has no such primitive)
Tool | Does |
| Hybrid search across all indexed conversations. Auto-collects on first use, diversifies results across chats, and returns a small context window around each hit. Returns |
| Explicit bulk-index into the local DB + embed for semantic search. The only tool allowed to bulk-fetch; runs once per call, never on a timer. |
Scope & privacy (all work offline, no LINE session needed)
Tool | Does |
| Denylist a conversation and purge its already-indexed data. Not just future capture — a denylist that left old data in the index would be fake privacy. |
| Re-allow a conversation (does not restore purged data). |
| Show the denylist / the full privacy policy (read from |
Session
Tool | Does |
| Passwordless secondary-device login. See below. |
Logging in
Prerequisite: on your primary phone, enable 設定 › 我的帳號 › 允許自其他裝置登入 (Settings › Account › Allow login on other devices). Without it LINE never offers this device a sign-in prompt — this is the single most common reason a first login appears to hang.
⚠️ Single Desktop Session Limit: LINE allows only one desktop client session at a time per account. Because Yomi connects as a desktop secondary device (
DESKTOPMAC), logging into Yomi will sign out your official LINE Desktop app (and signing back into LINE Desktop will invalidate Yomi's session). You cannot use Yomi and the official LINE Desktop client simultaneously.
You only need to give the agent your phone number in E.164 form — it supplies the
region itself (e.g. TW for a +886 number) when it calls the tool.
Yomi drives LINE's passwordless (secondary-device) flow. How the login surfaces depends on your MCP client:
Clients with the MCP
elicitationcapability —loginprompts you for your phone/region, shows the PIN in a dialog, and blocks to completion. One call, no PIN relayed through the model. Your phone number never enters the transcript.Clients without it (e.g. Claude Desktop today) — two calls.
login(with your phone + region) returns the PIN in its result; enter it in LINE on your primary phone and approve the device; then calllogin_complete, which blocks until the phone confirms. The agent should calllogin_completeimmediately — it does the waiting, so there is nothing for you to report back.From a terminal —
npx @rikaidev/yomi loginruns the whole flow on stdout, PIN and all. Always available as a fallback.
The one deadline that matters is LINE's: you have about 3 minutes from when the PIN is shown to enter it and approve the device. Yomi's own client keeps listening for many minutes beyond that, so a slow phone is never the failure — only LINE's 3-minute code lifetime is.
Once you've logged in, the session — including a login certificate — is persisted (see below), and future logins skip the PIN entirely.
There is also an experimental MCP Apps UI (a
ui://yomi/logincard) for clients that render interactive views. It is spec-correct and renders under the MCP Inspector, but some hosts fetch the resource without completing the view handshake, so it is display-only and never on the critical path — the flows above always work regardless.
Sessions and credentials
Yomi owns its own login. On startup it calls resumeSession() once, reading the
LINE session from the macOS Keychain (service dev.rikai.yomi.credentials, account
line) and silently refreshing the token if needed.
First-party credentials. The passwordless login persists the auth token, refresh token, certificate, MID, and the E2EE keypair itself — then reads them back to verify the write actually landed. A login that can't be persisted fails loudly at login, not silently at the next restart.
Shared session. The session is stored in the canonical
dev.rikai.yomi.credentialskeychain entry (or local credential store), allowing Yomi MCP and Yomi Desktop to share the exact same LINE login session seamlessly.Platform note. On macOS the session lives in the login Keychain. On Linux and Windows Yomi currently falls back to a local JSON file — functional, but less protected than an OS secret store, and less exercised than the macOS path. Native secure-storage backends (libsecret / DPAPI) are planned; until then, treat a non-macOS install accordingly.
Every tool except login and the offline scope/search tools returns an honest error
when there is no session. Yomi is otherwise a pure query server — it never polls,
never backfills in the background; each tool call makes exactly the LINE requests it
needs, and collect_messages is the only path that fetches across many chats at once.
Search
LINE has no cross-conversation search; Yomi builds one locally. The index is a
gitignored SQLite database (data/search-index.db) in the repo — nothing leaves
your machine.
Search is hybrid by design. It always runs FTS5 keyword search (bm25 over
bigram-preprocessed text, so CJK substrings with no word boundaries are covered) and,
when embeddings exist, semantic search, then fuses the two ranked lists by
Reciprocal Rank Fusion. Pure semantic search silently drops exact matches that
live in un-embedded messages; pure keyword misses paraphrases; fusing both surfaces
an exact term and a meaning-match together. The response's mode field always
reports which methods contributed.
Semantic ranking keeps each message as its own vector. Testing against real indexed LINE conversations found that embedding overlapping conversation windows diluted the center message and reduced retrieval quality. Context is therefore added only after ranking: Yomi limits one chat from flooding the top results and expands each winner with two messages on either side so the agent sees the exchange that gave the hit meaning without weakening the embedding itself.
Semantic ranking uses Xenova/bge-small-zh-v1.5 (BAAI general embedding, small,
Chinese-primary but multilingual) via transformers.js. Embedding inference runs
fully in-process on CPU — your message text is never sent anywhere.
The one caveat is a one-time model download: on the first collect_messages or
search_messages, transformers.js fetches the model (~90 MB) from huggingface.co
and caches it locally; every run afterwards is fully offline. That first fetch is an
outbound HTTPS request to HuggingFace for the model weights — it carries your IP and
which model is being downloaded, but no message content and no LINE data. If you
need Yomi fully air-gapped, pre-populate the transformers.js cache (or point it at a
local model directory) before the first search so no network call is ever made.
The secondary-device reality (read before trusting "I can't get old messages")
Yomi runs as a secondary device on your account. That shapes what it can see:
Group chats without Letter Sealing are plaintext at the LINE server — full history and media, no restriction.
Group chats with Letter Sealing are E2EE, and there the epoch matters. Such a group is encrypted with a shared group key that rotates (on membership changes, or when a client provisions a new one). LINE only ever hands a device the current group key — there is no API to fetch a superseded one. So a secondary device decrypts messages from the epoch whose key it holds onward; messages sent under an older epoch — before Yomi obtained the current key — can come back undecryptable, even in a group whose earlier history it can read. This is inherent to Letter Sealing's per-epoch group keys, not a bug here. It can also cut sideways: the epoch your phone holds and the epoch Yomi holds need not be the same, so the two devices can each read a different slice of the very same group.
Installing Yomi does not itself rotate anything, so "before I installed Yomi" is the wrong boundary. Yomi only ever resolves an existing group key; it never registers (mints) one, because minting rotates the group's shared secret for every member and strands every message encrypted under the previous one. So a fresh install picks up the current key and reads back to the last rotation — which may predate the install by months. The boundary is the last rekey, not your install date. And once Yomi has seen an epoch it keeps that key, so a rotation after install leaves it able to read both sides. If a group comes back undecryptable all the way to today, that is not this limitation — please report it.
1:1 media uses the account-level E2EE keychain, which a secondary device fully possesses (LINE syncs it during pairing) — Yomi can decrypt 1:1 images/files it can see.
1:1 history backfill is the one real limitation. LINE does not hand a secondary device the past 1:1 message history the way it does for groups. Messages received while Yomi is connected decrypt normally; deep-scrolling into 1:1 history that predates pairing may come back empty. This is a LINE server-side restriction, not a bug here.
When decryption genuinely fails, Yomi returns an explicit missing_decrypt_material
error — never a fake card or placeholder. Silence is honest; a fabricated result is not.
Development
For contributors working on the Yomi source code (requires bun
or Node.js 24+ — .nvmrc pins the same 24 that CI installs, so nvm use in this
directory picks it up; note nvm does not read engines, which is why the two are
stated separately and guarded by a test):
bun install # install dependencies (or npm install)
bun run.mjs # run the stdio MCP server
bun run.mjs login # run the login flow in a terminal
npm run build # tsc --noEmit — type-check only (Yomi ships & runs from src/)
npm test # bun testThe build only type-checks and compiles; this repo does not talk to live LINE
servers as part of its own build. Connecting an MCP client and calling login is
what actually starts a session.
src/
line/ LINE protocol core: TCompact/Thrift codec, E2EE (Letter-Sealing,
group keys, media), Talk/Auth/Sync service clients, session state,
passwordless login flow.
auth/ Credential store (macOS Keychain, JSON-file fallback off-darwin).
search/ Local cross-conversation index (SQLite + FTS5) and the offline
embedding pipeline (transformers.js).
mcp/ The stdio server: tool schemas, handlers, the privacy-policy loader,
and the experimental MCP Apps login view (mcp/ui/).
util/ [TAG]-prefixed logger (stderr only — stdout is the MCP JSON-RPC stream).Everything Yomi writes for humans goes to stderr; stdout is reserved for the
MCP JSON-RPC stream. A stray console.log corrupts the protocol — don't add one on
any path the server can reach.
Privacy
By default Yomi indexes all your conversations into the local, on-device search
index so an agent can search across them — a capture-all default, opt-out per chat.
Nothing is ever uploaded; the only data that leaves your device is whatever the agent
itself surfaces in its replies. (The one non-LINE network call Yomi itself makes is the
one-time embedding-model download from HuggingFace on the first search — model
weights in, no message content out; see Search.) PRIVACY.md
is the canonical policy,
and Yomi surfaces that same text to the agent on connect (and via get_scope_policy)
so it can disclose the default before any bulk read.
Disclaimer
Yomi is an independent, unofficial personal project, built for learning and for accessing one's own LINE account. It is not affiliated with, authorized, or endorsed by LINE Corporation. "LINE" is a trademark of its respective owner.
Running Yomi may violate LINE's Terms of Service, and operating an additional client
on an account can result in rate-limiting or suspension of that account. Yomi is
intended for accessing your own account and data. You are solely responsible for
how you use it. The software is provided "as is", without warranty of any kind — see
LICENSE.
Acknowledgments
Yomi's LINE protocol implementation was written with reference to three open-source projects, whose field layouts, E2EE chunk ordering, request shapes, and Thrift definitions informed this independent implementation:
evex-dev/linejs (MIT) — request shapes and the Letter-Sealing E2EE payload layout.
DeachSword/CHRLINE (BSD-3-Clause) — protocol field layouts and the passwordless login flow.
er1ce/LINE-Protocol (Apache-2.0) — Thrift enum definitions (ContentType, MessageRelationType, ServiceCode).
Their copyright notices and full license texts are reproduced in NOTICE,
as their licenses require.
License
MIT
Available Tools
41 toolsaccept_invitationA
Accepts a group/chat invitation for your LINE account — you join the chat. Use for a group you were invited to (its chatId appears with invited status). One accept per call.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE group/room MID whose invitation to accept, as returned by list_conversations. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It adds behavioral context such as 'you join the chat' and 'One accept per call,' implying it is a one-shot action. However, it does not disclose what happens if called multiple times, authentication requirements, or error conditions (e.g., already a member).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description consists of two concise sentences with no fluff. The purpose is front-loaded, and every sentence contributes meaning. It efficiently conveys the action, context, and constraint (one accept per call).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one parameter, no output schema, no nested objects), the description covers the essential aspects: what it does, when to use it, and parameter sourcing. It lacks details on success/error responses but is adequate for an agent to infer behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single parameter chatId. The description adds value by specifying that the chatId comes from list_conversations, which provides usage context beyond the schema's description alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Accepts' and the resource 'group/chat invitation for your LINE account'. It specifies the action 'you join the chat' and distinguishes the tool by mentioning the chatId appears with invited status, differentiating it from sibling tools like invite_member or list_conversations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: 'Use for a group you were invited to (its chatId appears with invited status).' This tells the agent when to use this tool. However, it does not explicitly state when not to use it or mention alternative tools, though siblings like leave_group and invite_member provide implicit contrast.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
add_friendA
Adds a person to your LINE friends by their MID (e.g. from get_group_members or find_contact). One add per call.
| Name | Required | Description | Default |
|---|---|---|---|
| mid | Yes | MID of the person to add as a friend, e.g. from get_group_members. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals a key behavioral trait: 'One add per call.' It also implies mutation (adding a friend). It does not discuss permissions or rate limits, but for a simple operation this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, each essential. No redundancy, directly conveys purpose and a key constraint. Front-loaded with the verb and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 parameter, no output schema), the description covers all necessary aspects: what it does, how to use it, and a limitation. No gaps for a tool of this complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the parameter is already documented. The description adds value by providing usage context ('e.g. from get_group_members or find_contact') beyond the schema description, helping the agent understand valid inputs.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Adds'), the resource ('a person to your LINE friends'), and the method ('by their MID'). It provides examples of where to obtain the MID, making the purpose unmistakable. It distinguishes itself from sibling tools like block_contact or find_contact.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives context on how to obtain the MID from other tools (get_group_members, find_contact), implying usage context. However, it does not explicitly state when not to use it or compare with alternatives like accept_invitation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
block_contactA
Blocks a contact for your LINE account — they can no longer message you. Reversible with unblock_contact. One block per call.
| Name | Required | Description | Default |
|---|---|---|---|
| mid | Yes | MID of the contact to block. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description must carry behavioral info. States 'they can no longer message you' and 'one block per call', but omits details like idempotency or permissions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loading purpose and key behavior with no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequately covers purpose, one-time action, and reversibility for a simple tool. Lacks return value info, but not critical given no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% for 'mid'; description does not add extra semantics beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Blocks' and resource 'contact'. Differentiates from sibling 'unblock_contact' by explicitly mentioning reversibility.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Mentions reversibility via 'unblock_contact', implying when to use. Lacks explicit exclusions or alternatives like 'remove_friend'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
cancel_reactionA
Removes this account's reaction from a LINE message. Undoes a react_message. One cancellation per call.
| Name | Required | Description | Default |
|---|---|---|---|
| messageId | Yes | LINE message id whose reaction to remove, as returned by get_chat_messages. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses scope (this account's reaction), undo behavior (undoes react_message), and limitation (one per call). No annotations provided, so description carries burden and does it well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with all essential info: action, scope, relation to sibling, usage constraint. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, description is fully informative: purpose, behavior, parameter source, usage patterns, and limitations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Only parameter messageId has schema description, which is 100% covered. Description adds context 'as returned by get_chat_messages', improving usability beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb 'Removes' and resource 'this account's reaction'. Distinguishes from sibling 'react_message' by stating 'Undoes a react_message'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly links to react_message as undo. Mentions 'One cancellation per call' implying usage constraint. No explicit when-not-to-use, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
collect_messagesA
Bulk-fetch recent messages from LINE conversations into Yomi's local cross-conversation search index (LINE has no native cross-chat search). Fetches up to perChat per chat (default 100) for chatIds, or all conversations when omitted, and best-effort embeds them for semantic search — re-running also repairs any messages still missing a vector. A background capture loop keeps the index current on its own, so call this only to force a reconcile or backfill specific chats. Undecryptable messages are skipped, not fabricated.
| Name | Required | Description | Default |
|---|---|---|---|
| chatIds | No | LINE chat/group/room MIDs to collect from, as returned by list_conversations. Omit to collect from all conversations. | |
| perChat | No | Maximum recent messages to fetch per chat (default 100). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It reveals that embeddings are done best-effort, re-running repairs missing vectors, and undecryptable messages are skipped (not fabricated). It also mentions the autonomous background loop, providing comprehensive behavioral insight.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, coherent paragraph that is concise yet informative. It front-loads the purpose and then adds details, but could benefit from slight structural improvements (e.g., bullet points) for even easier scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 optional parameters, no output schema), the description covers all necessary aspects: purpose, when to use, behavior (best-effort embedding, repair, error handling), and parameter defaults. It is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents both parameters. The description restates the parameter roles and defaults but adds no new semantic information beyond what is in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: bulk-fetching recent messages from LINE conversations into a cross-conversation search index. It uses specific verbs ('bulk-fetch') and resources ('recent messages'), and distinguishes itself from siblings by noting LINE's lack of native cross-chat search and the tool's role in indexing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description specifies that the tool should only be called to force a reconcile or backfill specific chats, as a background capture loop normally keeps the index current. This provides clear usage context, though it could explicitly reference sibling tools like get_chat_messages for comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_groupA
Creates a new LINE group/room immediately with the given members (no message is sent). chatType 0 = group (invitees must accept before joining), 1 = room (members added directly); default 1. Provide name and mids (initial members, e.g. from find_contact). One create per call.
| Name | Required | Description | Default |
|---|---|---|---|
| mids | Yes | MIDs of the initial members to add. | |
| name | Yes | Name for the new group. | |
| chatType | No | LINE chat type: 0 = group (invite-based), 1 = room (direct add). Default 1. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must bear full burden. It discloses that no message is sent, chatType affects member addition (invite vs direct), and only one create per call. Does not mention errors, rate limits, or idempotency, but is transparent about core behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is concise with four sentences that front-load the main purpose. No redundant information; each sentence adds unique value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
No output schema or annotations, but description covers key behavior. Lacks details on return value (e.g., created group ID), error handling, or prerequisites like login. Adequate for a simple tool but not fully comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with good descriptions. The description adds value by clarifying chatType meaning (group vs room) and noting that mids can come from find_contact, which aids parameter selection.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool creates a LINE group/room immediately with given members and no message is sent. Distinguishes between chatType 0 and 1, differentiating from sibling tools like list_groups or leave_group.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear when-to-use guidance: creating a group with initial members. Mentions that mids can come from find_contact and defaults chatType to 1. Does not explicitly state when not to use or give alternatives but implies the context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
exclude_chatsA
Add conversations to Yomi's privacy denylist. Excluded chats are (1) skipped by future collect_messages/search_messages auto-collect — never fetched or indexed — and (2) PURGED now: their already-indexed messages and embeddings are deleted from the local index in the same call. A real privacy action, not just a future filter. Local-index operation; works without a live LINE session.
| Name | Required | Description | Default |
|---|---|---|---|
| chatIds | Yes | LINE chat/group/room MIDs to exclude, as returned by list_conversations. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses both future filtering and immediate data purging, and notes it works locally without a live LINE session. No behavioral traits are hidden.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, each essential: purpose, effects, and operational context. Front-loaded and no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Comprehensive for a mutation tool with no output schema, covering what the tool does and its side effects. Minor gap: no mention of return value, but acceptable given the action-oriented nature.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description of parameter. The tool description adds meaning by explaining the consequences of passing chat IDs (skip and purge), going beyond schema details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it adds conversations to a privacy denylist, with explicit effects (skipping future auto-collect and purging existing data). It distinguishes from siblings like include_chats and list_excluded_chats by describing the dual action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for privacy exclusion of chats, but does not explicitly mention when not to use or provide alternatives. However, the context 'a real privacy action' and sibling names suggest reversal with include_chats.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
find_contactA
Find LINE friends whose display name contains name (case-insensitive substring). Returns each match's mid for send_message. Raw friend-list lookup — no ranking, no fuzzy scoring.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Substring to match against friends' display names, case-insensitive. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It discloses substring matching, case-insensitivity, and return of mid, but omits details like no-match behavior or pagination.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the purpose and provide key details with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple lookup tool with one parameter, the description covers return value (mid) and matching behavior, sufficient for the agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and description adds case-insensitivity detail, enhancing understanding beyond the schema's description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it finds LINE friends with display name containing the given substring (case-insensitive), specifying the output as mid for send_message and distinguishing from ranking/fuzzy scoring.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implied usage for exact substring matching with mention of no ranking or fuzzy scoring, but does not explicitly exclude alternatives like list_contacts for full listing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_chat_messagesA
Fetch messages from one LINE conversation. Text is E2EE-decrypted when keys are available; each message has fromName (resolved sender), a mediaType flag (image/video/audio/file) plus messageId for get_message_media, and mentions (LINE's raw contentMetadata.MENTION, or null — a literal "@name" in text is not itself a mention). Without before, returns the most recent count. With before (id/deliveredTime of the oldest message already seen), returns one older page — repeat to page further back.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Maximum number of messages to return (default 50). | |
| before | No | Cursor to fetch messages older than this point. Use the id and/or deliveredTime of the oldest message already seen. | |
| chatId | Yes | LINE chat/group/room MID, as returned by list_conversations. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided so description carries full burden. It discloses E2EE decryption, resolved sender name, mediaType flag, mentions handling, and paging behavior thoroughly.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph, front-loaded with main action. Every sentence adds value, though could be slightly more structured (e.g., separate sections).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and tool complexity (paging, E2EE, mentions), description covers key behavioral aspects and return fields adequately.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. Description adds meaningful context beyond schema, such as E2EE decryption, fromName, and mentions as raw contentMetadata.MENTION, enhancing parameter understanding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Fetch messages from one LINE conversation' with specific verb and resource. It distinguishes from sibling tools like get_message_media by mentioning messageId for that purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes when to use `before` for paging and explains default behavior (most recent messages). Does not explicitly mention alternatives but provides clear usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_group_membersA
List the members of one LINE group (mid + displayName each). Resolves persistent groups (c...); ad-hoc rooms (r...) without a group record return an honest error, never a fabricated empty list.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE group chat MID, as returned by list_conversations. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that ad-hoc rooms return an honest error, not a fabricated empty list. No annotations exist, so description provides useful behavioral context beyond the basic listing operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose, no wasted words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains output format, handles edge case for ad-hoc rooms, and parameter is well-defined. No output schema exists, so description compensates fully.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Single parameter chatId with 100% schema coverage. Description adds no new information beyond schema, but schema is sufficient. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states verb 'List', resource 'members of one LINE group', and output format 'mid + displayName each'. Distinguishes itself from sibling tools like list_conversations and get_chat_messages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (persistent groups) and when not (ad-hoc rooms returning error). Lacks explicit mention of alternatives but provides clear context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_insightA
A compact "what needs my attention" context network over the local index — you make the final call, this assembles the evidence cheaply. Nodes: connectors (people across ≥2 of your chats, with structural bridges) and relationships (per-conversation engagement, reply rhythm, recency). open: conversations whose latest message is NOT yours, ranked by how overdue they are relative to your usual reply rhythm there, each with fromName (last speaker), a preview of the latest message, overdueRatio/typicality, and a lastMessageId pointer. It carries NO message threads and makes NO judgement about addressee, nicknames, or open-request vs closing-ack — those are language understanding you do by reading each preview (a group message may be addressed to someone else, who then owns it), fetching the full thread with get_chat_messages only for the few worth it. Reads across all conversations (denylist-excluded dropped). Empty only when the index is empty.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | No | Optional focus: restrict `relationships` and `pending` to this chat (as returned by list_conversations). Omit to scan all conversations. | |
| sinceHours | No | Lookback window in hours, measured back from the newest captured message (not wall-clock). Default 504 (21 days). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that it carries no message threads, makes no judgement about addressee, reads across all conversations, and returns empty only when index empty. Fully transparent given no annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Dense but efficient: every sentence provides value, front-loaded with purpose. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Explains output structure, parameters, edge cases (empty index, denylist). Complete without output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 100% coverage with descriptions, but description adds context: chatId is optional, sinceHours default is 504. Adds practical meaning beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it assembles a 'what needs my attention' context network, describing nodes and 'open' conversations. Distinguishes from siblings by noting it carries no message threads and leaves judgement to the user.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides context on when to use ('get compact evidence') and suggests following up with get_chat_messages for full threads. Implicitly excludes use for fetching threads, but no explicit alternatives or when-not-to-use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_message_imageA
Download and decrypt one LINE image message. Legacy alias of get_message_media restricted to images; prefer get_message_media for video/audio/file.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID the message belongs to. Required to locate E2EE key material. | |
| preview | No | Fetch the smaller preview object instead of the full-resolution original. | |
| messageId | Yes | LINE message id, as returned by get_chat_messages. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Mentions decryption and that it's restricted to images, but lacks details on error handling or side effects. With no annotations, the description could be more thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. Front-loaded with the primary action and includes essential usage guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers purpose, legacy status, and alternative tool. Minor gap: does not explicitly state return format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear descriptions; the description does not add extra parameter information, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'Download and decrypt one LINE image message' and distinguishes itself from sibling get_message_media by noting it's a legacy alias restricted to images.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells when to use this tool (for images) and when to prefer the alternative: 'prefer get_message_media for video/audio/file'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_message_mediaA
Download and decrypt one LINE media message of any downloadable type (image, video, audio, file). Returns image/audio MCP content, or an embedded resource blob (with filename when known) for video/file. Non-media messages (text, sticker refs, unsupported types) return an honest error naming the content type — never fabricated bytes.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID the message belongs to. Required to locate E2EE key material. | |
| preview | No | Fetch the smaller preview object instead of the full-resolution original (images/video only). | |
| messageId | Yes | LINE message id, as returned by get_chat_messages. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Discloses decryption, return content types for each media, and honest error for non-media. Lacks mention of rate limits or authorization needs.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with main action, no redundant words. Every sentence adds critical information about behavior and types.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Handles all return types explicitly, including error case. No output schema, but description compensates fully. Covers edge cases and diverse media types.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers all 3 parameters (100%), baseline 3. Description adds context: chatId for E2EE key material, messageId from get_chat_messages, preview for smaller objects. Adds value beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool downloads/decrypts LINE media messages of any downloadable type, listing specific types (image, video, audio, file) and distinguishing from siblings by specifying error behavior for non-media.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit 'when to use' guidance or alternatives, but description implies only use for media messages by stating non-media return an error. Missing comparison to siblings like send_message or get_chat_messages.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_scope_policyA
Return Yomi's data-capture privacy policy (the disclosure to show the user) plus the current list of excluded conversations. Call this to show the user, in concrete terms, what Yomi captures by default and how to exclude conversations.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. It indicates a read operation returning data, but does not disclose authorization needs, rate limits, or any side effects. Adequate for a simple getter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words; front-loaded with purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, description could detail the structure of the returned policy or excluded conversations list. It mentions 'disclosure to show the user' but lacks specifics, leaving some ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters in input schema; baseline score of 4 applies since description adds no param info beyond schema, which is fine given zero parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly specifies returning Yomi's data-capture privacy policy and the list of excluded conversations, distinguishing it from sibling tools like list_excluded_chats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states the use case: 'Call this to show the user, in concrete terms, what Yomi captures by default and how to exclude conversations.' Does not mention when not to use, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_unread_digestA
One-shot unread digest: every LINE conversation with unread messages, each with its most recent messages (default 10), E2EE-decrypted, with resolved sender names. Saves calling list_conversations then get_chat_messages per chat. Read-only: never marks anything read, never touches the search index; denylist-excluded conversations are omitted. Returns an empty list when nothing is unread — never fabricated.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of conversations to scan for unread (default 20). | |
| perChat | No | Maximum recent messages to include per unread conversation (default 10). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses all key behaviors: read-only nature, no side effects on read status or search index, inclusion/exclusion criteria (denylist), output behavior (empty list vs missing data). Since annotations are absent, description fully covers transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: one states purpose and output, second contrasts with alternatives, third clarifies behavioral constraints. Every sentence adds value, no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers behavior, side effects, and edge cases (empty result). Lacks explicit output structure details, but since no output schema exists, the description provides enough for an agent to understand the returned data conceptually. Could mention that messages include text, timestamps, etc., but the key elements are described.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Parameter descriptions in schema are already clear (limit for conversations to scan, perChat for messages per unread chat). Description reiterates default values but doesn't add new semantic details beyond confirming they are defaults. Schema coverage is 100%, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Specific verb+resource: 'get unread digest' with clear scope: all conversations with unread messages, including decrypted messages and resolved names. Distinguishes from sibling tools list_conversations + get_chat_messages by being one-shot.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: instead of combining list_conversations and get_chat_messages. Also clarifies limitations: denylist-excluded conversations omitted, returns empty list when nothing unread.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
include_chatsA
Remove conversations from Yomi's denylist, re-allowing future capture. Does NOT restore data purged when the chat was excluded — capture resumes from empty history going forward. Local-index operation; works without a live LINE session.
| Name | Required | Description | Default |
|---|---|---|---|
| chatIds | Yes | LINE chat/group/room MIDs to re-include. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral traits: it only re-allows future capture, does not restore purged data, and operates on a local index. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three succinct sentences, each adding value: first states purpose, second clarifies limitation, third gives operational context. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and no output schema, the description is complete. It covers purpose, limitations, and operational context, leaving no gaps for an agent to decide.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (only parameter chatIds is described in the schema). The description does not add extra meaning beyond 'LINE chat/group/room MIDs to re-include.' Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Remove conversations from Yomi's denylist, re-allowing future capture.' It specifies the resource (conversations) and distinguishes from the sibling tool 'exclude_chats' by being the inverse operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context: it does NOT restore purged data, and it is a local-index operation. While it doesn't explicitly list when to use vs alternatives, the inverse relationship with exclude_chats is implied, and the limitations guide appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
invite_memberA
Invites members into a LINE group immediately. Invitees must accept before joining. Provide mids (from find_contact or get_group_members). One call per invite batch.
| Name | Required | Description | Default |
|---|---|---|---|
| mids | Yes | MIDs of the people to invite. | |
| chatId | Yes | LINE group/room MID to invite into, as returned by list_conversations. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description covers key behaviors (immediate invite, acceptance required, one batch per call) but lacks details on error handling, permissions, or idempotency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the primary action, no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter tool, the description covers the main functionality and usage, though absence of output schema and annotations is compensated with adequate behavioral notes.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema coverage, the description adds value by explaining the source of mids and batch constraint, going beyond the schema's property descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (invites) and the resource (LINE group members), and distinguishes from sibling tools like kick_member and leave_group.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides guidance on sourcing mids from find_contact or get_group_members and notes batch limitations, but does not explicitly compare with other group tools or mention when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
kick_memberA
Removes (kicks) members from a LINE group immediately — they lose access at once (re-adding needs a fresh invite); visible to every member. Provide mids (from get_group_members). One call per removal batch.
| Name | Required | Description | Default |
|---|---|---|---|
| mids | Yes | MIDs of the members to remove. | |
| chatId | Yes | LINE group/room MID to remove members from, as returned by list_conversations. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses immediate loss of access, visibility to all members, and need for fresh invite to re-add. This covers key behavioral traits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no filler, front-loaded with the main action. Every sentence adds essential information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately covers prerequisites and behavior. It does not explain return values, but the tool is simple enough that this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds context by specifying that mids come from get_group_members and chatId from list_conversations, adding value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'removes (kicks)' and resource 'members from a LINE group', clearly distinguishing it from sibling tools like invite_member and leave_group.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states to provide mids from get_group_members and that one call handles one batch. While not mentioning when not to use, the sibling context and prerequisites are clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
leave_groupA
Makes THIS LINE account leave a group immediately — it loses access to the group and its history. One leave per call.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE group/room MID to leave, as returned by list_conversations. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Even without annotations, the description discloses key behaviors: immediate action, loss of history access, and 'one leave per call' constraint. This is sufficient for a simple tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, zero waste. The first sentence states action and effect, the second adds a constraint. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and simple structure, the description adequately covers the tool's purpose, effect, and parameter. Could mention if the group must exist, but otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a clear description for chatId. The description adds no additional semantic value to the parameter beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'leave', the resource 'group', and the effect 'loses access to its history'. It distinguishes itself from siblings like kick_member (which removes others) and rename_group.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to make the account leave a group) but does not explicitly contrast with alternatives like kick_member or provide conditions for when not to use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_contactsA
List the authenticated user's full LINE friend list as-is (mid + displayName). No ranking, no interaction-frequency ordering.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the output fields and lack of ordering, but omits any side effects, authentication requirements, rate limits, or pagination behavior. As a read operation, it is likely safe, but this is not stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that conveys the essential purpose and constraints without unnecessary words. It is front-loaded with the main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (no parameters, no output schema), the description is largely sufficient. It names the output fields and clarifies the lack of ordering. However, it could benefit from details about output format, authentication, or pagination limits.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, and schema description coverage is 100%. The description adds no parameter information because none exist, which is appropriate. Baseline for 0 params is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list', the resource 'LINE friend list', and specifies the data returned (mid + displayName). It also clarifies what it does not include (ranking, interaction-frequency ordering), distinguishing it from potential similar tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for retrieving the raw, unfiltered friend list, but it does not explicitly state when to use it versus alternatives like find_contact or get_insight. No when-not-to-use or excluded cases are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_conversationsA
List LINE conversations (chats, groups, rooms) with unread counts, a preview of the last message, and a human-readable name (group title, or the other party's display name for a 1:1).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of conversations to return (default 20). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description bears the full burden. It discloses the output structure, which is helpful, but does not mention side effects, rate limits, authentication, or ordering behavior. Adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the action and efficiently conveys the tool's purpose and output. No redundant words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one optional parameter, the description covers the core functionality and output fields. Minor gaps like sorting order or pagination details are missing but not critical given the schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 100% coverage for the single parameter 'limit', and the description does not add any additional meaning beyond what the schema already provides. Baseline score of 3 applies as the description adds no extra value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'list', the resource 'LINE conversations', and explicitly mentions the returned fields (unread counts, last message preview, human-readable name). It is specific and distinguishes from sibling tools like list_contacts or list_stickers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as list_contacts or get_chat_messages. It does not mention any prerequisites, restrictions, or context for appropriate use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_excluded_chatsA
List the conversations currently on Yomi's privacy denylist. Returns [{ chatId, name }]; name is best-effort resolved when a live LINE session exists, otherwise null — never a fabricated placeholder. Local-index operation; works without a live LINE session.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses return format, name resolution behavior (best-effort, null without session, never fabricated), and offline capability. No annotations provided, so description compensates fully.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-loading purpose then details. Every sentence adds value; no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Fully explains return value and offline behavior. With no output schema, description provides necessary coverage. Could mention empty array case, but not critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist (0 param schema). Schema coverage is 100%. Baseline 4 applies as description need not add parameter info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'list the conversations on Yomi's privacy denylist' with specific verb and resource. Differentiates from sibling tools like list_conversations (all chats) and exclude_chats (adding to list).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Specifies it is a local-index operation working without a live LINE session, indicating when to use. No explicit alternatives but context from sibling tools provides implicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_stickersA
List the sticker packages this LINE account OWNS — the only stickers it can send. Returns each package's packageId (STKPKGID), title, and version (STKVER). Get individual sticker ids via search_stickers, then send_sticker. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| language | No | Locale for package titles, e.g. 'en' or 'zh-Hant'. Defaults to 'en'. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, but description explicitly states 'Read-only', which is a key behavioral trait. It also describes the return fields (packageId, title, version). However, it omits details like auth requirements or pagination, which are less critical for a simple list operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise with three front-loaded sentences: purpose, return fields, and usage guidance. No unnecessary words or repetitions.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description partially compensates by listing return fields. It covers the core functionality and usage context, though it could explicitly state the result format (e.g., array of objects).
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, with the language parameter already described well in the schema. The description does not add additional semantic meaning beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states 'List the sticker packages this LINE account OWNS' with a specific verb (list) and resource (sticker packages), and distinguishes from siblings by noting it only lists owned packages that can be sent.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly directs to use search_stickers for individual sticker ids and then send_sticker for sending, providing clear workflow guidance and distinguishing when to use this tool vs. alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
loginA
Log in to LINE via the passwordless secondary-device flow. Requires 設定 > 我的帳號 > 允許自其他裝置登入 enabled on the primary phone — with it off LINE never prompts that phone and NO login can succeed, so raise this with the human up front rather than after a failure. On MCP clients with form elicitation, this call first confirms that setting, then prompts for phone/region and PIN and completes login by itself; if the human says the setting is off, it returns the enabling steps without starting a login (relay them verbatim, then call login again). On clients without it (e.g. Claude Desktop), phone/region come from the arguments or a persisted login, and this returns as soon as LINE issues the PIN (or reports none needed) — then call login_complete IMMEDIATELY (do not wait for the human). LINE gives ~3 minutes from PIN display to confirm on the phone; login_complete blocks past that, so calling it late only wastes that window.
| Name | Required | Description | Default |
|---|---|---|---|
| phone | No | Phone number in E.164 form, e.g. +8869XXXXXXXX. Omit to be prompted (elicitation) or to reuse a persisted number. | |
| region | No | Region code, e.g. TW, JP, TH, ID, US. Omit to be prompted (elicitation) or to reuse a persisted region. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. Thoroughly explains flow: setting check, prompt sequence, client differences, PIN timeline, and blocking behavior of login_complete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is long but every sentence adds necessary context. Front-loaded with purpose, then layered details. Could be slightly tighter but complexity justifies length.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers prerequisites, client differences, parameter interactions, timing constraints, and error handling. No output schema but describes return behavior adequately. Complete for a complex login flow.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both parameters described). Description adds value by specifying E.164 format, region code examples, and clarifying that omitting parameters triggers prompting or reuse of persisted values.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Log in to LINE via the passwordless secondary-device flow.' Specifies verb and resource, and distinguishes from sibling tool 'login_complete' by describing their interaction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit when-to-use, prerequisites (setting on primary phone), handling of failure (setting off), client-specific behavior, and immediate follow-up requirement for login_complete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
login_completeA
Finish a passwordless login that login started on a client without form elicitation (not needed on form-elicitation-capable clients). No arguments. Call immediately after login returns — do not wait for the human. Blocks while they enter the PIN (skipped if a stored certificate is valid) and approve the device, then returns the profile. LINE's real deadline is ~3 minutes from PIN display. Errors if no login is pending.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses key behaviors: blocks while user enters PIN, skips if stored certificate valid, requires device approval, returns profile, and errors if no pending login. With no annotations, description fully covers the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single paragraph with front-loaded purpose, every sentence adds value (timing, blocking behavior, deadline, errors). No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers most essential aspects (flow, timing, errors) but lacks details about the returned profile structure. Without output schema, a bit more on what the profile contains would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist; description states 'No arguments.' Schema coverage is 100%, so no additional meaning needed. Baseline 4 for zero-parameter tools.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that this tool finishes a passwordless login initiated by 'login', specifies when it is needed (not on form-elicitation-capable clients), and distinguishes it from the sibling 'login' tool.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly instructs to call immediately after 'login' returns without waiting, mentions the 3-minute deadline, and warns of errors if no login is pending. Provides clear when-to-use vs. when-not (form-elicitation-capable clients).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
mark_readA
Send a LINE read receipt (mark a conversation read up to messageId, or the latest when omitted) — a real action the other party can see. Use ONLY when the user explicitly wants to mark a chat read; reading (get_chat_messages, get_unread_digest) and background capture never mark read. Fails honestly if there is nothing to mark.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID to mark read, as returned by list_conversations. | |
| messageId | No | Optional message id to mark read up to. Omit to mark read up to the latest message. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses real action visible to other party and honest failure. No annotations provided, so description carries full burden; covers key traits but could mention side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with action, no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a simple tool with no output schema; covers input semantics and behavioral impact. Slight gap on return value but acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline 3. Description adds explanation of messageId omission behavior, but does not significantly enhance schema info.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool sends a LINE read receipt, marks a conversation read up to a message ID, and distinguishes from reading tools like get_chat_messages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use ONLY when the user explicitly wants to mark a chat read' and names alternatives that do not mark read.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
preview_stickerA
Show sticker preview images (MCP image content from the public sticker CDN) so you and the user can SEE them before sending. Give a packageId (from list_stickers/search_stickers) to preview its first stickers, or add a stickerId to preview just one. Each image is labeled with its stickerId + packageId for send_sticker. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max stickers to preview when no stickerId is given (default 8). | |
| packageId | Yes | Sticker package id (STKPKGID) to preview. | |
| stickerId | No | Optional specific sticker id (STKID) to preview just that sticker. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Declares read-only nature and mentions it returns MCP image content from the public CDN. Without annotations, this covers basic safety but misses details like auth or rate limits. Adequate for a simple read operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences with no waste: purpose, usage guidance, and labeling info. Front-loaded with main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Complete for the tool's simplicity: explains what it does, how to use parameters, and what output looks like (images labeled). No output schema needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, baseline 3. Description adds value by explaining the relationship between packageId and stickerId, and mentions default limit. Goes beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it shows sticker preview images using MCP image content from the public sticker CDN, distinguishing it from siblings like send_sticker (sends) and list_stickers (lists metadata).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear usage context: give a packageId from list_stickers/search_stickers to preview stickers, or add a stickerId for a single sticker. Mentions labeling for send_sticker. Lacks explicit when-not or alternatives, but context is strong.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
react_messageA
Adds a reaction to a LINE message, visible to the conversation. reactionType: 2 = 👍 LIKE, 3 = ❤️ LOVE, 4 = 😆 LAUGH, 5 = 😮 SURPRISE, 6 = 😢 SAD, 7 = 😡 ANGRY (default 2). One reaction per call.
| Name | Required | Description | Default |
|---|---|---|---|
| messageId | Yes | LINE message id to react to, as returned by get_chat_messages. | |
| reactionType | No | Predefined reaction: 2=👍LIKE, 3=❤️LOVE, 4=😆LAUGH, 5=😮SURPRISE, 6=😢SAD, 7=😡ANGRY. Default 2. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries burden. Lists reactionType values and default, and mentions visibility. However, does not disclose side effects, permissions, or rate limits. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences: first for purpose, second for parameter enum. Front-loaded and no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Simple tool (2 params, no output schema). Description covers basic purpose and parameters but lacks usage context, return value (fire-and-forget?), or edge cases. Adequate for minimal viability.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%. Description adds value for messageId by noting it is 'as returned by get_chat_messages', providing context beyond the schema. However, reactionType info largely duplicates schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the action: 'Adds a reaction to a LINE message, visible to the conversation.' Specific verb (adds) and resource (reaction to LINE message). Distinguishes from sibling 'cancel_reaction' (which removes reactions) and other messaging tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives (e.g., cancel_reaction, unsend_message). Only mentions 'One reaction per call' but does not clarify use cases or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rename_groupA
Renames a LINE group/chat immediately; the new name is visible to every member. Works on groups/rooms (chatId starting with c/r). One rename per call.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | New group name. | |
| chatId | Yes | LINE group/room MID to rename, as returned by list_conversations. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of disclosing behavioral traits. It notes that the rename is 'immediate' and 'visible to every member', and restricts to chatId starting with c or r. It does not mention permissions, reversibility, or error cases, but provides adequate basic behavior for a simple mutation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences that cover purpose, effect, scope, and usage constraint. No redundant information, perfectly front-loaded with the core action. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (2 required params, no output schema), the description reasonably explains the effect and constraints. It could mention the response type or error handling, but it is sufficient for an agent to understand the tool's behavior. No output schema exists, but the description covers the essential outcome.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with both parameters described. The description adds extra value by specifying that chatId must start with 'c' or 'r', which is not in the schema. This helps the agent correctly format the chatId parameter beyond the schema's generic description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (renames) and the resource (LINE group/chat). It specifies that the new name is visible to all members, and distinguishes the tool by noting it works on groups/rooms with a specific chatId prefix, setting it apart from siblings like create_group.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: renaming a group/chat with a specific chatId prefix. It mentions 'one rename per call' to guide usage, but does not explicitly state exclusions or alternatives, which is acceptable as no sibling directly competes.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_messagesA
Search across your LINE messages. Hybrid ranking: FTS5 keyword search (covers every indexed message, so exact matches are never dropped) fused with semantic similarity when embeddings are available — the mode field reports which contributed (hybrid | semantic | keyword). If the index is empty and a session is live, it auto-collects all conversations first; a populated index searches locally with no network. Empty index with no session returns an honest notice, never a fabricated match list.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of results to return (default 20). | |
| query | Yes | Search query. Plain keywords and natural-language descriptions both work — keyword matching catches exact terms, semantic matching catches paraphrases. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses key behaviors: auto-collection on empty index with live session, hybrid ranking, mode reporting, and honest failure on empty index without session. This is thorough and transparent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat lengthy but each sentence adds valuable information. It is front-loaded with the core purpose and then details the behavior, making it efficient for an agent to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of hybrid search and auto-collection, the description covers the key behaviors well. While there is no output schema, it mentions the mode field, providing enough context for an agent to understand the return structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description adds meaningful nuance to the query parameter, specifying that plain keywords and natural-language descriptions both work. This goes beyond the schema's basic description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it searches across LINE messages with a hybrid ranking approach, and distinguishes itself from sibling tools like list_conversations and get_chat_messages by focusing on search functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit context for when the tool auto-collects versus searches locally, and mentions the behavior when the index is empty. However, it does not explicitly state when not to use this tool in favor of alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_stickersA
Search the account's OWNED sticker packages by title and expand each match into its individual sticker ids (STKID), ready for send_sticker. Case-insensitive substring match on the package title. Read-only.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max matching packages to expand with sticker ids (default 8). | |
| query | Yes | Substring to match against owned package titles (case-insensitive). | |
| language | No | Locale for package titles to match against, e.g. 'en' or 'zh-Hant'. Defaults to 'en'. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It explicitly states 'Read-only' and explains the expansion behavior. However, it does not detail output structure or edge cases like no matches.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, with three brief statements covering purpose, matching behavior, and read-only nature. No superfluous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of output schema and annotations, the description covers the main purpose and behavior well. It hints at the output (sticker IDs) but does not specify the exact structure, which is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, providing full parameter descriptions. The tool description adds no new information beyond the schema; it repeats the query substring match and limit defaults, so no added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches owned sticker packages by title and expands results into sticker IDs, ready for send_sticker. It specifies case-insensitive substring match, distinguishing it from list_stickers which likely lists all packages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates the output is ready for send_sticker, implying a use case. It does not explicitly mention when not to use or alternatives, but the context is clear enough for an agent to infer appropriate usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_audioA
Sends an E2EE audio message to a LINE conversation immediately (same pipeline as send_file). Provide exactly one of filePath or audioBase64; optional durationMs sets the recipient player length. Works for 1:1/group/room. One send per call.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID to send to, as returned by list_conversations. | |
| fileName | No | Optional original filename (used for the upload name; defaults to the basename of filePath or audio.m4a). | |
| filePath | No | Local filesystem path to the audio file. Mutually exclusive with audioBase64. | |
| durationMs | No | Optional audio duration in milliseconds, for the recipient player progress bar. | |
| audioBase64 | No | Base64-encoded audio bytes. Mutually exclusive with filePath. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states it sends an E2EE audio message immediately, but does not mention any required permissions, rate limits, or what happens on failure. The behavioral transparency is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the core purpose, and contains no superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a send tool with no output schema and 5 parameters, the description covers the key aspects: what it does, how to use params, and applicable conversation types. It could mention return value or error handling, but overall it is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3. The description adds value by clarifying mutual exclusivity between filePath and audioBase64, and explains that durationMs sets the recipient player length. This goes beyond the schema's individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('sends'), the resource ('E2EE audio message'), and the target ('LINE conversation'). It also notes it uses the same pipeline as send_file, which helps distinguish it from other send tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage guidance: 'Provide exactly one of filePath or audioBase64' and mentions optional durationMs. It specifies applicability to 1:1/group/room and that one send per call is allowed. However, it does not explicitly indicate when to use this tool versus alternatives like send_message or send_file.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_contactA
Shares a LINE contact card to a conversation immediately — the recipient sees a tappable card for contactMid (e.g. from find_contact or get_group_members). displayName is optional (resolved from the mid when omitted). Works for 1:1/group/room. One send per call.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID to send to, as returned by list_conversations. | |
| contactMid | Yes | MID of the person whose contact card to share, as returned by find_contact or get_group_members. | |
| displayName | No | Optional display name for the card. Resolved from contactMid when omitted. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the send is immediate, one per call, and displayName is optional (resolved from contactMid when omitted). It could mention permissions or error handling, but the key behavioral traits are covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main action, and contains no unnecessary words. Every sentence adds meaningful context.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 3 parameters (2 required) and no output schema, the description explains what the tool does, how to use it, and key constraints. It does not mention the response or success/failure signals, but for a side-effect tool, the information is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3. The description adds value by explaining chatId as a LINE chat/group/room MID, contactMid as coming from find_contact or get_group_members, and displayName's optional behavior. This enriches the schema definitions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool shares a LINE contact card to a conversation, specifying the action and resource. It distinguishes from sibling send tools like send_message or send_image by focusing on contact cards and referencing find_contact/get_group_members for the MID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly indicates the tool is for sharing contact cards and works in 1:1/group/room. It does not explicitly state when not to use it or mention alternatives, but the context from sibling tools makes the intended use case clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_fileA
Sends an E2EE file attachment (any type — .docx, .pdf, .zip, …) to a LINE conversation immediately (same pipeline as send_image; the original filename is sealed end-to-end). Works for 1:1/group/room; fails honestly if the key cannot be resolved or the upload is rejected. One send per call. Provide exactly one of filePath or fileBase64; fileName is required with fileBase64 (and overrides the basename when given with filePath).
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID to send to, as returned by list_conversations. | |
| fileName | No | Original filename shown to the recipient (sealed E2EE). Required with fileBase64; optional with filePath (defaults to its basename). | |
| filePath | No | Local filesystem path to the file. Mutually exclusive with fileBase64. | |
| fileBase64 | No | Base64-encoded file bytes. Mutually exclusive with filePath; requires fileName. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description fully discloses behavioral traits: E2EE, filename sealed, same pipeline as send_image, honest failure, one send per call, and mutual exclusivity of filePath/fileBase64. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. First sentence covers core action and scope; second sentence adds edge cases and constraints. Efficiently structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description adequately sets expectations (send succeeds or fails honestly). It covers the key aspects needed for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds significant value: clarifies mutual exclusivity of filePath/fileBase64, fileName requirement with fileBase64, and default behavior with filePath. This exceeds the schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it sends an E2EE file attachment to a LINE conversation, specifies supported file types, and distinguishes by noting it uses the same pipeline as send_image. This provides a specific verb+resource and differentiates from siblings like send_message and send_image.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explains when to use (sending files) and mentions failure conditions (key resolution/upload rejection). It doesn't explicitly state when not to use or list alternatives, but the guidance is sufficient for correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_imageA
Sends an E2EE image to a LINE conversation immediately (encrypt → upload to OBS → send). Works for 1:1/group/room; fails honestly if the key cannot be resolved or the upload is rejected. One send per call. Provide exactly one of imagePath or imageBase64.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID to send to, as returned by list_conversations. | |
| imagePath | No | Local filesystem path to the image file. Mutually exclusive with imageBase64. | |
| imageBase64 | No | Base64-encoded image bytes. Mutually exclusive with imagePath. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses behavioral traits: the E2EE encryption process, the upload to OBS, failure conditions ('fails honestly'), and the limitation of one send per call. This exceeds the minimum required for transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (three sentences) with front-loaded action and no extraneous details. Every sentence adds value: purpose, constraints, and parameter guidance.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool sends an image and has no output schema, the description covers essential aspects: encryption, upload, target types, failure cases, and input constraints. It lacks details on return values (e.g., success indicator) but is sufficient for most agents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides 100% coverage with descriptive parameter descriptions. The description adds value by explicitly stating 'Provide exactly one of imagePath or imageBase64', reinforcing the mutual exclusivity constraint. This is helpful but not critical given the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'sends' and the resource 'E2EE image' with a detailed workflow (encrypt → upload → send). It specifies the target conversation types (1:1/group/room) and distinguishes from other send tools by focusing on images with E2EE.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context on when to use this tool: for immediate sending of a single encrypted image. It mentions failure conditions (key resolution, upload rejection) and the constraint 'one send per call'. However, it does not explicitly mention when not to use it (e.g., for multiple images) or suggest alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_locationA
Sends a location (map pin) to a LINE conversation immediately — latitude/longitude plus optional title (place name) and address. Works for 1:1/group/room. One send per call.
| Name | Required | Description | Default |
|---|---|---|---|
| title | No | Optional place name shown on the pin. | |
| chatId | Yes | LINE chat/group/room MID to send to, as returned by list_conversations. | |
| address | No | Optional address shown under the pin. | |
| latitude | Yes | Latitude in decimal degrees. | |
| longitude | Yes | Longitude in decimal degrees. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions 'immediately' and 'One send per call,' but does not disclose rate limits, permissions, or side effects. Some useful context, but incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, no wasted words. The first sentence covers the action and parameters, the second covers scope and limit. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters and no output schema, the description covers the essential action and constraints. However, it does not mention what is returned (e.g., success indication or message ID), leaving a potential gap for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%. The description adds 'place name' for title and 'address shown under the pin,' which clarifies semantics beyond the schema. Baseline of 3 is exceeded by this additional nuance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it sends a location (map pin) with latitude/longitude and optional title/address, and specifies it works for 1:1/group/room. This differentiates it from sibling tools like send_message or send_image.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates immediate sending and limits to one send per call, which provides context. However, it does not explicitly compare to alternatives or provide when-not-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_messageA
Sends a text message to a LINE conversation immediately (not a draft). Always E2EE (pairwise for 1:1, group key for group/room); fails honestly rather than sending plaintext if the key cannot be resolved. One send per call. To @mention someone, put the visible "@name " into text AND pass a matching mentions entry — without mentions, "@name" is plain text and notifies no one. Resolve MIDs via get_group_members or find_contact first.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Plain-text message body, including the literal "@name" text for any mentions — mentions only mark up text that is already there. | |
| chatId | Yes | LINE chat/group/room MID to send to, as returned by list_conversations. | |
| mentions | No | Optional @mentions. Each entry marks a span of `text` as a mention of one user, which LINE highlights and notifies. Omit to send `text` as plain, non-notifying text. | |
| replyToMessageId | No | Optional message id (from get_chat_messages) this replies to — LINE renders a quoted reply. Omit for a normal message. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description fully discloses critical behaviors: immediate sending (not a draft), E2EE handling ('fails honestly rather than sending plaintext'), per-call limitation ('One send per call'), and mention mechanics. This level of detail is essential for an AI agent to understand the tool's side effects and constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is dense with useful information, but every sentence serves a purpose—no fluff. It is slightly long but front-loaded with the core action and then details. Structured logically: main action, then E2EE, then mentions, then dependencies. Could be trimmed slightly but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity and the set of sibling tools (31 tools including send_image, send_file, etc.), this description fully equips the agent. It addresses all relevant concerns: immediate sending, mentions prerequisites, E2EE safety, and how to obtain needed MIDs. No output schema is needed for this action.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although schema coverage is 100%, the description adds substantial meaning: it explains the relationship between the text parameter and mentions entries, specifies UTF-16 code units for offsets, and clarifies that replyToMessageId makes a quoted reply. It also instructs how to obtain MIDs for mentions, which is not in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Sends a text message to a LINE conversation immediately (not a draft)', uses a specific verb ('sends'), identifies the resource ('LINE conversation'), and distinguishes from related tools like send_image or send_file by focusing on text messages. It also clarifies behavioral nuances like E2EE and mentions, making the purpose unmistakable.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear guidance on when to use: for immediate text messages. It explains prerequisites for mentions ('resolve MIDs via get_group_members or find_contact first') and correct usage ('put the visible "@name " into text AND pass a matching mentions entry'). It does not explicitly state when to avoid this tool, but the context of sending text versus other media is implied.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_stickerA
Sends a LINE sticker to a conversation immediately, named by stickerId (STKID) + packageId (STKPKGID). Only OWNED stickers can be sent — get ids from search_stickers/list_stickers. Works for 1:1/group/room. One send per call.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID to send to, as returned by list_conversations. | |
| version | No | Sticker version (STKVER). Defaults to "1". | |
| packageId | Yes | LINE sticker package id (STKPKGID). | |
| stickerId | Yes | LINE sticker id (STKID). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It states immediate sending and per-call limitation. It could mention if a response is returned, but overall sufficiently transparent for a simple send operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no redundant words. The core action is front-loaded, and each sentence provides necessary information. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 4 parameters, no output schema, and no nesting, the description covers all essential aspects: input requirements, usage restrictions, and conversation types. It is complete enough for an agent to use correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so baseline is 3. The description adds context by explaining the naming convention (STKID, STKPKGID) and version default, but the schema descriptions are already adequate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool sends a LINE sticker to a conversation, specifying the exact identifiers (stickerId and packageId). It distinguishes itself from sibling tools like send_message by focusing on stickers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly mentions that only owned stickers can be sent and directs the agent to search_stickers/list_stickers for IDs. Also specifies scope (1:1/group/room) and limit (one send per call), providing clear when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
send_videoA
Sends an E2EE video to a LINE conversation immediately (same pipeline as send_file; uses LINE chunked video encryption so it plays and integrity-verifies on official clients). Provide exactly one of filePath or videoBase64; optional durationMs sets the scrubber length. Works for 1:1/group/room. One send per call.
| Name | Required | Description | Default |
|---|---|---|---|
| chatId | Yes | LINE chat/group/room MID to send to, as returned by list_conversations. | |
| fileName | No | Optional original filename (used for the upload name; defaults to the basename of filePath or video.mp4). | |
| filePath | No | Local filesystem path to the video file. Mutually exclusive with videoBase64. | |
| durationMs | No | Optional video duration in milliseconds, for the recipient player scrubber. | |
| videoBase64 | No | Base64-encoded video bytes. Mutually exclusive with filePath. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses encryption (E2EE, LINE chunked video encryption) and immediate delivery. No annotations provided, so description carries full burden. Missing rate limits or error behavior, but key traits are covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: first defines purpose and encryption, second parameter constraints, third target types and send limit. No redundancy, all information earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all key aspects for a send tool with 5 parameters and no output schema. However, does not describe the return value or confirm success/failure signaling, leaving a small gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Adds value beyond schema by stating mutual exclusivity of filePath and videoBase64, explaining durationMs sets scrubber length, and noting fileName default behavior. Schema coverage is 100%, so baseline is 3; description elevates to 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Sends an E2EE video to a LINE conversation immediately' with specific verb and resource. Could better differentiate from other media tools like send_audio or send_image, which are siblings.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides explicit constraints: 'Provide exactly one of filePath or videoBase64', 'Works for 1:1/group/room', 'One send per call'. However, no guidance on when to use this vs. send_file, send_audio, etc., leaving the agent to infer.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
unblock_contactA
Unblocks a previously blocked contact for your LINE account. Undoes block_contact. One unblock per call.
| Name | Required | Description | Default |
|---|---|---|---|
| mid | Yes | MID of the contact to unblock. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States 'One unblock per call' (a behavioral constraint). However, lacks disclosure of side effects, required permissions, or error handling (e.g., if contact is not blocked).
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the main action. No unnecessary words. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with one required param and no output schema. Description covers the function and its relationship to block_contact. Could mention what happens if mid is already unblocked, but not essential for a basic tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, and the description only repeats the schema's param description ('MID of the contact to unblock'). No additional semantic context beyond what schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Unblocks a previously blocked contact for your LINE account.' Specific verb (unblocks) and resource (contact). Explicitly pairs with block_contact sibling, distinguishing it.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Undoes block_contact.' This directly tells the agent when to use this tool (when you have a blocked contact to unblock) and identifies the related alternative (block_contact).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
unsend_messageA
Retracts (unsends) one of YOUR OWN LINE messages for everyone — deletes it from the conversation for all participants and CANNOT be undone. LINE allows unsending only your own messages. SAFETY GATE: you must pass confirm: true, or the call refuses so it can never fire by accident. One unsend per call.
| Name | Required | Description | Default |
|---|---|---|---|
| confirm | Yes | Must be true to proceed. Retraction is irreversible; the call refuses unless this is explicitly true. | |
| messageId | Yes | LINE message id to retract (must be your own), as returned by get_chat_messages. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description fully discloses irreversible action, deletion for all participants, requirement for own messages, safety gate (confirm: true), and one unsend per call. Thorough and accurate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise sentences, no superfluous words, well-structured with key information upfront.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers all essential aspects: action, scope, safety, constraints. No output schema needed for a void action. Complete for its complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema already describes both parameters with 100% coverage. Description adds value by specifying that messageId comes from get_chat_messages and explaining the confirm requirement's purpose (irreversibility safety).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly specifies the action (retracts/unsends), the resource (your own LINE messages), and the effect (deletes for all participants). Distinguishes from sibling tools like send_message or react_message.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context: only own messages, one unsend per call. Implicitly tells when to use (to undo a sent message). No explicit alternatives or when-not-to-use, but sibling tools don't have similar functionality, so it's acceptable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
39 tool updates
v0.4.1- Added
accept_invitation - Added
add_friend - Added
cancel_reaction - Added
collect_messages - Added
create_group - Added
exclude_chats - Added
find_contact - Added
get_chat_messages - Added
get_group_members - Added
get_insight - Added
get_message_image - Added
get_message_media - Added
get_scope_policy - Added
get_unread_digest - Added
include_chats - Added
invite_member - Added
kick_member - Added
leave_group - Added
list_contacts - Added
list_conversations - Added
list_excluded_chats - Added
list_stickers - Added
login_complete - Added
mark_read - Added
preview_sticker - Added
react_message - Added
rename_group - Added
search_messages - Added
search_stickers - Added
send_audio - Added
send_contact - Added
send_file - Added
send_image - Added
send_location - Added
send_message - Added
send_sticker - Added
send_video - Added
unblock_contact - Added
unsend_message
38 tool updates
v0.3.0- Removed
accept_invitation - Removed
add_friend - Removed
cancel_reaction - Removed
collect_messages - Removed
create_group - Removed
exclude_chats - Removed
find_contact - Removed
get_chat_messages - Removed
get_group_members - Removed
get_message_image - Removed
get_message_media - Removed
get_scope_policy - Removed
get_unread_digest - Removed
include_chats - Removed
invite_member - Removed
kick_member - Removed
leave_group - Removed
list_contacts - Removed
list_conversations - Removed
list_excluded_chats - Removed
list_stickers - Removed
login_complete - Removed
mark_read - Removed
preview_sticker - Removed
react_message - Removed
rename_group - Removed
search_messages - Removed
search_stickers - Removed
send_audio - Removed
send_contact - Removed
send_file - Removed
send_image - Removed
send_location - Removed
send_message - Removed
send_sticker - Removed
send_video - Removed
unblock_contact - Removed
unsend_message
40 tool updates
v0.2.0- First observed
accept_invitation - First observed
add_friend - First observed
block_contact - First observed
cancel_reaction - First observed
collect_messages - First observed
create_group - First observed
exclude_chats - First observed
find_contact - First observed
get_chat_messages - First observed
get_group_members - First observed
get_message_image - First observed
get_message_media - First observed
get_scope_policy - First observed
get_unread_digest - First observed
include_chats - First observed
invite_member - First observed
kick_member - First observed
leave_group - First observed
list_contacts - First observed
list_conversations - First observed
list_excluded_chats - First observed
list_stickers - First observed
login - First observed
login_complete - First observed
mark_read - First observed
preview_sticker - First observed
react_message - First observed
rename_group - First observed
search_messages - First observed
search_stickers - First observed
send_audio - First observed
send_contact - First observed
send_file - First observed
send_image - First observed
send_location - First observed
send_message - First observed
send_sticker - First observed
send_video - First observed
unblock_contact - First observed
unsend_message
TDQS
Most tools have distinct purposes, but there is some overlap: get_message_image is a legacy alias of get_message_media, which could cause confusion. Also, collect_messages and search_messages are related but serve different roles (indexing vs querying). Overall, boundaries are clear.
Tool names predominantly follow verb_noun pattern (e.g., list_stickers, send_message), but there are minor deviations like login (not login_user) and get_insight (unconventional verb). Overall, consistent enough for an agent to predict patterns.
41 tools is a large surface area, but LINE is a feature-rich platform. Some tools could be consolidated (e.g., send_media variants into a single tool with a type parameter). The count feels slightly excessive for the domain.
The tool set covers all major LINE operations: messaging (text, image, video, audio, file, location, contact, sticker), group management (create, rename, invite, kick), contact management, reactions, unsend, search, privacy controls, and login flow. No obvious gaps.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
WhatsApp CRM for AI agents: search contacts, read chats, manage the sales pipeline, send messages.
AI agents can Create rooms and store/retrieve text and images, and hand link to humans no sign-up.
Managed LinkedIn MCP server for AI agents: search, connect, message and enrich on accounts you own.
Disposable email inboxes for AI agents — read messages and verification codes.
Related MCP Servers
- AlicenseBqualityDmaintenanceEnables AI agents to send messages, manage rich menus, and interact with users through LINE Official Accounts via the LINE Messaging API. Supports both individual messaging and broadcasting to all followers with text and customizable flex messages.18767Apache 2.0
- AlicenseAqualityDmaintenanceIntegrates the LINE Messaging API with AI agents via the Model Context Protocol, supporting both stdio and SSE transport protocols. It allows agents to send messages, manage rich menus, and retrieve user profile information for LINE Official Accounts.10767Apache 2.0
- AlicenseAqualityBmaintenanceOperate your LINE Official Account from any AI agent through natural language.378297MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI tools to read and send messages through LINE Desktop via MCP, supporting manual or automatic sending without official LINE API tokens.59111MIT
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/RikaiDev/yomi'
If you have feedback or need assistance with the MCP directory API, please join our Discord server