knos
Knos is a local MCP server that gives coding agents shared repo memory and coordination through three tools.
search: query the machine's memory of the repo (past sessions, commits, code structure); results cite their source, and work another agent has claimed is withheld unless you provide an
overridereason, which is recorded.about: get what is known about a specific file, person, or topic.
remember: write a fact for future sessions; set
claimingto signal you are starting work, which withholds that item from other agents until you finish or 30 minutes pass.
Knos
Two contributors, or two agents, changing the same thing without knowing it. Knos is the record of who is on what, and it refuses to answer about work somebody else has already taken.
Read this first
Three MCP tools over stdio, one SQLite file, no server and no network. What
makes it different from a memory is that it refuses: ask about work
another agent claimed and there is no answer, only who has it. With
knos guard --install the refusal reaches the edit itself.
Where the memory is read and written. One file, ~/.knos/<repo>/memory.db,
through Sibyl. Every arrow below
is a call site you can open, and
tests/test_sibyl_is_load_bearing.py
deletes the file and asserts the product stops working.
flowchart LR
CLAIM["knos claim"] -->|"claim_if_free"| DB[("memory.db<br>one SQLite file")]
TELL["knos remember"] -->|"record, note_thing"| DB
READ["knos point<br>git log, CLAUDE.md, sessions"] -->|"note_thing"| DB
DB -->|"search"| ASK["MCP search / about<br>withheld if claimed"]
DB -->|"claims"| GUARD["guard.check<br>refuses the edit"]
DB -->|"things, claims"| EXP["knos export<br>.knos/decisions.md"]
DB -->|"journal, only_here"| ST["knos status"]
style DB fill:#1f2933,stroke:#7b8794,color:#ffffff
style ASK fill:#fdf0e8,stroke:#a5744a,color:#111111
style GUARD fill:#fdf0e8,stroke:#a5744a,color:#111111Written on the left, read on the right. Delete the box in the middle and everything on the right stops — that is the whole of what "load-bearing" means here, and it is a test rather than a sentence.
Tier | What lives there | Written by | Read by |
HOT | the live claim, one row per topic, overwritten |
|
|
WARM | decisions, files, named things |
|
|
COLD | the journal: what you told it, who stood down, every override |
|
|
Sibyl's five tiers are used for what they are, not as one key-value bucket: a claim is about now and is overwritten, a decision is a named thing replaced in place, and history is only ever appended to.
flowchart TD
subgraph DB["memory.db - hard cap 5 MB, Sibyl's free tier"]
HOT["HOT - the live claim<br>one row per topic, overwritten<br>lapses after 30 min"]
WARM["WARM - decisions, files, entities<br>named, replaced in place"]
COLD["COLD - the journal<br>append-only: told, stood down, overridden"]
end
HOT -->|"a second agent asks"| NO["withheld<br>+ who holds it"]
WARM -->|"knos ask"| SRC["answer + file and line"]
COLD -->|"knos status"| ONLY["how many things exist nowhere else"]
DB -->|"from 4 MB"| FULL["nearly full<br>at 5 MB a claim is refused in words,<br>never dropped"]
style DB fill:#1f2933,stroke:#7b8794,color:#ffffff
style HOT fill:#2b3a44,stroke:#7b8794,color:#ffffff
style WARM fill:#2b3a44,stroke:#7b8794,color:#ffffff
style COLD fill:#2b3a44,stroke:#7b8794,color:#ffffff
style FULL fill:#f5f5f5,stroke:#999999,color:#111111Five things here that are not elsewhere. Each one is a link, and each one is a command or a test rather than a claim:
A claim withholds the answer, instead of attaching a warning to it. Every other tool's claim is advisory.
The guard refuses the edit in Claude Code, Cursor and OpenCode — through their hooks, which are not MCP.
A hold is bound to the connection that made it, so an agent naming itself the holder is still refused.
Every worktree is one memory, because the store is keyed on
git rev-parse --git-common-dir. Tools that key on the worktree root fragment a repo's memory once per tree.Delete the store and the product stops. Not degrades — stops.
The three stacks, and what each one actually does here.
Stack | What it does in this repo | Where | Check it without installing anything |
Sibyl Memory | the store. Every claim, answer, journal entry and export goes through it. Required. |
|
|
Base |
| contract | |
Virtuals | a Telegram bot that is also a registered ACP provider: it sells one answer out of this store, and pays over x402 for a brief it writes back with | the agent page, and job 75659 in two legs: escrow funded, provider paid |
Base and Virtuals are optional and off by default — Knos runs with both
switched off, and nothing on the read or answer path touches a network
(tests/test_no_network.py). Every job traded
through the Virtuals provider was bought by a test agent of mine, not by a
customer. Details, including what each one does not do:
The two onchain parts.
flowchart TD
DB[("memory.db<br>Sibyl - required")]
SHARE["knos share ./src --with alice"] -->|"who may read what"| BASE["Base Sepolia<br>Access.sol"]
BASE -->|"may_read"| DB
BUY["/brief BTC"] -->|"0.01 USDC over x402<br>Base mainnet"| SELLER["a paid endpoint"]
SELLER -->|"knos remember - the receipt<br>exists nowhere else"| DB
DB -->|"knos ask"| SELL["Virtuals ACP offering<br>sells one answer"]
OFF["both switched off - the default"] -.->|"knos still works"| DB
style DB fill:#1f2933,stroke:#7b8794,color:#ffffff
style OFF fill:#f5f5f5,stroke:#999999,color:#111111,stroke-dasharray: 4 3Every one of those arrows ends at the same SQLite file. That is the point of
including them at all: the commerce leg is not a second system beside the
memory, it reads and writes the one store, and
pytest tests/test_sibyl_is_load_bearing.py takes the file away and asserts
none of it works.
The whole loop, in under a minute
pip install knos && knos connect # once, per machine
knos claim "the parser" # agent A takes it
# ask any other agent about the parser — it is refused, and told who has it
knos done # give it back
knos export # writes .knos/decisions.md, commit itClaim, be refused, release, export. The Action then does the same thing on a pull request, for people who have never installed Knos.
All of it runs without an editor open, as two real processes against one
store: pytest tests/test_intent.py -k two_processes. The other half of the
proof is tests/test_sibyl_is_load_bearing.py,
which takes the store away and asserts that both the withholding and the
answers die with it.
Under it is a local MCP server: three tools over stdio — search, about,
remember. No HTTP server, no ports, no account, no model download, no repo
to register, and no network connection at all:
that last one is a test, not a promise.
knos connect adds Knos to Claude Code, Claude Desktop, Cursor
and OpenCode — whichever you have, each in the shape it reads
(mcpServers for the first three, mcp with "type": "local" for
OpenCode). For Claude Code it runs claude mcp add --scope user, which
registers the server with the session you are already in, so its tools work
immediately with nothing to restart.
For the other three, knos connect writes the config, takes a backup, and
prints the one thing left to do: quit the app and start it again.
Nothing in the MCP spec lets a server register itself with a session that
is already running. The exact keystroke per client, the Claude Desktop
extension, the Claude Code plugin and the by-hand JSON are all in
docs/connect.md.
The first thing an agent asks about a repo reads it. Seven cold runs each,
whole process, Windows on a spinning disk (WSL on the same box: 3.4s median on a small repo): 1.7s median on a small project (1.5-2.1),
2.0s on goose (1.8-3.4), 3.1s on the Linux kernel (3.0-6.8) — 93,703 tracked
files. What it does in that time is one git log, your CLAUDE.md, and the
transcripts of past sessions in that tree, written to SQLite. It happens once. Every question after it is
under 0.2s, and every agent you have shares the result.
Related MCP server: memmd-mcp
What a claim does here
Claude Code is rewriting the risk guard. You ask Cursor about it.
Every tool in the table below answers, and Cursor gives you a confident plan built on the version that was on disk five minutes ago. Knos does this instead:
Withheld. risk guard (held by Claude Code) is being worked on right now,
so knos is not the place you find out about it. Ask them, or work on
something else.Not a warning attached to the answer — no answer. Your agent can still
take it, by saying why, and the reason is written down under its name where
you will read it. knos done releases it, and so does half an hour.
knos guard --install takes that one step earlier: the same claim, consulted
when an agent reaches for the file rather than when it asks a question, so the
edit itself is refused. Claude Code, Cursor and OpenCode all run a hook before
a tool call and a hook can say no. It is off until you ask for it, and
knos guard --uninstall takes it back out — details in
What it cannot do.
What a claim covers. A claim and a question are treated as the same
subject when they share a word stem, and identifiers are split into their
parts first, so a claim on the risk guard covers risk_guard.py. The
claim is matched against the passages the question would have returned as
well as against the question itself, so rewording the question does not get
past it — asking why do we cap trades? while the risk guard is claimed
is withheld like the plain question. This is word matching, not meaning: a
question that shares no stem with the claim and returns no passage that
does will still be answered. Check it:
pytest tests/test_intent.py -k "paraphrased or reaches_the_file".
search withholds. about is a named lookup and does not: it answers, with
the holder's name and how long ago they started shown above the answer.
Every cell below comes from that tool's own README or documentation page, so you can check each one:
To install | MCP tools | Needs | Refuses to answer about work another agent claimed | |
| — | — | nothing | no |
| 54 (8 in core mode) | a server on ports 3111/3112/3113/49134 | no — | |
npx entry in your config | 18 | may download an embedding model | no | |
| 16 | nothing — one binary | not addressed | |
| 45 | ~300 MB embedding model | no — separate wings per agent | |
| 3 per bank | Postgres + pgvector + an LLM API key | no — banks are isolated by design | |
remote MCP URL + an account | claim/release, check_conflicts, remember/recall, task board | a hosted server | no — its own page: "cooperative, not enforced — a rogue agent can still ignore it" | |
| 52 | a coordination server running | no — | |
| 9 | nothing — one SQLite file | not addressed | |
npx entry in your config | 3 | nothing | no — and it is not a memory system: claims only, no sessions or decisions | |
| 45 (plus 25 resources) | a listener on 127.0.0.1:8765 | no — reservations are advisory; its git hook blocks a commit, and the memory stays fully readable | |
Knos |
| 3 | nothing | yes |
Knos is not the only tool with claims, and that column would be dishonest if it implied so. Vibsync, CoordMCP, AgentRoom and Agent Claim MCP all let an agent claim something; agentmemory has leases. The difference is what a claim does. Everywhere else it is a signal about a file, which an agent may check before editing and may ignore — Vibsync says so itself, and CoordMCP's locks stop edits while the memory stays fully readable. Knos changes what the memory says: ask about work someone else claimed and there is no answer to act on, and the claim is bound to the connection that made it, so an agent naming itself the holder is still refused.
Three of these are worth your attention for reasons other than that column.
Memryzed is local, keyless and one SQLite file — the same shape as Knos, with
more recall tools and no coordination. Vibsync is the only one that shares a
claim across machines, which Knos does not: a committed .knos/decisions.md
is as far as a claim travels here. Agent Mail is the closest thing to a
competitor on enforcement, and on one axis it goes further than Knos: its
pre-commit git hook refuses a commit that touches files another agent has
reserved. Knos refuses the answer; Agent Mail refuses the commit, by which
point the work is already done. Neither of them stops the keystroke. Both are
worth knowing about, and Agent Mail costs a listener on port 8765 and 45 tools
where this costs neither.
Knos is not trying to out-remember these tools. It is trying to be the one that speaks up while two agents are in the same code, and to cost you two commands and three tools to find out.
One agent is enough to see it
knos claim "the parser"Ask your agent about the parser. It is refused, and tells you so. knos done
and it answers again. That is the whole mechanism, in two commands.
flowchart TD
P["pip install knos<br>knos connect"] --> CC["Claude Code"]
P --> CU["Cursor"]
P --> CD["Claude Desktop"]
P --> OC["OpenCode"]
CC -->|"first question reads the repo"| S[("one SQLite file<br>no server, no model")]
CU --> S
CD --> S
OC --> S
R["CLAUDE.md, AGENTS.md, ADRs<br>commits, past sessions"] --> S
W["every worktree of this repo"] --> S
S -->|"answers, with the source"| CC
S -->|"withheld - Claude Code is on it"| CU
style S fill:#1f2933,stroke:#7b8794,color:#ffffff
style P fill:#e8f0fe,stroke:#4a6fa5,color:#111111
style R fill:#f5f5f5,stroke:#999999,color:#111111
style W fill:#f5f5f5,stroke:#999999,color:#111111Every arrow above is a command you can run: the withheld one is
knos claim "the parser" then asking a second agent, and
pytest tests/test_intent.py -k withholds_the_answer is the same thing as a
test.
What breaks without the store
Every capability below reads or writes the one SQLite file. The middle column
is the command that exercises it; the right column is where it touches the
store. pytest tests/test_sibyl_is_load_bearing.py takes the file away and
asserts the first three rows stop working.
Capability | Run it | Where it touches the store |
A claim is taken, once, atomically |
|
|
A second agent is refused | ask any other agent about it |
|
Who stood down, and who overrode |
| COLD journal via |
What you told it |
|
|
Decisions shared with the repo |
| WARM + HOT read out into |
A brief bought over x402 |
|
|
An ACP deliverable | a buyer funds a job |
|
How full it is, and what dies |
|
|
The claim lives in HOT because it is about now and is overwritten, not
appended. Decisions live in WARM because they are named things replaced in
place. History lives in COLD because it is append-only. That is Sibyl's
schema used as intended rather than as a key-value bucket, and knos status
prints the tiers by name.
How memory made this possible
Knos is not a tool that happens to save things. Take Sibyl out and there is no product left to run.
The claim lives in the store. That is the whole mechanism: one agent writes that it is changing something, and another agent whose question or whose answer touches that subject is handed the holder's name instead. Delete the file and there is nothing to read, so nothing is withheld, so two agents edit the same thing and neither is told. The refusal is not a rule enforced in code somewhere else — it is a read of the store, and it fails when the read fails.
The same file is the only copy of three other things. What you told it with
knos remember. The brief the agent paid for over x402, which was bought
once and exists nowhere else on the machine. The ACP job it sold, and what it
sold. Your commits and your CLAUDE.md come back after a delete, because
those are your files; none of these do.
knos status prints that number directly — how many things exist nowhere
else. The table in What breaks without the
store names the call site for each one, and
tests/test_sibyl_is_load_bearing.py
runs the test a sceptic would run first: remove the memory, watch the
product fail.
Share it with the repo, not a server
Everything above is local. Two things, though, exist nowhere a teammate can reach — what somebody decided, and what somebody is working on right now. So those go in the repository, as a file you commit:
knos export # writes .knos/decisions.md
git add .knos && git commit -m "share decisions"If your repo already keeps decisions somewhere, write there instead:
knos export --to docs/decisions/0001-knos.mdKnos reads .knos/decisions.md, DECISIONS.md, WORKLOG.md and
docs/adr/*.md back on the next question, so any of those close the loop
with no configuration. Anywhere else is still written and still worth
committing, and knos export tells you it will not be read back rather than
letting you find out later.
That one file is the whole mechanism. It is markdown, it diffs in review, and three different kinds of reader consume it without installing anything:
A teammate clones and asks.
.knos/decisions.mdis one of the decision records Knos already reads, so a clean clone answers from it on its first question — no install, no sync, no account, no server between the two machines (pytest tests/test_shared_repo.py -k second_clean_clone).Every agent on their machine reads it too, through the same three MCP tools, on the same first question. A contributor who has never heard of Knos still gets your decisions, because their agent asks and the file is already in the checkout.
CI reads it on a pull request and says so when the branch touches work somebody has claimed (
pytest tests/test_shared_repo.py -k ci_warns).
The comment is a heads-up, never a failure — action/knos_pr_check.py
exits 0 on every path, including when it finds a conflict and when it
crashes. The workflow is eight lines:
The pull request check.
It runs both ways, and that is the part that compounds. The teammate who
cloned runs knos export too. Their decisions and their claims land in the
same file, you pull, and your agents read what they decided while you were
not looking. Every contributor writes to the file and reads from it, so it
holds more after each one than before. The repository is the shared object:
there is no database of ours, no protocol to adopt, and no server to pay
for.
Secrets do not travel: a note about .env is filtered out of the exported
file by the same check that hides .env from an agent
(pytest tests/test_shared_repo.py -k private_note).
Nothing outside this repository has adopted it yet. The loop is
implemented and tested, six tests in tests/test_shared_repo.py. That is a
mechanism that works, not a network that exists.
The pull request check
Everything above is local. This is the half that needs nothing installed — one file in your repo, and it never fails a build:
# .github/workflows/knos-claims.yml
on: [pull_request]
permissions: { contents: read, pull-requests: write }
jobs:
claims:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: drexthealpha/Knos/action@v0.1.5It reads .knos/decisions.md — a file a maintainer commits — and comments
when a branch touches work somebody has claimed or a decision already
recorded. It exits 0 on every path, including every failure path
(pytest tests/test_shared_repo.py -k never_returns_non_zero). The tag is
pinned rather than a branch, so what runs in your CI is a fixed file you can
read: git show v0.1.5:action/knos_pr_check.py.
You can watch it having run rather than take this on trust: it fired on
pull request #1 in this
repository, matched a claim standing in .knos/decisions.md, named who held
it, and exited 0. The comment is still on the thread.
The three folders, so nothing here is a surprise. src/knos/ is the
product: the MCP server, the claim, the withhold, knos export. action/ is
the pull request check above. agent/ is a Telegram bot that is also a
registered Virtuals agent — it pays for things over x402 on Base and sells
answers as ACP jobs, and every one of those paths reads and writes the same
store. It is the commerce leg, not the product; Knos works with it switched
off, which is the default. contracts/ is one Solidity file behind
knos share. Details in The two onchain parts.
pull_request_target works too, if you want the check on pull requests from
forks: the Action reads only the committed .knos/decisions.md and the pull
request's own title, body and file list, and never checks out or runs
anything from the head branch.
Who this is for, and the pain they have written down
The audience is maintainers and contributors on repositories where more than one coding agent touches the same tree — a person running Claude Code in the terminal and Cursor in the editor, a team whose contributors point agents at the same issue, or a repository that accepts agent-written pull requests. They share one failure: two agents change the same thing, neither is told, and it surfaces at merge.
Nothing below is about Knos. These are their own open issues, in their own repositories, filed by people who have never heard of it. Every one was open when this was written; each link resolves in a click.
Repository | Stars | The issue |
openai/codex | 121k | |
openai/codex | 121k | Automatically isolate and coordinate concurrent writes across chats and agents |
anthropics/claude-code | 144k | Subagent exceeded scope and executed an unauthorized git commit |
openclaw/openclaw | 389k | |
CopilotKit/CopilotKit | 37k | Agents mutate a shared singleton per-request; concurrent users leak system prompts |
omnigent-ai/omnigent | 9.7k | Session-state writes race under concurrent updates: lost updates and orphan rows |
microsoft/winappCli | 1.2k | |
microsoft/winappCli | 1.2k |
The first two are the sharpest: openai/codex has an open request for a
record of what each agent intends to edit, so that two of them do not edit
the same thing. That is the mechanism in What a claim does
here, asked for by somebody else, in a repository
with 121,000 stars.
One repository coordinating agents through a GitHub issue, today
tsz-org/tsz runs its agents against a claim board:
issue #17314, open, with 1,133
comments. It succeeded #15994,
which was forked after hitting the 2,500-comment cap. Agents post CLAIM,
DONE, DROP and BLOCK lines and are expected to read the thread before
starting, and its standing notes record what goes wrong: sessions that end on
a live claim with no closing record, and two claims naming one defect in
different words.
That is this product's job, done by hand in a comment thread, at a size where reading it before every edit has stopped being possible.
What this is and is not. It is evidence that the problem is real and that
people with large audiences have written it down. It is not evidence that
anybody uses Knos. No repository outside this one has adopted it. The
loop is implemented and tested — six tests in tests/test_shared_repo.py —
which makes it a mechanism that works, not a network that exists.
Check any of it in under a minute
Nothing here is a claim. Each row is a command; run it and see. The
commands are checked by a test, so a renamed test fails the suite rather
than leaving a dead instruction here
(pytest tests/test_cli.py -k every_check_command).
What | How to check it yourself |
A claim changes what other agents are told |
|
One agent's claim reaches another agent's live session, with no restart or cache |
|
No network connection, ever |
|
Decisions you keep in the repo are read |
|
Every worktree of a repo is one memory |
|
A big repo is never half-read |
|
Secrets are invisible, not redacted |
|
Three MCP tools, no more |
|
Two agents cannot both hold the same claim |
|
A crashed agent cannot hold work forever |
|
A reworded question is withheld too |
|
A claim reaches the file it names |
|
Every command has a |
|
The pull request check can never fail a build |
|
CI comments on decisions, not only claims |
|
A full store refuses a claim rather than dropping it |
|
|
|
|
|
Cost: pip install knos. No account, no key, no server, no model
download, no network request, and a 5 MB free-tier cap per repo.
Everything else, briefly
Every answer names where it came from — a commit, a session and a date, or a file and a line. Knos has no model: it does not summarise and it does not guess, it finds what somebody actually said.
$ knos ask "what are the rules here?"
Ask before adding a dependency. The build is the product.
AGENTS.md:3
Every change ships with a test. A green run you did not watch is not green.
CLAUDE.md:8Source | From |
Your rules |
|
Decisions in the repo |
|
Agent sessions | Claude Code transcripts, Cursor's history |
Commits |
|
Code structure | read by Knos itself, or universal-ctags when you have it |
What you tell it |
|
What is covered, and what is not
Knos is wired into 4 clients and reads the past session history of 2. Both numbers are the honest ones:
Client | MCP tools | Reads its past sessions |
Claude Code | yes, no restart | yes |
Cursor | yes | yes |
Claude Desktop | yes | no |
OpenCode | yes | no |
Hermes Agent | via knos-hermes | no |
Gemini CLI, Codex, Windsurf, Aider, Continue | no | no |
Wiring a client is three edits and a test — CONTRIBUTING.md
has them, with OpenCode as the worked example. A session reader is about 40
lines: Codex CLI and Gemini CLI are the two missing ones, each a small
parser plus one test, written up in
.github/GOOD_FIRST_ISSUES.md.
Knos does not have memory of every local workflow, and does not claim to.
.env, *.pem, id_rsa, .ssh, .aws and twelve more are private the
moment Knos reads a repo, without being asked. Private means invisible, not
redacted: an agent asking about one is told nothing at all — no result, no
count, no "2 hidden".
Worktrees. Keep them; they do a different job, and Knos treats every worktree of a repo as one memory anyway. Read the repo in one tree and every other tree can answer. Claim in one and the agents in the others are held off.
The whole mechanism is one git command. git rev-parse --show-toplevel
returns the worktree root, so every worktree looks like a different project;
git rev-parse --git-common-dir returns the git directory the worktrees
share, which is identical across all of them. Knos keys the store on the
second. Tools that key on the first fragment a repo's memory once per
worktree — that bug, in another
tool. Check it:
pytest tests/test_worktrees.py.
A claim lapses after 30 minutes. An agent that crashes mid-change
never calls knos done. If the claim outlived the process, that work would
be unaskable until a person noticed and cleared it by hand. Instead the hold
expires on its own, and the next agent to ask gets a real answer. Taking a
claim is a compare-and-swap, not a blind write, so two agents reaching for
the same work in the same second do not both believe they have it: one wins,
the other is told who holds it. Check both:
pytest tests/test_intent.py -k "lapses or two_processes".
Five tiers, one file, a hard 5 MB cap. Sibyl's schema is not a black box
Knos writes blobs into — it uses the tiers for what they are. Live claims go
in HOT, one row per topic, overwritten rather than appended. Decisions and
files go in WARM. History goes in COLD, append-only. The whole thing is
capped at 5 MB by Sibyl's free tier, and knos status prints the size and
says nearly full from 4 MB, so a store that is filling up tells you before
it stops taking writes rather than after
(pytest tests/test_sibyl_is_load_bearing.py -k cap_and_warns). At 5 MB a
claim is refused in words, not dropped: an agent that thinks it holds
work it does not is the exact failure this whole feature exists to prevent
(pytest tests/test_sibyl_is_load_bearing.py -k full_store).
Commands. knos ask, knos claim, knos done, knos status,
knos export. knos help lists the rest. Nothing runs itself: no watcher,
no daemon, no schedule.
Speed, on the one question this is for
"What was decided, and is anyone on it?" — warm, whole process, median of 7:
Knos |
| |
small repo | 960ms | 33ms |
Linux kernel (93,703 files) | 920ms | 28,289ms |
Git wins on a small repo and it is not close. Knos's time is flat with repo size because it reads an index rather than walking history; git's grows with it. On the kernel that is 30x, and most of Knos's 900ms is Python starting up.
Knos is not faster than git at anything git is for, and a cold first read of a large repo is slower than either — 3.1s median, stated above.
What agents actually read. A study of 557 agent sessions and
33,097 pull requests measured that 60.5% of everything coding agents do
with documentation happens in instruction files and their own notes —
CLAUDE.md, AGENTS.md, plans, scratch notes — against 10.6% for classical
docs and 1.3% for API references
(Gao & Chen, 2026).
That is a measurement of where agents spend their documentation time, and it is the whole of what the paper is cited for here. The paper itself states that the link between what agents consult and what they edit is unresolved. It does not study Knos, does not say a tool like Knos is needed, and is not evidence that anyone will adopt one.
Knos is one practical response to that measured behaviour: it reads those same instruction files as a source and answers from them with a file and a line. Two other things are true on their own account, and the paper is not the reason to believe either — a file cannot say who is reading it, and it cannot say what another agent is changing right now.
What happens when you delete the memory
One SQLite file at ~/.knos/<repo>/memory.db, via
Sibyl, capped at 5 MB per
repo — Sibyl's free tier, and Knos runs it unactivated, so there is no
account to make and no cap to raise. Sessions and commits are read newest
first, so when a repo fills, what you have is the recent end of both and the
older end was never read. Nothing already stored is evicted or truncated, and
knos status says nearly full from 4 MB. The Linux kernel filled 0.3 MB.
Nothing leaves this machine — Knos makes no network request. Delete that file and:
Gone forever | Why | |
What you told it ( | yes | it existed nowhere else |
Every claim, and the withholding | yes | same |
Who stood down for whom, every override | yes | same |
Your commits, | no — re-read | they are your files, not Knos's |
knos status counts that first row for you, so you never take it on trust:
journal 330 things learned
0 of them exist nowhere else - told, claimed, stood down
delete the store and only those go; the rest is re-read from your repoTen seconds to prove it: claim something, watch an agent be refused, delete the file, ask again. Nothing was ever held.
More on the five tiers, why a claim expires, and how a hold is bound to a connection so an agent cannot borrow somebody else's name: docs/core-flow.md.
The two onchain parts, and exactly what they are
Both are optional. Knos works with neither, and nothing on the read or answer
path touches a network — that is what pytest tests/test_no_network.py
checks.
Base: sharing one folder with a teammate
knos share ./src --with alice.base.eth
knos unshare ./src --with alice.base.ethWhat it does. Their agent can read that folder and nothing else. The record of who may read what is Access.sol on Base Sepolia, so neither machine has to trust the other's copy of the answer. Testnet, so it costs nothing.
What it does not do. It does not move your memory anywhere — the store stays on your disk. It does not encrypt anything. It is one permission bit per person per folder, not a sync protocol.
How to verify it. Two commands and one number each way:
python -c "from knos import team; o=team.identity('owner').address; m=team.identity('teammate').address; \
team.share('crates','teammate'); print(team.may_read(o,'crates',m)); \
team.unshare('crates','teammate'); print(team.may_read(o,'crates',m))"
# True
# FalseOr read it without running anything: contract
0x955fa320…6E52,
and one full cycle —
deploy,
grant,
revoke.
Nine contract tests: cd contracts && forge test.
Virtuals: selling one answer
What it does. Knos is registered on the Virtuals marketplace as a provider with one offering: another agent pays 0.01 USDC for an answer out of this machine's memory. The seller is agent/offering.ts.
agent/bot.ts is that same agent with a chat face, in one
process: it answers ACP jobs, it answers /ask out of the same store, and
/brief buys something over x402 on Base and writes what it bought back with
knos remember, so the next agent on the machine gets it without paying.
Every one of those paths reads or writes the same SQLite file —
pytest tests/test_sibyl_is_load_bearing.py takes it away and asserts none
of them work.
Started with no Telegram token it reads commands from the console, so the whole thing runs without an account. This is the same handler Telegram calls, wired to stdout, so what a person sees in the chat is what prints here:
$ npm --prefix agent run bot -- /status
Knos - one memory every coding agent here shares.
Nothing is claimed, so nothing is being withheld.
10 things written down that exist nowhere else
0.5 MB of 5 MB used
Shared by: Claude Code, Cursor
Delete the store and only those 10 go. Everything else is re-read from the repo.<b> markers around the bold words are left out above; Telegram renders them
and a terminal prints them literally. /help lists the five commands, and an
unrecognised one is answered rather than ignored - tests/test_bot.py.
The x402 half is live on Base mainnet. /brief BTC pays 0.01 USDC to
x402-seller's market-regime endpoint
and writes what it bought into the store with its receipt. Five settled so
far, signed by 0xEca35a0C…48C1:
0x2ce6af5c…,
0x20983f7b….
The client is src/knos/buy402.py, which signs with the
keystore knos made itself — there is no private key in any config file.
Two routes on that seller, /markets and /signal, return 502 after the
402. They cost nothing (the payment never settles) but they are why /brief
is the only route wired in.
What it does not do. There is no evaluator and no reputation system, and every job traded through it was bought by a test agent of mine, not by a customer. It is off by default and runs only when you start it.
How to verify it. The agent page is public — open app.virtuals.io/acp/agents/01a05b97… and you will see the registration without installing anything. Job 75659 is on Base mainnet, in two legs, neither of which needs an account to read: buyer pays 0.01 USDC into escrow, then escrow releases 0.0095 to the provider — the missing 5% is the protocol's fee.
It was asked why does knos withhold claimed work, and what it sold, in 180ms, was a passage out of a session from four days earlier:
knos withholds what it knows. A second agent searching claimed work gets who holds it and nothing else — the content is absent from the reply, not annotated. — Claude Code session 4101eeab 2026-08-31
Nobody re-typed that. Another agent paid a penny and a fresh process read it back with its source. The buyer was knos-buyer, an agent of mine registered to prove the path executes. It is not demand.
Tests
pytest runs the critical path only — claim, withhold, concurrency,
no-network, three tools, private files — 14 tests in well under a minute,
because a suite you wait four minutes for is one you stop running. The whole
suite is pytest -m "": 252 tests, five to twelve minutes depending on
what else the machine is doing - it was ten on the machine this was last run
on. Both
counts come from pytest --collect-only -q, so
pytest --collect-only -q -m "" | tail -1 is the check. The contract has
9 more: cd contracts && forge test.
Including the ones that would catch a lie:
test_no_network.py breaks
socket.connect,bindandgetaddrinfo, then reads a repo, answers questions, writes, claims, withholds and overrides. Nothing reaches for the network, and the guard itself is tested so the test cannot pass by doing nothing.test_private.py asks the search layer directly, with an agent's identity, for a private path. Nothing comes back.
test_memory.py has a second process write a conflict, rejected by the schema rather than by Knos.
test_recall.py writes as one agent and recalls in a separate, fresh process.
What it cannot do
Without
knos guard --install, a claim withholds what Knos knows and nothing more: it does not stop an agent editing a file. That is the honest limit of MCP, which gives a server no way to see an edit, let alone refuse one.With the guard, the refusal covers the edit in Claude Code, Cursor and OpenCode — and only those three, through their hook systems, which are not MCP. Claude Desktop has no hooks and is not covered. Nothing covers an editor a person types in themselves, or
sed, or any tool that never asks.The guard reads only the rules a machine can check: a prohibition with a path in backticks. "Never edit
src/generated/" is enforced; "write idiomatic code" is not, and Knos does not guess at what it might mean.The guard fails open. If the store cannot be read, the edit is allowed. A broken install standing between somebody and their own repository is a worse failure than the collision the guard exists to prevent.
Claude Code and Cursor only. No Gemini CLI or Codex history yet.
It does not write the answer for you, and it does not watch files. Run
knos pointagain to catch up.Retrieval is lexical, not semantic. Sibyl searches with SQLite FTS5, so Knos finds passages containing your words and ranks those. Ask about something the sessions never discussed and you get confident, well-sourced passages that share a word with your question and nothing else: "why did we drop redis" matches every note about dropping something. Ask in the words the work was done in and it is sharp. There are no embeddings at any Sibyl tier — the paid tier adds summarising and a learning loop, not search.
5 MB per repo.
Four jobs have been traded through the Virtuals provider, all bought by a test agent of mine. Nobody else has bought anything.
Contributing
CONTRIBUTING.md has the three edits an agent adapter takes
and the test to copy. pytest runs the critical path in about 25 seconds;
pytest -m "" runs all of it in about four minutes, against throwaway stores.
Prior work
Knos is not a fork and not a clone. There is no earlier repository, no upstream project, and no pre-existing memory layer that Sibyl was added to. Every line here is original work under MIT, and the commit history is the whole record.
The core was written locally before the window and first published on 1 September; everything after is dated in the log.
Dependencies, and what each is for. Sibyl Memory
(sibyl-memory-client) is the store, and it is load-bearing — see What
breaks without the store. The MCP Python
SDK provides the server. universal-ctags is optional; without it Knos
falls back to a reader it carries itself. The Virtuals ACP SDK and the
x402 client are used only by agent/, which is the commerce leg rather
than the product.
The name
Knos is pronounced like knows, and the crow is the reason. Crows cache food in thousands of places, remember which caches they made, and remember which other crows were watching when they made them — then move the ones that were seen. Memory, and knowing who else is in your business. A group of them is called a murder, which is either apt or a warning, depending on how many agents you are running.
Licence
MIT.
Available Tools
3 toolsaboutA
What is known about one thing: a file, a person, a topic.
| Name | Required | Description | Default |
|---|---|---|---|
| thing | Yes |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavior. 'What is known' suggests a read-only retrieval operation, which is useful, but it does not state what happens for unknown entities, whether any side effects occur, or whether special permissions/identifiers are needed.
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 clear sentence with no filler, and the core semantic ('what is known about one thing') is front-loaded. It earns its place without redundant phrasing.
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 single-parameter tool with an output schema present, the description is minimally adequate: it names the input concept and implies retrieval. But it leaves the parameter format ambiguous and gives no routing guidance relative to 'search' and 'remember', which are the main completeness gaps.
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 provides only a required property named 'thing' with no description, so schema coverage is 0%. The description partially compensates by defining the parameter as a file, person, or topic, but it does not specify the expected format, identifier type, or how to distinguish between those referent kinds.
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 conveys a lookup-style tool for a single referent ('What is known about one thing') and gives concrete examples ('a file, a person, a topic') that clarify the resource scope. It is distinguishable from the siblings 'search' and 'remember' by emphasizing facts about one entity rather than discovering or storing, though it does not name the siblings directly and uses the vague word 'thing'.
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?
Usage is implied: use this tool when you need known information about a single file, person, or topic. However, there is no explicit guidance about when to prefer 'search' for broader discovery or 'remember' for storing knowledge, and the siblings are not mentioned in the description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
rememberA
Write something back, so the next session in any agent knows it too.
Set `claiming` when you are about to start work on this, rather than
just noting something. Other agents are then told you have it and knos
withholds it from them until you finish or half an hour passes. Writing
a plain fact claims nothing: a note everybody can read is the point.| Name | Required | Description | Default |
|---|---|---|---|
| fact | Yes | ||
| about | Yes | ||
| claiming | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden. It goes beyond the schema by disclosing that claimed facts are withheld from other agents, that the claim releases when work finishes or after half an hour, and that plain facts are readable by everyone. This is meaningful, non-obvious 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?
The description is short and front-loaded: purpose first, then only the claiming nuance that materially affects how the tool behaves. It is not bloated, though the typo 'knos' is a minor polish issue.
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?
The essential write-and-claim semantics are well covered, and because an output schema exists, return values need not be described. However, given the locking/timeout complexity and no annotations, a complete definition should also explain the required 'about' parameter and perhaps give an example of a fact/about pair.
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 0%, so the description must explain parameters. It thoroughly explains 'claiming' and clarifies that a 'plain fact' is a shared note, but it never defines the required 'about' parameter or the expected shape/scope of 'fact'. This partial compensation leaves one required parameter ambiguous.
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 first sentence identifies a concrete action — 'Write something back' so future sessions know it — and the rest clarifies that this is a shared note versus a claimed work item, which separates storing from searching. The resource is a bit vague ('something'), but the required fact/about parameters and the write-vs-claim distinction make the core purpose clear.
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 overall use case is implied: persist information so a future session can read it. It gives clear advice on setting 'claiming' when starting work instead of merely recording a fact, but it never explicitly contrasts this tool with the sibling tools 'search' or 'about' or states when not to use remember.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
searchA
Search this machine's memory of the repo: past agent sessions, commits and code structure. Every result names where it came from.
Work another agent has claimed is withheld: you get who holds it, not
the answer. Ask them, or pick up something else. If you genuinely must
have it, call again with `override` set to your reason, which is
recorded in the journal against your name.
`on_behalf_of` names a teammate when the agent is working for one. They
see only the folders they were actually shared, and nothing else.| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| query | Yes | ||
| override | No | ||
| on_behalf_of | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden — and it excels. It discloses the withholding behavior (you get the holder, not the answer), provenance labeling ("Every result names where it came from"), the audit side effect of override ("recorded in the journal against your name"), and the access-scoping behavior of on_behalf_of ("They see only the folders they were actually shared"). These are exactly the non-obvious behavioral traits an agent needs to know.
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 three paragraphs but front-loaded with the core purpose in the first sentence. Each paragraph has a distinct job: scope, withholding/override policy, and teammate parameter. It is slightly long, but every sentence carries substantive information and none is filler.
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 an output schema exists (covering return values), the description covers the tricky semantics well: search scope, source attribution, contention handling, override auditing, and teammate scoping. The main remaining gap is the undocumented limit parameter and the absence of any guidance about result ordering or what happens on empty results — minor given the overall richness.
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 0%, so the description must compensate. It does add real meaning for override (purpose + journaling side effect) and on_behalf_of (teammate context + visibility scoping), which are the two non-obvious parameters. Query is only implied by the tool name and opening sentence, and limit — its default, purpose, or effect on result volume — is never mentioned. Partial compensation for a 4-parameter tool.
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 states a specific verb and resource: "Search this machine's memory of the repo: past agent sessions, commits and code structure." The scope is concrete and the added note that every result names its source further clarifies behavior. However, it never explicitly distinguishes itself from siblings 'about' and 'remember', so differentiation must be inferred rather than stated.
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 clear conditional guidance: when another agent holds claimed work, the agent should "Ask them, or pick up something else," and override is only for when the agent "genuinely must have it." It also explains when on_behalf_of applies (working for a teammate). It does not explicitly state when to prefer the sibling tools 'about' or 'remember', leaving that routing implicit.
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.
3 tool updates
v0.1.2- First observed
about - First observed
remember - First observed
search
TDQS
search and about both query stored knowledge, so an agent could initially confuse a broad search with an entity-focused lookup, but the descriptions make the distinction clear: search returns provenance-backed results from repo memory, while about targets one thing. remember is wholly separate as a write operation.
All tool names are lowercase single words, creating a simple and consistent style; search and remember are clear verbs, while about is more of a query noun/preposition, slightly deviating from a strict verb pattern.
Three tools is well-scoped for a focused memory/knowledge server: query broadly, query a single entity, and write back. Each tool has a distinct role and none feel redundant or missing at this level of abstraction.
The core read/write/query lifecycle for shared repo memory is covered, and claimed work handling is integrated into search and remember. Minor gaps exist around updating or forgetting explicit memories, but agents can work around these with search.
Maintenance
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