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Glama

LMGram

by io.github.saezbaldo

Request a human match

request_human_match

Creates an opt-in LMGram human match request only after the user explicitly asks to use LMGram to find a collaborator, peer, mentor, or helper. Never invoke for general advice, dating or romantic matchmaking. Never include secrets, credentials, API keys, raw transcripts, customer data, or private documents; ask for a minimized non-sensitive summary first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
needYesThe concrete collaborator, peer, mentor, or helper the user explicitly wants. Dating and romantic matching are not supported.
topicYesShort, non-sensitive title for the practical or professional session topic. Dating and romantic requests are not supported.
summaryYesMinimized non-sensitive summary. Never send secrets, credentials, API keys, raw transcripts, customer data, or private documents.
urgencyNo
languageNo
matchTypeNopeer
sensitivityNonormal
maxCandidatesNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed3 schema fields changed
    • changedInput schema / properties / need / description
      Previous value: -"The concrete human connection the user wants."New value: +"The concrete collaborator, peer, mentor, or helper the user explicitly wants. Dating and romantic matching are not supported."
    • changedInput schema / properties / summary / description
      Previous value: -"Minimized summary. Do not send raw transcripts, secrets or private documents."New value: +"Minimized non-sensitive summary. Never send secrets, credentials, API keys, raw transcripts, customer data, or private documents."
    • changedInput schema / properties / topic / description
      Previous value: -"Short title for the current session topic."New value: +"Short, non-sensitive title for the practical or professional session topic. Dating and romantic requests are not supported."
  2. First observed

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the annotations (readOnlyHint=false, openWorldHint=true), the description reveals important behavioral constraints: it is opt-in, excludes romance/dating, and prohibits sensitive data like secrets or API keys. This adds privacy/trigger context not captured in annotations. It doesn't contradict annotations, though it could further clarify side effects (e.g., persistence or notification).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three compact sentences, front-loaded with the core purpose, then usage boundaries and data-safety instructions. Every sentence adds value with no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description nails the trigger and safety constraints, but with 8 parameters and no output schema, it leaves gaps: no explanation of matchType/sensitivity/maxCandidates, and no indication of what the response/result looks like or next steps. It is adequate for a well-scoped tool but not fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 38%, with descriptions for need, topic, and summary but no descriptions for urgency, language, matchType, sensitivity, or maxCandidates. The description repeats some schema constraints (non-sensitive summary, no dating) but adds no new meaning for the five undocumented parameters, so it doesn't compensate for the low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates an 'opt-in LMGram human match request' and specifies the exact trigger ('only after the user explicitly asks to use LMGram to find a collaborator, peer, mentor, or helper'). It distinguishes itself from sibling tools by focusing on match requests rather than messages/chats, and explicitly excludes dating/romantic use.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit when-to-use guidance ('only after the user explicitly asks'), clear exclusions ('Never invoke for general advice, dating or romantic matchmaking'), and even instructs on the preprocessing step ('ask for a minimized non-sensitive summary first'). This goes beyond a general hint and gives actionable direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct resource and action: user profile, match requests, messages, sending, and chat initiation. There is no meaningful overlap between any two tools, and their purposes are clearly separable.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (e.g., get_current_user, list_messages, send_message). The naming style is uniform and predictable, making it easy to infer tool behavior from the name.

Tool Count5/5

Six tools is well within the ideal range for a focused messaging and matchmaking server. Each tool serves a clear and necessary function without redundancy, and the count feels appropriately scoped.

Completeness4/5

The core workflow is covered: viewing user, listing/requesting matches, starting chats, and messaging. Minor gaps exist such as lack of a single match detail view or explicit match acceptance, but the main lifecycle is sound and workable.

Resources