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Glama
JinyangWang27

people-context

remember

Capture a durable fact, trait, or interaction about a person in one call. Resolves existing profiles or creates a new person, storing role, relationship, and date details.

Instructions

Record one thing the user stated about one person, in a single call.

Use this when the user directly tells you something durable — "Alice from Acme prefers short emails", "Bob is my manager", "I had coffee with Dana today". person is the name as the user said it: it is resolved first, and a new person is created only when nobody matches. org/role record an affiliation, relationship records how the user relates to them (e.g. manager_of, friend_of, from the user's point of view), and note records the statement as a fact, trait, or interaction. Leave kind as auto to classify the note by a fixed keyword rule, or set it explicitly when you know. Pass occurred_at when the statement says an interaction happened earlier ("met Dana last week"); without it such a note is refused rather than dated today, because that date is what the staleness report reads.

Identity is never guessed for a write: status: ambiguous or unconfirmed returns candidates and records nothing — ask the user, then call again with the exact canonical name or a unique alias. Everything recorded commits in one transaction and is audited like the individual tools. For material you extracted or inferred from a transcript rather than a direct statement, use stage_candidates so the user reviews it first.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
orgNo
kindNoauto
noteNo
roleNo
personYes
sourceNoagent
predicateNo
occurred_atNo
sensitivityNopersonal
relationshipNo
trait_categoryNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. First observedv1.1.1

TDQS

A4.9/5.0
Behavior5/5

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

Discloses important behaviors beyond annotations: identity is never guessed, ambiguous/unconfirmed status returns candidates and records nothing, missing occurred_at causes refusal rather than defaulting to today, everything commits in one transaction and is audited. These are significant and non-obvious behavioral details that an agent needs to handle correctly.

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?

The description is dense but every sentence earns its place: purpose, usage trigger, identity resolution, field semantics, temporal behavior, failure mode, transaction guarantee, and alternative routing. The most critical constraints are front-loaded, and there is no filler.

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

Completeness5/5

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

For a complex 11-parameter write tool, the description covers all essential aspects: when to use, what each core parameter means, identity resolution behavior, failure/refusal conditions, and the recommended alternative tool. The presence of an output schema means return values need not be spelled out; the remaining gaps are minor auxiliary parameters already penalized in parameter semantics.

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

Parameters4/5

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

With 0% schema description coverage, the description must carry parameter meaning. It does so for the most important fields: person, org, role, relationship, note, kind, and occurred_at, with examples and the purpose of each. However, source, predicate, sensitivity, and trait_category are left unexplained, so compensation is strong but incomplete for all 11 parameters.

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 opens with a specific verb and resource: 'Record one thing the user stated about one person, in a single call.' It clearly positions this tool as the direct-statement write path, distinguishing it from stage_candidates and the individual record tools by emphasizing the single-call consolidated behavior.

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?

Explicitly states when to use it ('when the user directly tells you something durable' with concrete examples) and gives a clear exclusion: material extracted or inferred from a transcript should go to stage_candidates. Also provides guidance for ambiguous identity: ask the user, then call again with the canonical name.

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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