claudette

verify_attribution

Check Wikidata to confirm a woman wrote a given work before naming her from memory, returning ok, weak, or not_found.

Instructions

Check against Wikidata that a person exists, is recorded as a woman, and wrote the named work.

Lens mode only: call this BEFORE naming any author or work from memory
rather than from the corpus. `ok` means name her. `weak` means name her
with the stated caveat. `not_found` means do not. Not for authors already
in the corpus — search_corpus is their check. The one network call this
server makes; it goes only to Wikidata.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`name`	Yes	A thinker or writer you intend to name from memory, e.g. 'Elinor Ostrom'.
`work`	No	The work you intend to attribute to her, e.g. 'Governing the Commons'. Optional but strongly encouraged.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`data`	No
`status`	Yes	ok — passages found that match most of the question's terms. weak — something matched, but thinly; say so if you use it. no_coverage — the corpus does not speak to this. Say that. Do not answer from elsewhere. not_found — a specific reference did not resolve.
`constraint`	No		Answer only from these passages. Quote or closely paraphrase, and cite each claim as [Author, Title §n]. If the passages do not speak to the question, say so plainly rather than filling the gap from elsewhere.
`provenance`	No		Every passage is from a work by a named woman author. Each hit's `source` says where that text came from and on what basis; `curated` says whether a person reviewed the edition.
`limitations`	No	Part of the answer, not a disclaimer.

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.5.2Sep 19, 2026

TDQS

A4.5/5.0

Behavior4/5

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 this is the only network call the server makes, that it goes only to Wikidata, and interprets possible outputs ('ok', 'weak', 'not_found'). It does not mention latency or failure modes, but for this tool the key behavioral facts are covered well.

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?

Four compact sentences, each earning its place: what it checks, when to use it, how to interpret results, and what distinguishes it from alternatives. Front-loaded with the core purpose, then operational guidance.

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?

Given that an output schema exists and the parameters are fully documented, the description covers the essential context: the exact use case (memory-based attribution in lens mode), the exclusions (corpus authors), the network/behavioral profile, and the meaning of the return states. Nothing critical is missing for an agent to call it correctly.

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

Parameters3/5

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 clearly. The description adds usage context around them ('a thinker or writer you intend to name from memory' is already in the schema; the description reinforces the purpose) but does not add substantial meaning beyond what the input schema provides.

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?

States a specific verb and resource: 'Check against Wikidata that a person exists, is recorded as a woman, and wrote the named work.' It clearly distinguishes itself from corpus-based tools by specifying this is for authors/works named from memory, not from the corpus.

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 says when to use: 'Lens mode only: call this BEFORE naming any author or work from memory rather than from the corpus.' It also names the alternative: 'Not for authors already in the corpus — search_corpus is their check.' This leaves no ambiguity about routing.

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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