claudette

corpus_provenance

Identify the source, curation process, and limitations of the text corpus used for answering questions.

Instructions

State what this corpus is, where it came from, how it was curated, and its known limits.

Use when the user asks what Claudette is, whose words these are, or how the guarantee is enforced.

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

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, in the public domain, via Project Gutenberg.
`limitations`	No	Part of the answer, not a disclaimer.

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 18, 2026

TDQS

A4.7/5.0

Behavior4/5

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

With no annotations, the description carries the behavioral burden. It conveys that this is an informational, non-mutating tool by saying 'State what...', and it discloses the boundaries of what will be reported, including known limits. It does not discuss side effects or auth, but for a zero-parameter informational tool the description is adequately transparent.

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?

Two sentences with no filler: the first states the tool's job and output content, the second gives usage triggers. It is front-loaded and every clause earns its place.

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?

The tool has zero parameters and an output schema, so the description only needs to convey purpose and invocation timing, which it does. Nothing essential is missing for correct selection and invocation.

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?

There are no parameters, so the schema places no burden on the description. The baseline of 4 applies because there is nothing for the description to annotate about parameter meaning.

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 opening sentence uses a specific verb ('State') and resource (corpus provenance) and spells out the exact content: what the corpus is, its origin, curation, and limits. This separates it clearly from siblings like search_corpus and read_passage, which focus on lookup rather than provenance.

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?

The second sentence gives explicit trigger conditions: use when the user asks what Claudette is, whose words these are, or how the guarantee is enforced. This is concrete enough for an agent to route to this tool without opening sibling definitions.

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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