claudette

list_works

Browse the full corpus of public-domain women-authored texts by author, title, year, inclusion reason, and slug. Use it to see available works or select a slug for restricted searches.

Instructions

List every work in the corpus: author, title, year, why it is included, and its slug.

Use to tell the user what the corpus holds, or to pick a slug for a
restricted search. Not a search — it returns no passages.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`shelf`	No	'thought' or 'fiction', or unset for all.

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

A3.8/5.0

Behavior3/5

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 the output fields and explicitly states it returns no passages, which is useful. However, it does not state whether the operation is read-only, mention any permission requirements, or describe behavior such as pagination or error handling. For a simple list tool this is adequate but not rich.

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 two sentences with zero fluff. The first sentence states the core function and outputs; the second provides usage guidance and an explicit exclusion. It is front-loaded and every phrase earns its place.

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

Completeness4/5

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

For a straightforward list tool with an output schema and fully documented parameters, the description covers purpose, usage, and key output characteristics. It does not explicitly mention all sibling tools, but the combination of the description and schema is sufficient for an agent to call it correctly. Minor gaps around error handling or performance are not critical here.

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?

The schema fully describes the only parameter (shelf) with its allowed values and default, so the schema carries the semantic weight. The description does not mention the parameter at all, so it adds no value beyond the schema, warranting the baseline score of 3.

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

Purpose4/5

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

The description clearly states the action (List every work) and the exact fields returned (author, title, year, why it is included, slug), making the purpose unambiguous. It differentiates from search_corpus by explicitly stating 'Not a search', but does not explicitly distinguish itself from read_passage or corpus_provenance, so it falls short of full sibling differentiation.

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

Usage Guidelines4/5

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

The description provides explicit use cases ('tell the user what the corpus holds' and 'pick a slug for a restricted search') and a clear exclusion ('Not a search — it returns no passages'). It implies the alternative search_corpus without naming it, and does not mention when read_passage or corpus_provenance would be preferred, so it is clear but not exhaustive.

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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