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Penwright — writing-craft library, guide metadata, and magazine

Choose your camp on a guide's debates

choose_camp
Read-only

Given a guide slug and one pick per debate ('A', 'B', or skip, in debate order, as a single string e.g. 'ABAB'), returns which library ids argue the picked side of each debate and the union reading list. Pure compute over public debate data — no book text is generated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
guideYesGuide slug (e.g. memoir-writing, nonfiction-writing, fiction-writing, getting-published).
picksNoOne char per debate in order: A, B, or any other char (or omit) for skip.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
picksYes
contractYes
guideSlugYes
guideTitleYes
libraryIdsYes
canonicalUrlYes
guideCanonicalUrlYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so the safety profile is covered and the bar is lower. The description adds real context beyond that: it is 'pure compute over public debate data' and generates 'no book text', and it discloses the shape of the result (per-debate library ids plus a union reading list).

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

Conciseness4/5

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

Two sentences, front-loaded with the input contract followed by the output and the compute-only caveat. Every clause carries information, though the dense parenthetical syntax for picks takes a second read.

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?

An output schema exists, so return-value explanation is not strictly required, and the description nonetheless summarizes the return. Inputs, requiredness and the read-only compute nature are all covered; only explicit sibling routing is missing.

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 baseline is 3. The description restates the picks encoding ('A', 'B', or skip, in debate order, as a single string e.g. 'ABAB') but adds no syntax or edge-case detail beyond what the schema already documents; guide slugs are likewise already exemplified in the schema.

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 action (returns which library ids argue the picked side of each debate plus the union reading list) over a specific resource (a guide's debates and picks). This is clearly distinguishable from siblings like get_debate or get_guide, which surface the debate content rather than computing a reading list from picks.

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

Usage Guidelines3/5

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

Usage is implied: the tool is for computing reading lists from picks over public debate data, and 'pure compute' signals it is a derived/aggregation step rather than a raw fetch. However, it never states when to prefer it over siblings (e.g., get_debate to inspect debates first, or search_library to browse works), so the agent must infer the workflow position.

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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