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Check Plot Consistency

check_plot_consistency
Read-onlyIdempotent

Scan manuscript chapters to find plot inconsistencies like timeline conflicts, contradicted facts, and dropped threads, returning the issues found.

Instructions

Scan a set of documents for plot-level inconsistencies — timeline conflicts, contradicted facts, dropped threads — and return the issues found with the documents involved. Use this for story/plot coherence across chapters; use check_consistency for general consistency checks or analyze_writing_style for prose-level analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoRun as a background job and return a job id instead of waiting. Default false.
documentsYesArray of documents (id and content) to check together, e.g. the chapters of a manuscript.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobIdNoIdentifier of the queued job (present when run asynchronously).
issuesNoPlot-level inconsistencies found (present for synchronous runs).
messageNoHuman-readable status message.
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds valuable behavioral context about the types of inconsistencies checked (timeline, facts, threads) and confirms it returns issues. While it doesn't add new safety or cost details, it enriches the agent's understanding of the tool's behavior beyond what annotations alone provide.

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 long, with the main purpose front-loaded and alternative usage in the second sentence. Every word serves a purpose; no filler or redundancy. Highly efficient.

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?

Given the tool's moderate complexity, existence of an output schema, and rich annotations, the description covers the key aspects: what it checks (three types of issues) and when to use it. It is complete enough for an agent to understand the tool's role, though it omits potential prerequisites or limitations (e.g., document size) which are minor gaps.

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 per guidelines. The description does not add further parameter-specific information beyond what the schema already conveys (e.g., documents = array of id+content, async = background job flag). No additional semantic value is provided.

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 clearly states the verb 'scan' and the resource 'set of documents for plot-level inconsistencies' with specific examples (timeline conflicts, contradicted facts, dropped threads). It also explicitly distinguishes from siblings 'check_consistency' and 'analyze_writing_style', making the purpose unmistakable.

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 description provides explicit when-to-use guidance ('Use this for story/plot coherence across chapters') and contrasts with alternatives ('use check_consistency for general consistency checks or analyze_writing_style for prose-level analysis'). This fully informs the agent about selection criteria.

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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