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review_manual

Checks a manual outline against required structure before writing: chapter order, FAQ/glossary placement, project-specific justification, figure numbering; returns issues and page budget.

Instructions

Check a manual outline against the required structure before writing it out: the six chapters in order, FAQ and glossary last, a reason and evidence for any project-specific chapter, and continuous figure numbering. Returns the problems found and the page budget.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "software_name": "<software_name>",
      "version": "<version>",
      "chapters": "<chapters>",
      "total_pages": "<total_pages>"
    },
    "name": "review_manual"
  }
}

Input Schema

NameRequiredDescriptionDefault
versionYes
chaptersYes
total_pagesYes
software_nameYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.6.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description must carry the behavioral load; it discloses that the tool reports "the problems found and the page budget," which reveals it is a non-mutating validator returning diagnostics. It does not state whether it is strictly read-only, whether results are exhaustive or truncated, or any permission requirements for a validation step.

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?

One dense sentence with the validation target front-loaded and the checklist items enumerated; every clause carries information. It is slightly crowded but not padded.

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

Completeness3/5

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

An output schema exists, so the return shape needn't be spelled out, and the description still summarizes the two outputs. The gap is on the input side, where two required parameters lack any description, which for a four-required-parameter tool leaves the agent guessing what software_name and version should contain.

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 coverage is 0%, so the description needs to compensate: it usefully explains that chapters must include a project-specific chapter with reason and evidence and that numbering must be continuous, and it maps total_pages to the page budget. However, software_name and version are never mentioned, leaving half the required parameters with no semantic guidance anywhere.

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 gives a specific verb and resource ("Check a manual outline against the required structure") plus the concrete rule set it enforces, so the agent knows exactly what the tool validates. It implicitly separates itself from generate_materials via "before writing it out" but never names a sibling, keeping it short of a 5.

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?

"Before writing it out" establishes the workflow position clearly: validate the outline prior to generation. It gives no explicit exclusion or named alternative (e.g. explain_rules for rule semantics), so an agent must infer which sibling to pick when it only wants rule explanations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.