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audit_prd

Audit PRD files for quality and completeness by checking section coverage, Mermaid syntax, wireframes, versioning, and changelog against a 13-section structure. Detect version sprawl and ensure cross-PRD consistency.

Instructions

Audit a PRD file for quality and completeness against a 13-section structure. Checks section coverage, Mermaid syntax, wireframes, versioning, and changelog.

check_sprawl=True: Detect multiple versions of the same PRD (suggest archiving old ones) check_consistency=True: Check cross-PRD consistency for period selectors and tiers

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
check_sprawlNo
check_consistencyNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden. It describes what the tool checks but lacks behavioral details such as whether it modifies files, requires specific permissions, outputs format, or handles errors. The description adds some context (e.g., what sprawl and consistency checks entail) but is insufficient for a mutation-like audit tool.

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?

The description is appropriately sized and front-loaded, with the first sentence covering the core purpose and checks. The second sentence details optional parameters efficiently. There is minimal waste, though it could be slightly more structured (e.g., bullet points for clarity).

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?

Given no annotations, 0% schema coverage, but an output schema exists, the description is moderately complete. It covers purpose and parameter semantics but lacks behavioral transparency (e.g., mutation risks, output format). The output schema mitigates some gaps, but for an audit tool with potential file interactions, more context is needed.

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?

Schema description coverage is 0%, so the description must compensate. It explains the semantics of check_sprawl ('detect multiple versions of the same PRD') and check_consistency ('check cross-PRD consistency for period selectors and tiers'), adding meaningful context beyond the schema's basic titles. However, it does not clarify file_path usage (e.g., format, supported file types).

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 tool's purpose with specific verbs ('audit', 'checks') and resources ('PRD file'), detailing what aspects are evaluated (quality, completeness, 13-section structure, coverage, Mermaid syntax, wireframes, versioning, changelog). It distinguishes from sibling tools by focusing on PRD-specific auditing rather than general document operations.

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?

The description implies usage for auditing PRD files but does not explicitly state when to use this tool versus alternatives (e.g., other document-checking siblings like check_document_freshness or detect_contradictions). It mentions optional checks (sprawl, consistency) but lacks guidance on prerequisites or exclusions.

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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