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task_audit

Read-only

Audit the Task Passport for continuity risks and advisory verification evidence, read-only and non-blocking. Use before finalizing, after long gaps, or when drift is suspected.

Instructions

Audit the current Task Passport for continuity risks and advisory-only risk-proportional adversarial-verification evidence (a concrete self-challenge at low risk; independent read-only review and a named disconfirming check at medium/high risk). It does not judge semantic correctness or block lifecycle actions. Call before finalizing, after a long gap, or when drift is suspected; skip when a recent audit already answered it. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
jsonNoReturn structured JSON instead of formatted text.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv1.4.0
    • addedInput schema / properties / json / description
      Added value: +"Return structured JSON instead of formatted text."
  2. First observedv1.3.0

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses that the audit is advisory-only, risk-proportional, and independent, and that it neither judges semantic correctness nor blocks lifecycle actions. This adds meaningful behavioral context beyond the structured annotation.

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 dense but well-structured, starting with the core purpose and then adding usage and safety context. The opening sentence is somewhat jargon-heavy, but every sentence contributes necessary information and the key points are front-loaded.

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?

The description covers purpose, behavior, when to use, and safety profile, which is strong for a read-only tool with one optional parameter. However, since there is no output schema, it does not explicitly describe what the audit result contains or how it is structured, which is a minor completeness gap.

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 single optional boolean parameter is fully documented in the schema with a clear description of its effect. The tool description adds no parameter-specific meaning, but the schema alone is sufficient, so the baseline score of 3 applies.

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 identifies the tool as auditing the current Task Passport for continuity risks and generating advisory-only verification evidence. It explicitly distinguishes itself from lifecycle-mutation tools by stating it does not judge semantic correctness or block lifecycle actions.

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 gives explicit conditions for when to call the tool ('before finalizing, after a long gap, or when drift is suspected') and when to skip it ('skip when a recent audit already answered it'). This provides actionable selection guidance without ambiguity.

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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