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audit_agent

Download and verify an AI agent's decision chain for tampering, returning INTACT or BROKEN with details.

Instructions

Audit an agent's complete reasoning chain. Downloads every decision and verifies the chain has not been tampered with. Returns INTACT or BROKEN with details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agent_idNo
Behavior3/5

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

Without annotations, the description must reveal behavioral traits. It mentions downloading decisions and verifying integrity, but omits side effects, resource usage, authentication needs, or whether the download is stored. For a tool with no annotations, this is moderate disclosure.

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 are concise and front-loaded with the main action. However, details about output format are embedded rather than structured, and no parameter info is included.

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?

The description covers the core function and return values but lacks prerequisites (e.g., agent existence, required scopes), error handling, and details on the 'details' response. For a tool with no output schema, more would be expected.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and the description does not mention the 'agent_id' parameter at all. The parameter's purpose, format, or source is unexplained, leaving the agent to infer from the name alone.

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 it audits an agent's complete reasoning chain, downloads decisions, verifies tampering, and returns INTACT or BROKEN. This distinguishes it from sibling tools like get_reasoning or verify_reasoning by specifying the full chain download and integrity check.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like verify_reasoning or get_agent_history. The description lacks when-not-to-use context or prerequisite conditions.

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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