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Agent call log

agent_logs
Read-onlyIdempotent

What an agent was asked and what it answered — the trace to read when its replies look wrong. What it actually said in real conversations. To try a hypothetical instead, without sending anything, use agent_query; to read the prospect-facing thread use conversation_get. Requires the "Agents" permission on the plan.

Input Schema

NameRequiredDescriptionDefault
pageNo1-indexed page number.
agentIdYesAI agent id, from `agent_list`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds a real behavioral constraint the annotations lack: it requires the "Agents" permission on the plan. It stops short of describing pagination or log volume, which is the only remaining gap.

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?

Front-loaded with the core purpose, then routing alternatives, then the permission note. The middle sentence ('What it actually said in real conversations') slightly restates the opening clause rather than adding new information, but the description stays short and readable.

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?

For a read-only log tool with no output schema, the description adequately conveys what is returned (the ask/answer trace) and the routing alternatives. The permission requirement is a useful addition. Pagination behavior for potentially large logs is the one notable omission.

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% with only two parameters, so the schema already documents both agentId and page. The description adds no parameter detail beyond what the schema provides, which is the expected baseline when the schema does the heavy lifting.

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?

States a specific resource and scope: the trace of what an agent was asked and what it answered. It explicitly names the sibling tools it is not (agent_query for hypotheticals, conversation_get for the prospect-facing thread), so an agent can disambiguate without opening any schema.

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?

Gives an explicit trigger — read this when an agent's replies look wrong — and names two alternatives with the condition that selects each ('to try a hypothetical instead... use agent_query'; 'to read the prospect-facing thread use conversation_get'). Nothing about tool selection is left to inference.

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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