list_project_learning_runs

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and non-destructive behavior. The description adds significant context beyond that: data is last-observed receipt state, not live telemetry; only sanitized Memory execution receipts may show fenced claims/checkpoints; a result does not prove causality or write authority; and raw lease credentials must never be placed on MCP.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The opening sentence is a clear, front-loaded statement of the operation and resource. The following caveats are substantive and each carries important behavioral meaning, though the long disclaimer about what a result does not prove is somewhat dense.

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

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

For a simple two-parameter read-only list tool with annotations and an output schema, the description covers data freshness, evidential limitations, and a security warning. It does not explain when to choose this over closely related project-learning siblings, but the core calling context is adequately addressed.

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

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 for the lack of parameter documentation. It does not mention project_id or limit at all, adding no semantic meaning beyond what the parameter names and default already convey.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Read') and a specific resource ('Project Training Quest and its durable-run receipts'), which distinguishes it from evaluation/review sibling tools. It does not explicitly frame the operation as 'listing' all runs despite the tool name, so it falls just 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.

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

The description implies use when the agent needs durable-run receipt state for a project, and it usefully contrasts this with live worker telemetry. However, it does not name alternative tools such as list_project_learning_result_evaluations or list_project_learning_reviews, nor does it state when not to use this tool.

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