suggest_managers

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It describes the detection logic, scoring, and side effect of writing a file (controlled by the `write` parameter). It also mentions auto-exclusion of PMs. This provides good transparency, though it could be more explicit about the impact on data.

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 description is concise and well-structured: a brief introductory sentence, a paragraph explaining the algorithm, and a bullet list of arguments. Every sentence adds value, and there is no repetition or unnecessary detail.

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?

Given that an output schema exists (so return values are documented there), the description is fairly complete. It covers the tool's purpose, algorithm, parameters, and side effects. However, it could mention prerequisites (e.g., authentication) or expected input format details for the `projects` parameter.

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?

The input schema has 0% description coverage, so the description must compensate. It explains each parameter: lookback_days (activity window, default 90), projects (comma-separated shortnames, empty for all), write (controls file writing vs. printing), instance (optional). This adds significant meaning beyond the schema's type and default information.

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 clearly states the tool's purpose: 'Bootstrap a manager mapping from recent YouTrack activity.' It explains the algorithm (detect PMs, score candidates) and the output (writes managers.suggested.json). No sibling tool has a similar purpose, so it is well-distinguished.

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 explains what the tool does but does not provide explicit guidance on when to use it versus alternatives, nor does it mention any exclusions or prerequisites. Usage is implied by the context of manager suggestion, but there is no direct 'when to use' or 'when not to use' advice.

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