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

Beyond the read-only annotation, it discloses meaningful behavior: projects with too few fixed issues return null rather than a fabricated ratio, the tool returns no credentials, and the metric only counts fixes that were flagged by a Boosthis rule while the app was healthy versus after crashes or poor ratings. This sets accurate agent expectations and does not contradict the annotations.

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 compact and front-loaded, leading with the core question, then covering parameter semantics and output honesty in two more sentences. There is no filler; each clause adds selection or invocation value.

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?

With no output schema, the description still explains what the tool reports, the counting rule, the null policy, and the credential/period parameters. An agent has enough information to invoke the tool correctly and interpret the result at a high level.

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 coverage is 100%, so the baseline is already 3; the description adds context for account_token as the dashboard credential and defines window_days defaults plus the all-time option ('0 or all'). The added 'all' wording sits oddly with the schema's number type, which keeps this from a 5.

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 opening sentence clearly states the tool reports whether each project's fixes are preventive or reactive, and the next sentence defines the metric as fixes before user impact versus after crashes or poor ratings. This gives it a specific purpose and unique identity, but it does not explicitly name alternatives among the sibling tools.

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 gives a clear context for use: to analyze the preventive/reactive split of actually fixed issues, with honest nulls for low sample sizes. It stops short of saying when not to use it or naming a sibling alternative, so no explicit exclusion criteria are provided.

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