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

Discloses a non-obvious behavior: a project with too few fixed issues returns null rather than a fabricated ratio, which prevents an agent from misreading absent data. It also states 'Read-only; returns no credentials.' Annotations already declare readOnlyHint, so the null-handling rule is the real added value.

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?

Tight, front-loaded definition of the metric followed by empty-data behavior and a safety note. Two sentences carry distinct information; the 'Maintenance Mix:' prefix is slightly redundant with the title but not wasteful.

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 read-only metric with a fully covered schema and no output schema, the description covers concept and null behavior but omits the return shape (what ratio/fields come back) and any unit or interpretation guidance. Adequate but with clear gaps given 28 sibling analytics tools.

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 window_days and account_token are fully documented in the schema. The description adds no parameter-level detail beyond what is already structured, making 3 the correct baseline.

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?

It defines a specific metric — the ratio of issues fixed pre-impact versus post-impact. The concept is clear but the framing as a 'Maintenance Mix' is idiosyncratic and doesn't obviously distinguish it from siblings like boosthis_trend or boosthis_vigilance without the reader inferring what 'mix' means.

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?

No statement of when to use this tool versus the many sibling analytics tools (trend, vigilance, snapshot, crash_risk). The definition explains what the metric is but gives no route for an agent deciding between these overlapping analytics endpoints.

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