get_at_risk_issues

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

Annotations already declare readOnly, idempotent, non-destructive, open-world, so the safety profile is covered. The description adds valuable runtime behavior: the history-walk cost model for QA skip, the 'pattern matching' on decorated field names, and the fact that limit_per_category is ignored in JSON mode. This goes beyond what annotations convey.

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 longer than average but earns its length given 10 parameters. It front-loads the core action and category list, then gives behavioral context, then a cleanly labeled Args section. No repeated restating of parameter titles from the schema; each sentence adds semantic 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?

For a 10-parameter read-only tool with an output schema present, the description is nearly complete. It covers defaults, edge semantics (QA history verification, zero-cost when no QA field), output format differences, and aliases. An agent can confidently construct correct calls.

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 carries full burden. It explains every one of the 10 parameters with defaults and nuance (e.g., exclude_patterns is regex, category accepts aliases, format controls full-set behavior, instance is optional). This effectively compensates for the bare schema.

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 opens with a precise action and resource: 'Find at-risk issues' and immediately enumerates the distinct categories (overdue, qa_skipped, stalled, forgotten, unestimated, over estimate, ancient). This clearly distinguishes it from sibling search/reporting tools and gives an agent a concrete sense of what the tool computes.

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 detailed behavior for QA-skip detection, staleness thresholds, category filtering, and output formats. It doesn't explicitly contrast against alternatives like search_issues or get_issues, but it makes its own applicable context obvious (at-risk classification rather than general querying or listing). The 'Args' section also clarifies when JSON vs report output should be preferred ('programmatic consumers like a daily deadline bot').

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