get_at_risk_issues

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

With no annotations, the description fully bears the burden of disclosure. It transparently describes field pattern matching, QA-skip logic with state history walk, and format-dependent behavior, leaving no ambiguity about tool actions.

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 well-structured with a succinct summary followed by detailed parameter explanations. It is slightly lengthy but every sentence adds value, earning a high score for organizing complex info effectively.

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 the complexity (10 parameters, no annotations, output schema present), the description covers all necessary aspects: purpose, parameter semantics, behavioral nuances, and return format. It is complete for effective tool usage.

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 0%, but the description explains all 10 parameters in detail, including defaults, accepted values, and behavior nuances (e.g., limit_per_category ignored when format='json'). This adds critical meaning beyond 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 clearly states it finds 'at-risk issues' and enumerates specific categories (overdue, qa_skipped, etc.), distinguishing it from sibling tools like search_issues or get_issues by its specific focus on risk detection.

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 when to use the tool (to find at-risk issues) and provides context on field matching patterns and per-category behavior. It implicitly guides usage through detailed parameter descriptions, but does not explicitly state when not to use it.

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