list_intents

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

With no annotations provided, the description carries full burden. It thoroughly discloses behavior: how q matches per-word (all words must appear, any order), AND-combination of q and overlaps, the effect of match='any', alert_level values when overlaps is given, and the purpose of each parameter mode. No contradictions exist between description and annotations (none provided).

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 numbered use cases and clear separation, but it is quite lengthy. While every sentence adds value, it could be slightly more concise by integrating the alert_level explanation into the use case descriptions. Overall, it is well-organized but not maximally concise.

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 13 parameters, no output schema, and no annotations, the description covers the three distinct use cases thoroughly and explains parameter interactions. However, it does not describe the return format beyond mentioning 'alert_level.' Without an output schema, a brief note on the fields returned (e.g., summary, kind, status, author) would improve completeness.

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 high (92%), but the description adds significant meaning beyond individual parameter descriptions: it explains the three usage patterns, how parameters interact (e.g., summary enables semantic checks, overlaps triggers alert levels, q and overlaps are AND-combined, omit q for collision checks), and provides real-world context for parameters like session, branch, and my_kind.

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 'Query in-flight and recent work across the team,' clearly stating the action and resource. It then enumerates three distinct use cases, each with a specific purpose, effectively distinguishing this read-only tool from its siblings (post_intent, update_intent, etc.).

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 explicitly instructs the agent to 'pick exactly one' of the three use cases and provides concrete guidance on when to use each: pre-planning semantic check (summary + overlaps), fast glob collision check (overlaps alone), and context search (q + since). It also warns against combining q with overlaps incorrectly and explains when to omit q, offering exceptional decision support.

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