knitbrain_propose_agents

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

No annotations are provided, so the description must fully convey behavioral traits. It indicates 'Auto-detect' which is read-like, but does not explicitly state if the tool modifies data, requires permissions, or is idempotent. The phrase 'Review/edit' is ambiguous regarding the tool's own effects.

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 a single sentence that efficiently conveys the core action and purpose, followed by a brief instruction for the next step. No extraneous words, and the key verb is front-loaded.

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 lack of parameters, annotations, and output schema, the description is minimally complete. It explains the tool's purpose and suggests a workflow, but it omits details like return format, side effects, or permissions. A more comprehensive description 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?

The input schema has zero parameters and 100% coverage, so a baseline of 3 is appropriate. The description adds no parameter-specific information, but none is needed. It explains the tool's overall purpose, which is adequate for parameter semantics.

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 the action (auto-detect) and resource (agent proposals from knowledge graph). It also mentions the follow-up tool knitbrain_create_agent, helping disambiguate from siblings. However, it does not explicitly differentiate from other similar tools like knitbrain_scan or knitbrain_classify_task.

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 provides a workflow hint ('Review/edit, then create with knitbrain_create_agent') but lacks explicit guidance on when to use this tool versus alternatives. No prerequisites, exclusions, or context are given.

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