build_plan

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

No annotations exist, so the description must carry the behavioral load. It usefully discloses the return content (overview, key specs, numbered steps, validation criteria) and that output is grounded in real framework docs. However, it omits any caveats on plan generation (e.g., does it require a knowledge base to be populated, latency, or that plans may be generic for undocumented frameworks).

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?

Front-loaded purpose sentence followed by scope and a bulleted use-case list; the trailing 'Returns:' line is slightly redundant with the earlier 'Returns an actionable plan' sentence but is cheap and skimmable. Overall tight and well-structured.

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?

With no output schema, the description correctly compensates by enumerating return fields (overview, specs, steps, validation criteria). For a simple 2-parameter generation tool this is close to complete, though the relationship to review_plan in a plan workflow is left implicit.

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 100%, so both 'goal' and 'constraints' are already documented with inline examples. The description adds no syntax, format, or interaction detail beyond what the schema supplies. Baseline 3 applies.

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?

States a specific verb and resource: 'Get a structured implementation plan based on knowledge base documentation.' It clarifies the grounding source (KB docs across ML/AI frameworks) and the output shape. It does not explicitly distinguish itself from the sibling review_plan, which an agent might confuse with plan generation.

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?

Three explicit 'Use this tool when' bullets give clear triggering conditions (about to implement, want doc-informed sequence, want validation criteria). No when-not conditions or named alternatives (e.g., review_plan for critiquing an existing plan) are provided, so it stops short of full routing guidance.

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