finalize_profile

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

No annotations are provided, so description carries burden. It discloses writing to disk, verification steps, anti-fabrication checks, and stub behavior for zero probes. Lacks mention of idempotency or potential side effects but is otherwise transparent.

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 long and includes imperative warnings that are important but could be condensed. It front-loads the main purpose, then adds constraints. Some redundancy exists in the verification phrasing.

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 complexity and lack of output schema, description covers essential conditions (zero probes, verification, return of skill_path). It could detail the return format further but is sufficiently complete for an agent.

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 50%; only usage_summary has a description in schema. The tool description adds meaning for usage_summary but does not explain the 'target' parameter at all, leaving agents unclear about its role.

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?

Description clearly states the tool synthesizes workspace model, operational model, capability profile, quality report, and SKILL.md from safe observations and writes them to disk. It distinguishes from siblings like generate_skill by specifying the full artifact set and finalization aspect.

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?

Description provides context for when to use: after accumulated safe observations, with verification requirements. It also covers the zero-probes edge case. However, it does not explicitly list alternative tools or when not to use this tool.

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