mark_skill_materialized

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

The description discloses side effects beyond annotations: it stops the brief() skill_hint nudge, appends a move note, and mirrors skill directories on a best-effort basis. This adds significant behavioral context to the idempotentHint and non-readOnly annotations.

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 somewhat lengthy but well-structured, starting with purpose, then behaviors, then parameter details, then additional mirroring. Every sentence adds value, though it could be slightly more 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?

The description covers main behaviors and parameters. Given an output schema exists, return values are covered. It could mention prerequisites (e.g., thread must be closed) more explicitly, but overall it is fairly complete for a tool with this complexity.

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?

With 0% schema description coverage, the description fully compensates by explaining thread_id (required thread context) and skill_path (optional, behavior when empty vs provided, absolute path requirement). This adds essential meaning beyond the 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 records that a closed thread's insights were materialized into a skill, stops a nudge, appends a note, and optionally mirrors the skill. It uses specific verbs and distinguishes from siblings like skill_record by focusing on the learning loop closure.

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 tells when to use it (after a closed thread's insights are written into a skill) and explains the effect of providing or omitting skill_path. It does not explicitly mention when not to use it or alternatives, but context is sufficient for an AI agent.

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