fedbrain_confirm

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

No annotations provided, so description carries full burden. It clearly discloses side effects: propagates confirmation globally (increments confirm_count on knowledge certificate), updates local CKG confidence, and triggers Gold Standard at threshold. No contradictions with non-existent 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?

Three sentences, zero waste. First sentence states core action, second explains effect, third gives success criterion. Front-loaded with key verb and noun.

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 100% schema coverage and no output schema, description is complete enough. It explains input requirements (syndicated lesson id, outcome, optional topic), process, and outcome. The only minor gap is no mention of error conditions or authorization requirements.

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 baseline is 3. Description adds value by connecting parameters to real-world context: 'id' is from fedbrain_search results, 'topic' updates CKG confidence, 'outcome' has enum with clear meaning. It explains the purpose of each parameter beyond schema descriptions.

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's purpose: confirming that a syndicated lesson worked, with specific verbs ('confirm', 'propagates', 'increments', 'updates') and a distinct outcome (Gold Standard at 10 confirmations). This distinguishes it from siblings like fedbrain_search (search) and fedbrain_contribute (publish).

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 implies when to use: after consuming a syndicated lesson from fedbrain_search results, to confirm its effectiveness. It does not explicitly state when NOT to use (e.g., for lessons not syndicated) or mention alternatives, but the context is clear enough 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.