approve_learning_item

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

No annotations provided; description compensates by disclosing required scope (learning:arbiter:write), mentions Arbiter constitutional policy and ProofLink receipt, indicating governance and audit trail.

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?

Two sentences, front-loaded with core action, no extraneous information. Every word contributes.

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?

For a simple one-parameter tool with no output schema, description covers purpose, parameter, and behavioral context (scope, receipts). Adequate but could mention success indicators briefly.

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 coverage is 100% and already describes pattern_id as 'Pattern ID from get_learning_queue'. Description adds no additional meaning beyond requiring pattern_id, so baseline 3 is appropriate.

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 verb 'Approve', resource 'Tier 2 learning pattern', and action 'promotion to Agent Brain'. Distinguishes from sibling tools like approve_sie_finding.

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?

No explicit guidance on when to use this tool vs alternatives such as get_learning_queue or other approval tools. Lacks usage context.

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