publish_lesson

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

With no annotations, the description fully discloses key behaviors: PII stripping, irreversibility, return fields, and visibility under framework/category tag. Minor omission of potential auth requirements.

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?

Five sentences, each providing necessary information without redundancy. The main purpose is front-loaded, and the description is dense but not verbose.

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?

Covers purpose, behavior, return values, and irreversible nature. Lacks explicit error conditions or auth requirements, but given no output schema and no annotations, it provides adequate context for an agent to use the tool correctly.

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%, but the description adds context beyond schema: explains that topic becomes public category, framework examples are given, and PII stripping is noted for lesson. Output fields are also listed.

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 the verb 'Publish' and the resource 'lesson' to the 'Cachly Public Brain', and explicitly distinguishes it from sibling tools like learn_from_attempts and syndicate.

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?

Provides explicit guidance on when to use this tool versus alternatives: 'Use learn_from_attempts or global_learn for private lessons; use syndicate for anonymized global sharing without framework tagging.'

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