scout_and_update_skill_library

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

With no annotations provided, the description carries full responsibility for disclosing behavioral traits. It does mention a side effect ('automatically logging into persistent agent memory'), which indicates a write operation, but it omits details such as whether this overwrites existing memory, whether it requires authentication, or potential rate limits from the GitHub API. The description is vague about the memory update mechanics and any risks, leaving significant gaps for an agent.

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 a single, dense sentence that front-loads the primary action (querying GitHub API) and the secondary effect (logging to memory). It is efficient and avoids redundant wording, though it could be slightly more structured for clarity. The information is presented in a logical order with no wasted phrases.

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 that this tool performs a network call and a persistent memory write, the description is incomplete. It does not specify what the tool returns (no output schema), the exact nature of 'architectural patterns' being logged, or how it relates to the sibling get_latest_trending_repos. The absence of usage guidance and behavioral details makes it difficult for an agent to know the full scope of side effects and expected results.

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 both parameters (min_stars and domain_query) are fully described in the schema. The description itself does not add semantic value beyond what the schema provides, except implicitly associating domain_query with 'domain' and memory logging. Since the schema already covers parameter meaning, the baseline score of 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?

The description clearly states the tool queries GitHub's search API for trending repos/libraries and logs patterns to persistent memory. It is specific about the action and resource, but does not explicitly differentiate from the sibling get_latest_trending_repos, which likely performs a simpler query without memory updates. The purpose is unambiguous enough for an agent to understand its core function.

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 gives no explicit guidance on when to use this tool versus alternatives. It implies continuous skill updates ('automatically logging new architectural patterns') but does not state when to prefer it over a plain repo query like get_latest_trending_repos, nor any prerequisites or conditions. An agent would have to infer usage context.

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