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

Adds useful behavior beyond the readOnly/idempotent annotations: results are ranked by relevance with GitHub stars as a tiebreak, and tools lacking clear local-running evidence are excluded from local filters. It does not cover authentication or rate limits, but those are outside the main behavior for this read-only recommendation tool.

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 dense sentences with the core purpose, ranking logic, filters, and the most nuanced filter guidance front-loaded. Parenthetical examples earn their place by illustrating plain-language task input and local-running use cases.

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?

Complete enough for a read-only recommendation tool with no output schema: the description covers what the tool does, how results are ordered, and what each major filter means. A minor gap is that it does not describe the shape of the returned recommendations beyond ranking.

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?

The description adds meaning beyond the schema for the runs_locally filter, explaining offline versus self-hosted_or_offline and the exclusion behavior, and clarifies that the task is plain words. It only names pricing and open_source without adding semantics, and does not mention the limit parameter, so coverage is partial.

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?

States a specific verb and resource: it suggests AgentScout tools for a plain-language task, with relevance ranking and GitHub stars as tiebreak. It is clear, but it does not explicitly distinguish itself from the sibling search_tools, leaving the agent to infer that this is a recommendation engine rather than a raw keyword search.

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?

Gives explicit guidance for the runs_locally filter, including when data must stay local, and mentions optional pricing and open-source filters. It does not explain when to use this tool versus search_tools or get_tool, so the agent must infer the boundary between recommendation and lookup.

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