github-org-intel

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

Describes scope (up to 25 top repos), caching behavior (1 hour), and data source (GitHub public API). No annotations exist, so description carries full burden. Lacks disclosure on rate limits or authentication, but non-critical for a public API 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?

Three sentences with no waste. First sentence states primary function and output, second lists outputs, third provides context and source. Front-loads key information efficiently.

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 no output schema, description adequately explains return structure (org profile, repos, tech stack, activity signals). Also covers limitations (25 repos) and caching. Complete for a read-only intel tool with simple schema.

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%, baseline 3. Description adds value by explaining 'org' accepts both name and URL, confirms default and max for 'top_repos', and reinforces sorting by stars. This goes beyond the 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?

Clearly states verb 'returns' and resource 'GitHub organization intelligence', enumerates specific data outputs (org profile, top repos, tech stack, activity signals). Distinguishes from sibling 'github-repo-intel' by focusing on org-level data and top repos sorted by stars.

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?

Lists explicit use cases (due diligence, competitive analysis, investment research, talent sourcing). Does not provide when-not-to-use or direct alternatives, but the context is clear enough for typical usage.

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