CompanyScope

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

Without annotations, the description carries the full burden and succeeds in explaining the data sources (HTTP headers, DNS, GitHub) and return structure (frameworks, languages, hosting, analytics, CDNs). Minor gap: does not explicitly state if this is read-only, rate-limited, or potentially costly due to external scraping behavior.

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?

Four sentences each serving distinct purposes: mechanism, output, sibling differentiation, and input constraints. No redundancy or filler. Information is front-loaded with the core action.

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 single-parameter analysis tool, the description is complete. It compensates for the missing output schema by detailing the categories of returned data. Combined with perfect input schema coverage, no additional description is necessary.

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?

With 100% schema description coverage, the baseline is 3. The description reinforces the domain requirement and company-name constraint, but does not add semantic details beyond what the schema already provides (format, examples, constraints).

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 opens with a specific action ('Detect') and clear resource ('technology stack'), detailing the methodology ('analyzing HTTP headers, DNS records, and GitHub repositories'). It effectively distinguishes from siblings by contrasting with lookup_company for technology-specific needs.

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?

Explicitly states when to use this tool versus alternatives ('Use this instead of lookup_company when you only need technology information'). Also clarifies input requirements versus unsupported formats ('Requires a domain name — company names are not supported'), preventing common misuse.

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