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

Beyond the annotations (readOnly, idempotent, destructiveHint false), the description adds critical behavioral context: it explains that `partnerships_declared` being 0 means none declared, not that the firm has no partners, and provides measured frequency data. It also notes that a refused slug does not mean the firm is absent, because the published tranche is an editorial subset. This is valuable nuance not captured in annotations.

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 efficiently structured: an action sentence, a return-semantics sentence, and an exclusions sentence. It is slightly dense due to the parenthetical measurement detail ('re-measured 2026-08-14... 96,8 %'), but every clause contributes to understanding. It is front-loaded and appropriately sized for a tool with this nuance.

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 the presence of an output schema and annotations, the description is complete. It explains the key return field's semantics and the potential misinterpretation, while the schema covers slug handling in depth. No important behavioral or usage aspects are left undocumented for the tool's complexity.

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 schema description coverage at 100%, the baseline is 3. The tool description merely recaps the slug source ('rows[].slug from search_firms') already fully detailed in the schema, adding no new parameter semantics. The schema itself contains extensive guidance on numeric slugs and refusal behavior, but that belongs to the schema, not the tool description.

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 action ('Fetch one organisation from the published directory') and the specific resource ('published profile'), using the verb 'Fetch' with a precise scope. It distinguishes from siblings by noting it returns public fields and does not return the paid firm-intelligence profile or contacts, making its purpose unambiguous.

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 implies when to use the tool (when a single firm's published profile is needed) and tells the user to source the slug from search_firms, noting that the slug is taken verbatim. It also states exclusions (no paid profile, contacts, or persons), which hints at alternatives, but it does not explicitly name tools like get_firm_intel or search_firms for those needs.

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