Returns the full dossier for a single firm in the directory: description, headquarters, founded year, employee band, services, locations, and directory meta (publisher, claim URL, takedown URL).
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the return contents in detail, including directory meta (claim URL, takedown URL), which is useful. However, it does not mention error behavior (e.g., unknown slug), data freshness, authentication, or whether this is a read-only operation, though 'Returns' implies a non-mutating read.
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 concise and front-loaded with the primary action, followed by a structured list of return fields. Every line adds useful detail, and there is no redundant or filler content.
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?
The tool is low-complexity (one parameter, no output schema), and the description covers the main return fields. However, it lacks guidance on the slug source, error handling, and relationship to the sibling directory tools, leaving some important context implicit for an agent.
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 0% schema description coverage and a single required 'slug' parameter, the description's only hint is 'single firm in the directory', which does not explain what a slug is, its format, or how to obtain it. The description adds minimal value beyond the schema's bare 'Slug' title, failing to compensate for the low coverage.
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 verb 'Returns' and the resource 'the full dossier for a single firm in the directory', enumerating the exact contents (description, headquarters, founded year, etc.). This distinguishes it from siblings like find_professional_services_firm (discovery) and get_services (specific subset), making the 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 this tool: when you need a comprehensive profile of a known single firm, identified by slug. It does not explicitly mention alternatives or when not to use it, but the context is clear enough for a retrieval tool, and siblings like find_professional_services_firm are not referenced as alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clear, distinct purpose. The get_* tools retrieve different data types (services, firm profiles, case studies, audit offerings), the request_* tools target different actions (introduction, quote, strategy session), and assess_ai_readiness and claim_listing are unique. No two tools appear to do the same thing.
Tool names are all snake_case and follow a verb_noun structure, but the verbs vary (assess, claim, find, get, request) rather than using a single consistent pattern. The get_ and request_ subgroups are internally consistent, so the naming is readable and predictable despite the variety.
With 10 tools, the server is well-scoped. Each tool serves a clear function in the marketing/directory domain: discovery (find, get), engagement (request, claim), and assessment (assess, get_wcag_audit). The count is neither sparse nor overwhelming.
The surface covers the core workflows: searching the directory, retrieving firm details and services, requesting intros/quotes/sessions, claiming listings, and checking AI readiness. Minor gaps exist (e.g., no tool to update a listing or access the compliance registry directly), but these are not likely to cause agent failures.
