Build a source-linked contractor-verification checklist for up to 12 supported states. Returns official lookup links, scope boundaries, and freshness caveats; it does not scrape, cache, or resell license records.
| Name | Required | Description | Default |
|---|---|---|---|
| states | Yes | State codes to include. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. On top of that, the description adds concrete behavioral disclosure: what it returns ('official lookup links, scope boundaries, and freshness caveats') and what it deliberately does not do ('does not scrape, cache, or resell license records'). This negative-space disclosure is genuinely valuable and fully consistent with the read-only annotation — no contradiction.
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 sentences, roughly thirty words, with the core action front-loaded ('Build a source-linked contractor-verification checklist') and the clarifying exclusions following immediately. Every clause earns its place; there is no boilerplate, redundancy, or restating of the tool name.
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 tool with a single required parameter, rich annotations, and no output schema, the description covers the key ground: purpose, output contents (links, scope boundaries, freshness caveats), and behavioral boundaries. The only minor gap is that it does not describe the output's structural form (e.g., per-state checklist layout) or error behavior for unsupported state codes — but given the low complexity, this is a small omission.
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 description coverage is 100% — the single 'states' parameter is already documented as 'State codes to include' with a 12-value enum. The description adds marginal context by specifying 'up to 12 supported states,' which clarifies the array's intended maximum beyond what the schema conveys. Per the baseline rule for high coverage, this is adequate but does not substantially exceed the schema's documentation.
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 states a specific verb and resource: 'Build a source-linked contractor-verification checklist for up to 12 supported states.' It clearly defines the deliverable (a checklist of official lookup links) and the negative space ('does not scrape, cache, or resell license records'). However, it does not explicitly differentiate from closely-related siblings like contractor_license_sources or wa_contractor_verify, leaving the multi-state vs single-state distinction implicit in the name only.
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?
Usage context is implied by 'for up to 12 supported states' and the state enum in the schema — the agent can infer this is for multi-state contractor verification. But the description offers no explicit when-to-use guidance, no exclusions, and does not name alternatives such as contractor_license_sources (for raw license sources) or wa_contractor_verify (for single-state verification).
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.
Several tool clusters overlap heavily—company due-diligence and risk tools (counterparty_risk_score, company_trust_check, entity_dossier, issuer_diligence_dossier, resolve_entity, entity_resolve), carrier vetting tools, sanctions screening tools, and recall tools all have subtle boundary distinctions. While descriptions are detailed, an agent navigating 294 tools will frequently struggle to pick the right one.
Most tools follow a readable snake_case domain-prefix pattern (fdic_, edgar_, sanctions_, congress_), which helps. However, verb placement is inconsistent—search_available_datasets vs cdc_dataset_query, resolve_entity vs entity_resolve—and synonyms like search, lookup, get, detail, fetch, and status are used interchangeably.
294 tools is an extreme number for a single MCP server, far beyond what an agent can reliably hold in context or select from accurately. The presence of tool-group discovery helpers mitigates but does not solve the fundamental scale problem.
The data breadth is genuinely extensive, covering finance, health, legal, real estate, transportation, energy, cyber, education, and many other domains, often with generic query fallbacks. Still, some capabilities are shallow or incomplete—package tracking stops at a link, property tools are demo-only in places, and caselaw coverage is limited—so it is not a fully complete surface.