Query the current state of any in-flight async operation by operation_id.
WHEN TO USE: Use to poll the state of a pending_async operation when no webhook callback has arrived or to check progress. WHEN NOT TO USE: Do not poll more frequently than once per 10 seconds — use webhook delivery for real-time updates instead. COST: free - no key required LATENCY: ~50ms
| Name | Required | Description | Default |
|---|---|---|---|
| operation_id | Yes |
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, idempotentHint=true, and destructiveHint=false, so the description is not required to re-state those. It adds useful behavioral context beyond annotations: polling cadence guidance, approximate latency, and cost/auth expectations. No contradictions with the 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 well-structured, front-loaded with the core purpose, and uses clear WHEN TO USE / WHEN NOT TO USE sections. Every sentence adds actionable information for call selection or invocation, including cost and latency data.
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 simple one-parameter polling tool, the description covers the core purpose, usage policy, and operational constraints. The main gap is that there is no output schema and the description does not describe the response shape or status values, but the agent has enough to invoke the tool correctly and interpret that it returns current state.
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 0%, so the description carries the burden of explaining operation_id. It does identify operation_id as the identifier of the in-flight async operation, which gives basic semantics, but it does not explain the format, provenance, or expected values (e.g., how the operation_id is obtained).
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 identifies the verb ('Query') and resource ('the current state of any in-flight async operation'), keyed by operation_id. This is specific enough for an agent to understand exactly what the tool does and to distinguish it from sibling tools like get_outcome.
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 explicitly states when to use the tool (poll pending_async when no webhook arrived, check progress) and when not to use it (polling more than once per 10 seconds, using webhook for real-time updates). This gives the agent clear decision criteria and mentions the preferred alternative.
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.
Most tools target clearly distinct compliance subdomains: messaging compliance, sanctions screening, trade restrictions, company verification, and cost preview. The main overlap is between map_trade_restriction and screen_sanctions, since both screen parties against sanctions lists, but their descriptions differentiate trade-level screening from dedicated name screening well enough.
Tool names mostly follow a consistent snake_case verb_noun pattern: check_compliance, get_outcome, get_status, preview_cost, screen_sanctions, verify_company_record. self_test is the one minor deviation since it reads more like a noun than an imperative verb_object name, but it does not break the overall pattern.
Eight tools is a well-scoped size for a compliance pre-flight server. Each tool has a distinct role, and the count is neither bloated nor too thin for the apparent domain.
The core compliance workflows are covered: messaging pre-flight checks, sanctions screening, cross-border trade restrictions, company registry verification, and cost/status helpers. The main gaps are intentional exclusions like PEP screening, export-control product classification, and consent management, which are documented but prevent the set from being a fully comprehensive compliance suite.