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Get audit status

get_audit_status
Read-only

Poll a running audit by run_id (from run_audit or list_audits). Status queued/pending/running means keep polling (every 15-30 seconds): the response includes a progress field (phase, message, page/link counts) when available. Status queued means cloud audits are busy and the run is waiting for a slot: it starts by itself, and its queue field gives its position, a rough eta_minutes (null when unknown) and a message to pass on. Do not start the audit again. Status completed means the report is ready: call get_report with the same run_id. Status failed/cancelled includes the error and completion reason. A failed run also carries failure_reason_code (one of dns, tls, connection, timeout, http_4xx, http_5xx, redirect, robots, audit_timeout, stalled, unknown) and failure_next_step, so you can act on the cause rather than parsing the error sentence, plus failure_diagnostics: attribution (target_site, squirrelscan, mixed or unknown; never guess past it), category, stage, the observations that support it, what remains uncertain, and the bounded list of fetch attempts; legacy is true when the run predates recorded evidence. A cancelled run has none of these, because it was stopped rather than defeated by the site. Once the run has a report, health_score and issues_found are read from that published report, so they equal get_report's summary.healthScore and its failed+warnings (#1700). health_score is null for a blocked or unreachable site: that audit has no meaningful grade. A completed run also carries a schedule field describing the website's recurring audits: state is off, active, capped, unschedulable or paused, cadence_label reads as a sentence, settings_url is where the user changes the cadence or turns it off, and cap says how many scheduled sites the plan funds and how many are spent. estimated_cost is the most those runs spend per run, week and month. Recurring audits turn on by themselves after a site's first successful audit and each run costs credits, so pass that on rather than leaving the user to discover the charge.

Input Schema

NameRequiredDescriptionDefault
run_idYesRun id returned by run_audit or listed by list_audits.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +{}
  2. Changed2 schema fields changed
    • changedInput schema / $schema
      Previous value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"
    • removedInput schema / additionalProperties
      Removed value: -false
  3. First observed

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description still adds substantial behavioral context beyond them (queue position/ETA semantics, terminal status meanings, recurring-audit side effects and credit charges), but the score reflects that much of the value here is return-value semantics rather than traits the annotations couldn't already convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the core polling loop, but the body sprawls into an extremely long block covering failure codes, diagnostics attribution, health_score provenance, and scheduling economics. Much of it earns its place, yet the density and run-on sentences hurt scannability for an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the full burden of describing the response surface — status values, progress fields, failure_reason_code enum, failure_diagnostics, health_score, schedule and estimated_cost — and it does so thoroughly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% for the single run_id parameter and the schema already documents it. The description only restates its origin (run_audit or list_audits), matching the baseline for a fully documented schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource (poll a running audit by run_id) and immediately anchors run_id's origin to run_audit/list_audits, distinguishing it from the sibling that starts a run and the sibling that fetches the report.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicit polling cadence (every 15-30 seconds), explicit 'do not start the audit again', and explicit routing to get_report on completion. Status-specific next steps are spelled out rather than inferred.

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

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