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Get audit results

get_audit
Read-onlyIdempotent

Poll an audit started with audit_page. Pass the job_id. When status is running, call again. When complete, returns findings grouped as priority / worth considering / not measured. Does NOT start a new audit. Does NOT charge. Does NOT invent checks. An empty group means none, not that the site is perfect.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "job_id": "<job_id>"
    },
    "name": "get_audit"
  }
}

Input Schema

NameRequiredDescriptionDefault
job_idYesThe job_id from audit_page.
audit_idNoAlternative to job_id: the id of a stored audit report.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / audit_id / description
      Added value: +"Alternative to job_id: the id of a stored audit report."
  2. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description explains polling behavior, returned finding groups, the meaning of an empty group, and that it does not charge or invent checks. These are meaningful operational details not captured by annotations or schema alone.

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

Conciseness5/5

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

The description is front-loaded with the core action and polling behavior, then adds compact constraints. Every sentence contributes useful routing or behavioral information without verbosity.

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?

There is no output schema, so the description carries the burden of explaining results. It does so by naming the grouped findings categories and clarifying empty-group semantics, which is sufficient for an agent to call and interpret the tool correctly.

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?

The schema fully documents both job_id and audit_id, including that audit_id is an alternative to job_id. The description only repeats the job_id requirement and does not add new parameter-level semantics, so the high schema coverage puts this at baseline 3.

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?

The description states a specific verb and resource: it polls an audit started by audit_page and returns findings. It explicitly distinguishes itself from the sibling audit_page by saying it does NOT start a new audit.

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?

It gives clear usage instructions: pass the job_id, call again while status is running, and expect findings when complete. It also names the prerequisite tool, audit_page, making the workflow unambiguous.

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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