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get_findings

Read failures from a previous assessment report and filter them by minimum severity (critical, high, medium, low) to prioritize issues.

Instructions

Read failures from a previous assessment.json, filtered by minimum severity (critical, high, medium, low).

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": {
      "report_json": "<report_json>"
    },
    "name": "get_findings"
  }
}

Input Schema

NameRequiredDescriptionDefault
report_jsonYes
min_severityNolow

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations supplied, the description must carry the behavioral burden; 'Read' does establish a non-mutating operation, and the severity ladder clarifies that filtering is threshold-based rather than exact-match. It says nothing about error behavior for a missing/invalid report, whether results are ordered, or limits, so it does not fully cover a no-annotation tool.

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?

A single sentence with the action, source, and filter all front-loaded; every clause carries information and there is no filler or repetition.

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

Completeness4/5

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

The tool is simple, an output schema exists so return values need no explanation, and the filter semantics are given. The only real gap is the format of the required report_json argument, which matters because schema coverage is zero.

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 description coverage is 0%, so the description is the only source of parameter meaning. It explains min_severity well by listing the accepted levels (critical, high, medium, low), but it never clarifies whether report_json is a filesystem path, a raw JSON string, or an identifier — a meaningful ambiguity for the sole required parameter.

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

Purpose4/5

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

The description gives a specific verb ('Read') and resource ('failures from a previous assessment.json') plus the filtering dimension, so it is clearly distinguishable from run_assessment (which produces the report) and the list_* tools. It does not explicitly name a sibling to contrast with, which keeps it short of a 5.

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

Usage Guidelines3/5

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

The phrase 'from a previous assessment.json' implies a prerequisite (an assessment must already have been run) and implies this is the post-run triage step, but it never states when to use this versus re-running an assessment or when not to use it. Usage is inferable rather than stated.

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