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probe_report

Audit an MCP server by static linting and optional behavioral fuzzing, then score conformance across four dimensions and produce a Markdown report.

Instructions

Run introspect + lint (and fuzz when requested) against the target, score the result on four dimensions, and return a Markdown report with the overall score, letter grade, per-dimension breakdown, findings, and fuzz table.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fuzzNoWhen true, run the behavioral fuzzer before scoring. Default false; only static dimensions are measured when omitted.
maxToolsNoForwarded to probe_fuzz when fuzz=true. Defaults to 10.
connectionIdNoIdentifier returned by probe_connect. Defaults to the most recent connection.
fuzzDestructiveNoForwarded to probe_fuzz when fuzz=true. Also fuzz tools annotated destructiveHint:true (default false — the dry-run safety guard).
Behavior3/5

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

Annotations provide readOnlyHint=false and openWorldHint=true, indicating possible side effects. The description adds context about running optional fuzz and defaults, but does not elaborate on behavioral traits like destruction, auth needs, or rate limits beyond what annotations and schema 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.

Conciseness5/5

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

One sentence efficiently lists all actions and output components with no filler. Every part earns its place; it is front-loaded with the main verb and resource.

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?

Given there is no output schema, the description fully explains the return value (Markdown report with overall score, letter grade, per-dimension breakdown, findings, fuzz table). It also covers optional fuzz behavior and defaults, making the tool's behavior complete for selection and invocation.

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 100%, so baseline is 3. The description adds minor context (e.g., fuzz triggers behavioral fuzzer) but does not significantly enhance parameter meaning beyond the schema's own descriptions and defaults.

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 clearly states the verb ('run introspect + lint + fuzz') and the resource ('the target'), specifies the output ('Markdown report with score, grade, breakdown, findings, fuzz table'), and distinguishes from siblings by combining multiple operations into one.

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 description implies that fuzz is optional via 'when requested' and gives a default for fuzz. However, it does not explicitly say when to use this tool versus individual sibling tools (e.g., probe_lint, probe_fuzz) or provide any exclusions or alternatives.

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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