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governance_report

Turn Spectral findings into a self-contained HTML governance report — severity summary, grouped by rule, framed toward progress.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultsYesSpectral findings to render. An array, or the `{ results: [...] }` object a run returned.

TDQS

B3.3/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It conveys the output nature (a self-contained HTML report) but says nothing about side effects, whether the operation writes files or performs network calls, or if it is a pure read-only transform. Since the tool mutates input into a persistent artifact, the lack of any side-effect disclosure is a meaningful gap.

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

Conciseness4/5

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

The description is a single efficient sentence that front-loads the verb, resource, and output format. The only slightly wasteful element is the vague 'framed toward progress,' which adds tone but little actionable meaning; otherwise there is no redundancy.

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?

For a tool of this low complexity — one documented parameter, no output schema, no nested objects — the description covers the essential facts: the input type, the output format, and the report's structure. The main residual gap is the ambiguous 'framed toward progress' and the absence of any statement about whether the operation is side-effect-free, but these are minor given the tool's simplicity.

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%, and the schema already documents the sole parameter well, including that it may accept an array or the `{ results: [...] }` wrapper object. The description adds only general context ('Spectral findings'), not new meaning beyond the schema, so the baseline 3 is appropriate.

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 names a specific operation — turning Spectral findings into a self-contained HTML governance report — with a concrete output format and content outline (severity summary, grouped by rule). This distinguishes it from report-adjacent siblings like api_scorecard and audit_pipeline. The phrase 'framed toward progress' is vague and slightly muddies the scope, so it stops 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?

Usage is implied rather than stated: an agent can infer it is used after a Spectral run to produce an HTML report, but the description never explicitly says when to choose it over alternatives such as api_scorecard, govern_estate, or audit_pipeline. There is no when-not guidance or mention of exclusions, so the routing burden falls on inference.

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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TDQS

C2.7/5.0
Disambiguation4/5

Most tools have distinct purposes with clear descriptions, reducing ambiguity. However, some overlap exists between search tools like 'find_posts' and 'search_api_evangelist', though they target different scopes (stories vs. unified search). Overall, an agent can reasonably differentiate them.

Naming Consistency3/5

The majority of tools follow a verb_noun pattern (e.g., find_areas, get_post), but several use noun_noun or inconsistent prefixes (e.g., api_coverage, company_gaps, insights_adoption). This inconsistency can confuse pattern recognition, though the pattern is still readable.

Tool Count2/5

With 56 tools, the server is overloaded for a typical MCP context. While the domain is broad, the sheer number risks agent confusion and selection errors. Calibration suggests 25+ tools are excessive, and this server far exceeds that threshold.

Completeness4/5

The tool set covers a wide range of API governance, search, analysis, and generation tasks. There are no obvious dead ends for navigating the API Evangelist network, though some areas (e.g., direct API creation) are intentionally out of scope. Minor consolidation could improve efficiency.

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