audit_pipeline
Score a repository's Spectral CI setup against an 8-point maturity rubric and return a prioritized punch-list. Pass a public repo ("owner/name") or files.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Score a repository's Spectral CI setup against an 8-point maturity rubric and return a prioritized punch-list. Pass a public repo ("owner/name") or files.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose side effects, authentication requirements, rate limits, or other behavioral traits. It only mentions input and output, lacking transparency for a tool that might access external repositories.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that front-loads the action and output. Every segment earns its place, with no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is incomplete given no output schema and no annotations. It does not specify the structure of the punch-list, the definition of 'files', or any prerequisites. The mismatch between schema and description adds confusion.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema is empty with additionalProperties true, but the description mentions parameters `repo` and `files`. This adds meaning beyond the schema but is vague on formats and relationships. Schema coverage is 100% due to no parameters, so description compensates partially.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool scores a repository's Spectral CI setup against an 8-point maturity rubric and returns a prioritized punch-list. This distinguishes it from sibling tools, which are diverse and unrelated.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides context for input ('Pass a public repo or files') but does not specify when to use vs alternatives or when not to use. No exclusions or alternatives are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.