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cvcue_api_search

Search CV-CUE API endpoints by keyword, module, or HTTP method to find matching paths and operations for API discovery before inspecting schema or executing a request.

Instructions

Search CV-CUE API endpoints (step 2 of API discovery).

Matches every word of keyword against path, operationId, summary and description. Use cvcue_api_schema on a result before cvcue_api_execute.

Input Schema

NameRequiredDescriptionDefault
limitNoMax results (default 40)
moduleNoOptional module filter (from cvcue_api_modules)
keywordYesSearch term, e.g. 'reboot', 'ssid', 'packet capture', 'rogue'
method_filterNoOptional HTTP method: GET/POST/PUT/DELETE

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

No annotations exist, so the description carries the full burden, and it does disclose the non-obvious matching semantics: every word of the keyword must match across path, operationId, summary and description (implicitly AND-style multi-field matching). It does not describe the shape of returned results or whether the search is paginated beyond the limit parameter, which keeps it short of a 5.

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?

Three short clauses, zero filler, with the identity and pipeline position front-loaded and the downstream tool routing last. Every sentence earns its place.

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 four-parameter, read-only discovery tool with full schema coverage and no output schema, the description covers purpose, matching behavior and the surrounding workflow. The remaining gap is that an agent cannot tell what a result entry looks like (identifier, method, path), which it would need to hand off to cvcue_api_schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline would be 3, but the description adds real meaning for the required keyword parameter by specifying which fields it is matched against and how (every word). It adds nothing new about limit, module or method_filter, which is acceptable since the schema documents them fully.

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 names a specific verb and resource ('Search CV-CUE API endpoints') and positions itself in a discovery pipeline ('step 2 of API discovery'), which cleanly separates it from cvcue_api_modules (step 1), cvcue_api_schema and cvcue_api_execute. An agent can distinguish it from all siblings without opening a schema.

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 states the exact follow-up workflow: use cvcue_api_schema on a result before cvcue_api_execute. Combined with the 'step 2' framing, the when-to-use and the alternatives are both explicit, leaving nothing to inference.

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