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Search Technical Knowledge

search_technical_knowledge

Search technical knowledge by combining exact identifier matching, full-text lookup, and vector similarity to return cited, project-aware results across kernel, firmware, WMI, API, and driver docs.

Instructions

5-stage hybrid retrieval across the knowledge base: Combines exact identifier matching, lexical full-text (GIN), and pgvector cosine similarity via RRF.

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes
project_pathNo
confirm_projectNo
project_contextNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the hybrid retrieval mechanics—exact matching, lexical full-text, pgvector cosine similarity, and RRF—but omits important behavior such as read-only safety, latency/rate limits, result ordering, and how project scoping or confirmation parameters affect results.

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 short, front-loaded, and free of filler. However, the phrase '5-stage' is not fully explained, and the brevity contributes to missing operational guidance.

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

Completeness2/5

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

An output schema exists, so return-value details are less necessary. But for a five-parameter hybrid search tool with zero schema description coverage and no annotations, the description does not provide enough information to invoke it correctly, especially around project scoping and confirmation behavior.

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

Parameters1/5

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

Schema description coverage is 0% across five parameters, and the description does not explain any parameter meanings. It never clarifies query, limit, project_path, confirm_project, or project_context, leaving most invocation semantics undocumented.

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 and resource: search technical knowledge via hybrid retrieval across the knowledge base. It clearly states what the tool does, but does not differentiate it from lookup_technical_entity, which may also handle exact identifier lookups.

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

Usage Guidelines2/5

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

There is no explicit guidance on when to use this tool versus lookup_technical_entity or get_kb_health_status. It also does not indicate when a plain keyword search is appropriate versus exact identifier matching or project-scoped retrieval.

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