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ceaksan

dnomia-knowledge

by ceaksan

search

Retrieve relevant code and documentation from project knowledge using hybrid semantic and keyword search. Filter results by domain, language, file path, and linked projects to find answers quickly.

Instructions

Hybrid semantic + keyword search across project knowledge.

Args: query: Search query text domain: Filter by "all", "code", or "content" project: Project ID (default: DNOMIA_KNOWLEDGE_PROJECT env var) cross: If True, also search linked projects limit: Maximum results to return language: Filter by language (e.g. "python", "typescript") file_pattern: Filter by file path pattern (e.g. "auth", "models.py") show_content: If True, show full chunk content instead of truncated snippet

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
crossNo
limitNo
queryYes
domainNoall
projectNo
languageNo
file_patternNo
show_contentNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the burden of behavioral context. It does convey the hybrid search behavior, the ability to search linked projects, and optional full-content display. Still, it does not disclose aspects like result ordering, pagination semantics, environment variable requirements, or any operational caveats beyond the implied read-only nature of search.

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?

The one-sentence summary is front-loaded and immediately informative, and the Args list is compact yet covers all 8 parameters without unnecessary filler. Every line adds value and no information is redundantly repeated from the schema.

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?

Given the 8-parameter complexity and the presence of an output schema, the description is largely complete: it explains all inputs, the scoped knowledge domain, cross-project search, and filtering options. It could be stronger by explicitly addressing how this tool relates to graph_query or noting any setup prerequisites, but nothing critical is missing for basic invocation.

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 description coverage is 0%, so the description must compensate, and it does by explaining every parameter: query text, domain values, project defaulting to an env var, cross-project behavior, limit, language, file pattern, and content display. The only minor issue is that the project default is described as env var-based while the schema says default null, introducing slight ambiguity.

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 clearly states the tool performs 'Hybrid semantic + keyword search across project knowledge,' giving a specific verb and resource. It does not explicitly differentiate itself from sibling tools like graph_query, but the word 'search' and the hybrid semantic/keyword detail make the purpose unambiguous.

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 the tool should be used when searching across project knowledge, and the parameter list hints at filtering and cross-project scenarios. However, it does not explicitly state when to use this tool versus graph_query or other siblings, nor does it provide 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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