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lorsabyan

okf-mcp-server

by lorsabyan

Search an OKF bundle

okf_search
Read-onlyIdempotent

Search OKF bundle concepts using full-text query to find matches across titles, IDs, types, tags, descriptions, and bodies, then review results with metadata.

Instructions

Full-text search over a bundle's concepts — titles, ids, types, tags, descriptions, and bodies.

Args:

  • bundle_path (string): directory containing the bundle

  • query (string): search text, 1-200 characters

  • limit (number): 1-50, default 10

  • response_format ('markdown' | 'json'): default 'markdown'

Returns: { "query": string, "count": number, "results": [{ "id": string, "title": string, "type": string, "description": string, "tags": string[], "status": ..., "trust": ..., "updated_at": string, "stale_since": string }] }

Examples:

  • Use when: "Where is churn defined?" -> query="churn"

  • Use when: you do not know the concept id

  • Don't use when: you have the exact id (use okf_get_concept, it is cheaper)

Error Handling:

  • No matches returns the available types and tags to redirect the search

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum results
queryYesSearch text
bundle_pathYesPath to the OKF bundle directory (a folder of .md files). Absolute paths are safest.
response_formatNo'markdown' for reading, 'json' for machine processingmarkdown
Behavior5/5

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

The description goes well beyond the annotations (readOnlyHint, idempotentHint) by detailing the full-text search behavior, the return object shape, and error behavior when no matches are found. It also clarifies defaults for limit and response_format, adding genuine behavioral context.

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 description is well-structured with clear sections (Description, Args, Returns, Examples, Error Handling). Every section is concise and informative; there is no fluff or repetition of schema fields that are already self-explanatory.

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

Completeness5/5

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

Despite having no output schema, the description provides a full return shape, making it self-contained. It also covers edge cases (no matches) and offers concrete usage examples. Given moderate complexity and rich sibling context, this is complete.

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 baseline is 3. The description adds extra semantic nuance: 'Absolute paths are safest' for bundle_path, 'markdown' for reading vs 'json' for machine processing, and the 1-200/1-50 ranges in Args. This goes beyond the schema descriptions.

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 opens with a specific verb and resource: 'Full-text search over a bundle's concepts'. It lists the exact scopes (titles, ids, types, tags, descriptions, bodies) and clearly differentiates from sibling tools like okf_get_concept by explicitly stating when not to use it.

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?

The description provides explicit 'Use when' and 'Don't use when' guidance, naming the alternative tool (okf_get_concept) and the rationale (it is cheaper). This is exactly the kind of practical selection guidance an agent needs.

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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