knowledgelib-mcp

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

Annotations declare read-only/idempotent/open-world properties, so description focuses on adding return structure details ('ranked by relevance', 'confidence scores, source counts, token estimates') and workflow sequence. Does not contradict annotations.

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?

Three tightly constructed sentences with zero waste: workflow position and action, return format specification, and error-handling guidance. Front-loaded with the critical 'STEP 1' designation.

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?

Despite lacking an output schema, the description compensates by detailing the return metadata structure. Combined with 100% input schema coverage and complete annotations, this provides sufficient context for a search tool, though it could explicitly highlight the filtering capabilities (domain, region, jurisdiction) present in the schema.

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?

Schema description coverage is 100%, providing complete documentation for all 6 parameters (query, domain, region, jurisdiction, entity_type, limit). Description implies the query parameter through the search verb but adds no syntax details beyond the schema, warranting the baseline score of 3.

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?

Specific verb ('Search') + resource ('knowledgelib.io knowledge units') combination clearly defines the scope. Explicitly distinguishes from sibling 'suggest_question' by stating when to use that alternative instead.

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?

Provides explicit workflow positioning ('STEP 1') and clear fallback instruction ('If no results are found, use suggest_question'). Names the specific alternative tool to invoke in failure cases.

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