Open an OKF bundle

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds valuable behavioral context beyond those hints: it explains the return shape (JSON structure with counts and health summary), error behavior for missing directories or non-concept folders, and the default response_format. No contradictions with 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?

The description is well-structured with clear sections: intro, bundle definition, Args, Returns, Examples, and Error Handling. The 'Start here' opener is immediately useful, and each section adds necessary context without fluff. The length is justified by the tool's role as an entry point.

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?

Given the absence of an output schema, the description fully compensates by including a detailed return structure. It covers usage context, error cases, and relationships to sibling tools. The bundle definition provides essential domain knowledge for an AI agent, making the description complete for this tool's complexity.

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 coverage is 100%, so baseline is 3. The description adds marginal value by including an Args section that restates defaults and types, plus concrete examples like bundle_path='./knowledge' and an explanation that response_format 'json' is for machine processing. This is helpful but not essential beyond the schema.

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?

The description uses a specific verb ('Open') and resource ('OKF bundle') and clearly states it describes the bundle's contents with 'Start here.' It distinguishes from siblings by noting when not to use it (if you already know the concept id, use okf_get_concept).

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?

Explicitly provides 'Use when' examples, including concrete bundle_path values and a comparison to okf_list_concepts, plus a 'Don't use when' exclusion with a named alternative. This gives clear guidance on when to choose this tool over siblings.

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