Reason About Objective

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

Beyond the readOnlyHint annotation, the description discloses that the tool does not take action, uses the active AI provider, and includes specific error-handling behavior if the provider is not configured. It also describes the return structure for JSON format. This adds significant richness beyond the annotations and fully explains the tool's non-mutating, provider-dependent nature.

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: purpose, pipeline placement, what it does not do, args, returns, examples, and error handling. It is front-loaded with the primary purpose and every section adds value. The length is justified by the inclusion of a return schema (since no output schema is provided) and error handling, making it efficient rather than verbose.

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?

The description is complete for an agent to call this tool correctly. It covers the input parameters, provides a return schema for JSON format, explains the provider dependency and how to inspect it (see chaoscore_inspect), gives usage examples, and documents error cases. With no output schema present, the included return structure is essential and well-provided.

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%, so baseline is 3. The description adds a bit of extra clarity, e.g., for 'context' it specifies the exact structure '[source, content]' and for 'response_format' it notes the default. It also explicitly lists enum values and says 'empty array if none.' While mostly redundant with the schema, it provides a slightly more concise and action-oriented explanation, justifying a 4.

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 states a specific action ('Analyze an objective and its context BEFORE committing to a plan') with a clear resource (the objective and context) and delivers structured analysis. It explicitly distinguishes itself from siblings: 'Does NOT produce an executable plan... call chaoscore_plan next.' The purpose is unambiguous and differentiates well from chaoscore_plan, chaoscore_execute, etc.

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 concrete when-to-use and when-not-to-use guidance with an example ('Should I migrate memory storage...?') and explicitly references the alternative ('use chaoscore_plan directly'). It also frames this as the first stage in the Cognitive Core loop, giving clear context for when this tool should be invoked.

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