analyze_schema_candidates

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

No annotations are provided, so the description carries full burden for behavioral disclosure. It does not state whether the operation is read-only, if authentication is required, or if it modifies data. The description implies an analytical read operation but lacks explicit confirmation.

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 two sentences that directly convey the tool's function and output. No redundant information. It is front-loaded with the core purpose and structured efficiently.

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 that there are no annotations and no output schema, the description covers the basic purpose but lacks details about return format, error conditions, and edge cases. For a tool with 4 parameters, minimal behavioral context is 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?

The input schema has 100% description coverage, so the baseline score is 3. The description does not add additional meaning beyond the schema: it does not explain how parameters like entity_type or user_id affect the analysis, nor the impact of min_frequency and min_confidence thresholds.

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 clearly states it analyzes raw_fragments to identify fields for schema promotion, with recommendations and confidence scores. The verb 'analyze' and resource 'schema_candidates' are specific. However, it does not differentiate itself from the sibling tool 'get_schema_recommendations', which may have overlapping purpose.

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?

The description provides no guidance on when to use this tool versus alternatives (e.g., get_schema_recommendations, register_schema). It does not state prerequisites, such as whether raw_fragments must already exist, or when it is inappropriate to use.

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