suggest_synthesis

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions scanning and identifying clusters but doesn't describe how the tool behaves: e.g., whether it returns a list of topics with metadata, how it handles large datasets, or if it requires specific permissions. For a tool with no annotation coverage, this leaves significant gaps in understanding its operation.

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 appropriately sized and front-loaded: the first sentence states the core purpose, and the second provides parameter details. There is no wasted text, and the structure is clear and efficient, making it easy for an agent to parse quickly.

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 tool has an output schema (which likely describes return values), the description doesn't need to explain outputs. However, with no annotations and only one parameter, the description covers the purpose and parameter semantics adequately but lacks behavioral details (e.g., how clusters are identified, performance considerations). It's minimally viable but could be more complete for a clustering tool.

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 description adds meaningful context for the single parameter 'min_captures', explaining it as 'Minimum number of RC entries on a topic to flag it' and noting the default value. Since schema description coverage is 0% (the schema only provides title and type), the description compensates well by clarifying the parameter's purpose and default, though it could add more about valid ranges or effects.

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 the tool's purpose: 'Scan your Rapid Capture entries and identify topic clusters ready to be synthesized into a SYN page.' This specifies the verb ('scan', 'identify'), resource ('Rapid Capture entries'), and outcome ('topic clusters ready to be synthesized'). However, it doesn't explicitly differentiate from sibling tools like 'search_captures' or 'find_connections', which might have overlapping functionality.

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. It doesn't mention prerequisites (e.g., having Rapid Capture entries), exclusions, or comparisons to sibling tools like 'search_captures' or 'find_connections'. The agent must infer usage context solely from the purpose statement.

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