Synthesize

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: the session stays open after synthesis, contradictions should be noted, and gaps suggest next steps. This goes beyond a generic 'synthesizes' statement.

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 and front-loaded with the purpose. It is a bit lengthy with multiple paragraphs, but each sentence provides useful guidance with little fluff, so it remains appropriately concise for the tool's complexity.

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 thoroughly covers the tool's purpose, use timing, and behavior, and the input schema is complete. The only minor gap is that it does not explicitly describe the tool's return value or output, which matters because there is no output 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 coverage is 100%, giving a baseline of 3. The description adds meaning by explaining what should go into `synthesis`, `contradictions`, `gaps`, and `recommendations` (e.g., agreement, contradiction, gaps), enriching the schema's short descriptions.

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 verb and resource: 'Synthesize findings across all applied lenses into a unified view.' This clearly distinguishes it from sibling tools like start_analysis and apply_lens, which have different purposes.

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?

It explicitly says to call after applying 2+ lenses, and it advises what to do if gaps remain (apply more lenses and synthesize again). While it doesn't explicitly mention alternatives like get_strategy, the usage condition is clear and well contextualized.

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