team_synthesize

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

No annotations provided, so description carries full burden. It discloses key behaviors: proposes a merged version, shows contributions by author, consensus, union of failures, and canonical lesson. The word 'proposes' implies non-destructive action, which is helpful. Could explicitly state if it modifies or only presents.

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?

Five concise sentences, front-loaded with the core purpose. Each sentence adds value: action, context, output summary, and usage guidance. No wasted words.

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?

Covers what the tool does, the scenario (multiple contributors, same topic), and the output elements (contributions, consensus, failures, canonical version). Could be slightly more detailed about the output format or merging algorithm, but is adequate for a proposal tool with two simple parameters.

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% with both parameters described. The description adds no extra information about parameters beyond the schema's field descriptions. Baseline of 3 is appropriate as schema already documents the parameters adequately.

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?

Description clearly states the tool merges multiple contributors' lessons into one canonical version, using specific verbs ('merge', 'synthesize') and resource ('team brain lessons'). It distinguishes from siblings like brain_federate and brain_diff by focusing on consensus/union across multiple authors on the same topic.

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 two concrete use cases: 'when onboarding new team members or before documenting a process.' While it doesn't list sibling alternatives, the context sufficiently guides when to apply this tool.

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