export_co_scientist_findings

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

No annotations are present, so the description carries the disclosure burden. It is transparent about filtering behavior ('intentionally skips inconclusive, contradicted, and unsafe/out-of-scope hypotheses') and the destination library. It could still mention duplicates/overwrite behavior or return values, but core side-effect selection is clear.

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?

Well-organized with AUTOMATIC TRIGGERS, WORKFLOW POSITION, and PARAMETERS sections, and the core purpose is front-loaded. The skip/unsupported idea is repeated a couple times, but the overall length is reasonable and every section adds value.

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?

For a moderate-complexity tool with no annotations or output schema, the description covers what it does, when to call it, which parameters to provide, and what it intentionally excludes. Missing return/error details are a minor gap, not a blocker for correct invocation.

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 0%, but the PARAMETERS section compensates by explaining each parameter's meaning and optionality ('created_by: Session orchestrator agent_id or model (required)', 'project: Optional...'). This adds practical meaning beyond the bare JSON schema, though run_id could use a bit more format detail.

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?

States a specific action ('Export ... claims into the main knowledge library') and identifies the resource type ('supported Co-Scientist claims') and destination. This wording differentiates it from generic library or finding tools by tying it to Co-Scientist claims and their supported status.

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 explicit automatic trigger conditions ('A final Co-Scientist report exists...', 'user explicitly asks...') and places it in the workflow ('Use after final report review'). It also tells what will be skipped, but it does not name alternatives or explicitly state when not to use it compared to sibling tools.

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