create_co_scientist_run

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

With no annotations provided, the description carries the full burden. It does disclose the main side effect: it creates two linked sessions in one call and prevents transcript leakage between generation and verification. However, it does not clarify return behavior, whether the workflow runs asynchronously, resource costs, or any permission prerequisites, which leaves the behavioral picture incomplete.

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 uses clear section headers, front-loads the core action, and provides concise trigger conditions, workflow placement, and parameter semantics. Every sentence contributes meaningful guidance without extraneous detail.

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 multi-session workflow creation tool, the description covers purpose, triggers, placement, and all parameters. It lacks any mention of return values or follow-up steps, and with no output schema present, that leaves a moderate gap. Still, for selecting and invoking correctly it is largely sufficient.

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 description coverage is 0%, so the description must supply parameter meaning, and it does. Each of the four parameters receives a useful explanation beyond type/default information: topic is the research objective, constraints are optional limits or domain notes, created_by identifies the creator, and top_k specifies how many hypotheses go to verification.

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 opens with a precise verb and resource: 'Create a linked Co-Scientist generation and verification workflow.' It further clarifies scope by stating it creates both generation and verification sessions in one call, cleanly distinguishing it from related tools like start_hypothesis_verification or create_co_scientist_final_report.

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 'AUTOMATIC TRIGGERS' section explicitly states when to call the tool: when a user asks to start a Co-Scientist run, when two linked sessions are needed, or when hypotheses must be generated and verified without transcript leakage. It also notes the workflow position: use after confirming topic scope. However, it does not explicitly mention alternatives or when not to use it.

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