screen_co_scientist_scope

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

With no annotations provided, the description carries the full behavioral burden. It discloses the return contents (allowed status, risk level, matched categories, reasons, required approvals) and the blocking implication of allowed=False, making the tool's gatekeeper behavior clear. It does not explicitly state whether the tool is read-only or whether it triggers approvals, but the screening framing and decision output are sufficiently transparent.

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 with a front-loaded purpose, clear trigger bullets, workflow position, parameter explanations, and return-value summary. Every section earns its place, and the length is appropriate for the tool's role as a decision gate.

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 no output schema and no annotations, the description sufficiently explains what the tool returns and how the agent should act on it. It covers parameters, return fields, workflow position, and the critical allowed=False behavior, making the tool actionable without requiring additional context.

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 compensate, and it does. It explains topic as "Proposed research objective" and constraints as "Optional hard limits, domain notes, or requested actions," adding meaning beyond the bare string/array types. This is enough for an agent to populate both parameters correctly, though examples or formatting details are not provided.

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 specific verb and resource: "Screen a proposed Co-Scientist run before creating sessions." It clearly differentiates this tool from siblings like create_co_scientist_run by positioning it as the first gate before session creation, and its triggers name Co-Scientist, hypothesis generation, and hypothesis verification.

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 explicit automatic triggers with concrete conditions, states the workflow position as "First gate before any Co-Scientist session creation," and gives a clear post-condition: "If allowed=False, do not create a Co-Scientist session." This gives the agent actionable when-to-use and when-to-stop guidance.

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