research_project_continue

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

With no annotations, the description carries the full burden. It discloses the return data comprehensively, implying a read operation. However, it does not explicitly confirm non-destructiveness or mention authorization needs, leaving slight ambiguity about side effects.

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 two sentences, front-loaded with the action and key return details. Every phrase adds value with no redundancy.

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 tool with one parameter and no output schema, the description covers the purpose, return structure, and usage timing sufficiently. It lacks error handling guidance but is otherwise complete for an agent's decision-making.

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?

The single parameter 'projectId' is self-explanatory, but schema coverage is 0% and the description adds no additional meaning (e.g., format, source). It is adequate but does not compensate for the lack of schema 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 clearly states the tool resumes context from a paused research project and specifies the exact return data (central question, 50 findings with details, open gaps). This distinguishes it from sibling tools like research_project_create or research_finding_add.

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 explicitly says to use this BEFORE asking new questions in an existing project to avoid duplication, providing clear usage context. It does not explicitly name alternatives but implies when not to use (e.g., for new projects).

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