perform_research

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

With no annotations provided, the description carries the full burden. It discloses the cascading search order and fallback to web search, and mentions confidence thresholds. However, it does not explain side effects (if any), authentication needs, rate limits, or whether the tool is read-only, leaving behavioral gaps.

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 a single sentence with a colon-separated list, which is concise and efficient. It could be slightly more structured (e.g., bullet points) but contains no unnecessary 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?

Given 5 parameters, full schema coverage, and no output schema, the description explains the process but omits return value format, error handling, or success criteria. For a comprehensive research tool, output behavior should be clarified.

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%, so baseline is 3. The description adds overall context about cascading sources but does not enhance individual parameter semantics beyond what the schema already provides. Parameters like projectPath and adrDirectory are adequately described in the schema.

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 verb 'perform research' and specifies the resource as 'cascading sources' with a clear order: project files, knowledge graph, environment resources, web search fallback. This distinguishes it clearly from sibling tools like llm_web_search or analyze_environment.

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 implies usage for answering research questions but does not explicitly state when to use this tool versus alternatives like search_codebase or analyze_* tools. No exclusions or alternative recommendations are provided.

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