suggest_approach

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

No annotations exist, so description carries full burden. It does not disclose whether the tool is read-only, has side effects, or requires permissions. Minimal behavioral context beyond the recommendation claim.

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?

Extremely concise (3 lines), front-loaded with key usage signal ('CALL WHEN UNSURE'). Every sentence adds value without 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?

Covers core purpose and key considerations but lacks output details (no output schema). Only addresses three of eight sibling tools, missing guidance for alternatives like search_tools or list_workflows.

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 covers 100% of parameters, so baseline is 3. Description adds marginal context by mentioning considerations (e.g., operation count, data size) that loosely map to parameters, but does not specify how each parameter influences output.

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 explicitly states the tool's purpose: analyzing tasks to recommend between execute_code, execute_workflow, or direct MCP. It uses specific verbs ('analyzes', 'recommends') and distinguishes from sibling tools by specifying when to call it.

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 clear 'call when unsure' condition and lists considerations (operation count, data size, existing workflows). Lacks explicit exclusions or alternatives beyond the three mentioned tools, but guidance is strong.

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