suggest_workflow

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

No annotations are provided, so the description fully carries the behavioral transparency burden. It clearly states the tool is advisory, uses a 'local deterministic router', and returns candidate actions without executing them. This provides sufficient insight into its non-destructive, read-only nature.

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 extremely concise: two sentences that front-load the purpose and then add essential behavioral clarification. Every sentence 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?

Given the tool has no output schema, 6 optional parameters (0% schema coverage), and no annotation safety net, the description is too sparse. It explains the overall behavior but leaves the agent guessing about parameter usage and return format, which is inadequate for effective tool invocation.

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%. The description does not mention any of the 6 parameters (goal, files, top_k, context, problem, min_score) or their meaning. An agent has no guidance on how to set these parameters to influence the suggestions, making this a critical gap.

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's purpose: 'Suggest explicit manual next tool calls from Brain Region routing.' It specifies the verb (suggest), resource (next tool calls), and context (Brain Region routing). It also lists example candidate tools (plan_task, consult_problem, etc.), distinguishing it from siblings.

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 states it is 'advisory only' and that it 'never calls those tools or models,' clarifying when to use it (for suggestions) and what it does not do. It implies when not to use: when direct execution is needed, use sibling tools directly. However, it does not explicitly state alternatives or exclusions.

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