profitpilot_analyze

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

With no annotations, the description carries the full burden of behavioral disclosure. It clearly reveals key traits: the server does not call external LLMs, it produces structured prompts for the client to execute, and the analysis is multi-turn. This materially prevents an agent from assuming the tool runs a local model or returns a final answer immediately.

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 longer than average but earned: the flow list and agent domains are organized and relevant. The main behavioral facts are front-loaded, and the detail supports correct multi-step usage rather than padding.

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, the description adequately conveys what the first call produces (a reasoning prompt) and outlines the full interaction pattern. It does not detail error or session lifecycle behavior, but for an initial invocation tool the guidance is sufficient.

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 the schema already documents role, problem, verbose, and sessionId. The description adds little beyond tying 'problem' to the flow and noting the client later sends a response; this is marginal but acceptable given the schema's completeness.

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 concrete verb and resource: it executes the full ProfitPilot pipeline using Chain of Thought. It then names profitpilot_continue in the numbered flow, making the division of labor between the two sibling tools explicit. Even though 'completo' is slightly broad, the flow makes clear this is the entry point for the iterative analysis.

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 numbered flow states exactly when analyze should be called (with the problem) and when continue should be called (with the model's response), and notes the cycle repeats until complete. It does not explicitly say when to use status or reset instead, but the core when-to-use guidance is present and unambiguous.

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