get_disqualification_signals

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

Annotations already declare readOnlyHint=true and openWorldHint=true, indicating a safe, exploratory operation. The description adds behavioral context by explaining the three analysis layers (ICP fit, anti-pattern matching, churn patterns) and the actionable outcome ('tells you whether to keep investing or walk away'), which goes beyond annotations. However, it does not disclose details like rate limits, authentication needs, or specific output format.

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 front-loaded with the core purpose in the first sentence, followed by specific analysis details and outcome. It uses two efficient sentences with zero wasted words, each earning its place by clarifying the tool's function and value.

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's complexity (10 parameters, nested objects) and lack of output schema, the description is reasonably complete for a read-only analysis tool. It explains the analysis method and decision outcome, but does not detail the return format (e.g., score, reasons, confidence) or error handling, which could be important given the open-world hint.

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 100%, so the schema fully documents all 10 parameters. The description does not add any parameter-specific semantics beyond what the schema provides, such as explaining how 'techStack' influences disqualification or how 'dealContext' affects the analysis. It only implies general usage of company and deal data.

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 with specific verbs ('find out', 'runs', 'tells you') and resources ('company', 'three layers of signal'), and distinguishes it from siblings by focusing on disqualification signals rather than scoring, classification, or prospecting. It explicitly answers 'whether to keep investing or walk away', which is unique among the listed tools.

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 provides clear context for when to use this tool ('wasting time on a deal that won't close'), but does not explicitly state when not to use it or name alternatives among siblings. It implies usage for deal evaluation but lacks explicit exclusions or comparisons to tools like 'classify_opportunity' or 'get_icp_fit_score'.

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