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

With no annotations provided, the description carries full responsibility for behavioral transparency. It explains the scoring mechanism (0-100 based on stars, age, plausibility, payment-bot presence), the output sorting, and even the operator context (Krab Bot, free preview tier). This goes beyond a typical description, though it does not detail possible side effects or rate limits.

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 three sentences, each earning its place: the first states the core purpose, the second explains the scoring and output, the third gives usage guidance and operational context. It is front-loaded with the key action and contains no fluff or repetition.

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 parameters, no annotations, and no output schema, the description is largely complete. It covers what the tool does, how it works, when to use it, and even operator limitations. The only minor gap is not specifying the exact shape of returned results (e.g., fields included), but 'top results sorted by that score' gives a reasonable expectation.

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?

The tool has zero parameters, so the baseline is 4. There is no parameter schema to supplement, and the description appropriately focuses on the tool's behavior rather than parameter specifics. The scoring criteria mentioned are not parameters but internal logic, so no additional meaning is needed.

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 a specific verb and resource: 'Find open-source bounties that are actually likely to pay out.' It also distinguishes from sibling tools (check_package_risk, check_stack_eol) by focusing on bounty discovery rather than risk assessment, and adds a unique value proposition with the credibility scoring.

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 explicit usage context: 'Use when looking for paid open-source work worth attempting.' This clearly indicates when to use the tool, though it does not mention alternatives or when not to use it. Since the sibling tools have clearly different purposes, the context is sufficient.

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