find_cascade_risk

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

No annotations are provided, so the description carries the full disclosure burden. It transparently explains the algorithm, including the formula for saturation_rps, and lists the return fields with meaning. It does not mention permissions, side effects, or data sources, but given the analytical nature, these omissions are minor. The description is largely adequate for understanding behavior.

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 well-structured with a clear first sentence and subsequent details including algorithm, formula, args, and returns. It is concise enough (roughly 100 words) without redundant information, but the inclusion of the formula could be simplified if the return fields already imply the computation. Still, it earns its place.

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 simplicity (single parameter, no annotations, output schema present), the description is complete. It explains the tool's purpose, algorithm, parameter meaning, and return structure including risk levels. No major gaps remain: an agent can confidently use this tool based solely on the description.

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%, but the description compensates fully. It defines the sole parameter repo_name as 'The logical name of the upstream repository to analyse,' adding semantic context beyond the schema's type and title. The Arg section in the description provides a clear explanation, satisfying the parameter semantics needs.

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 starts with a clear statement of what the tool does: 'Find upstream endpoints at cascade risk from saturated downstream services.' It then details the algorithm, including walking CALLS_REST edges and comparing saturation_rps to current_rps, which distinguishes it from sibling tools like blast_radius or find_callees that have different focuses.

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 explains the specific condition under which a risk is flagged (saturation_rps < current_rps), providing implicit guidance on when to use the tool. However, it does not explicitly contrast with alternatives (e.g., when to use find_callees vs. this tool) or state prerequisites like having perf data ingested, limiting the guidance value.

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