Get Finding Remediation

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

Even though readOnlyHint=true, the description importantly discloses that this read can spend AI budget, which annotations alone would not convey. It also explains the fallback to static guidance text and the 'source' field, giving the agent a clear mental model of non-obvious 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 compact but information-dense: every sentence contributes either to purpose, cost behavior, fallback semantics, or a precondition. It is front-loaded with the core action and output format, making it easy for an agent to parse quickly.

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?

For a single-parameter read with no output schema, the description covers what the tool returns, the format, the source distinction, the budget implication, and the required context. Nothing essential for an agent to decide whether and how to invoke this tool is missing.

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% and the single parameter findingId is already well documented as the Public Id from get_security_findings. The description adds little parameter-specific meaning beyond confirming the tool operates on a single finding, so the baseline score of 3 is appropriate.

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 names a specific verb and resource ('Get remediation advice for a single finding') and adds the output format (GitHub-flavored markdown). It distinguishes this tool from list-style reads like get_security_findings by emphasizing it targets one finding and can produce an AI-generated suggestion.

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 gives clear context for when the tool is appropriate, including the AI Assist budget condition and fallback behavior. It also explains why it is separate from other reads ('Unlike the other reads this one can spend AI budget') and notes the prerequisite of project context, though it does not name specific alternative tools.

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