suggest_fixes

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

No annotations are present, so the description carries the full burden of behavioral disclosure. It discloses the core behavior—analyzing failures and returning remediation hints/prompt snippets—but leaves ambiguous how 'recent' is defined, whether it reads from persisted state, and whether any side effects occur. This is partial transparency.

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 a single efficient sentence that front-loads the primary action and the expected output. Every word earns its place; there is no redundancy or filler.

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 simple one-optional-param tool, the description covers the main action and return value. However, with no output schema and no annotations, it doesn't clarify what 'recent' means, whether prior checks are required, or the structure of the returned remediation hints—leaving some ambiguity for an agent selecting or invoking the tool.

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 single optional parameter `project_path` is fully described in the schema as 'Optional target project directory path.' With 100% schema coverage, the description doesn't need to add parameter details. The baseline 3 applies because no additional semantics beyond the schema are provided.

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 states a specific verb ('Analyze') and resource ('recent validation failures'), and explicitly describes the output ('structured remediation hints and prompt snippets'). This clearly distinguishes it from sibling tools like run_checks or get_check_status, which focus on execution or status rather than remediation.

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 implies a clear usage context: use when there are recent validation failures. This gives the agent enough situational signal. However, it does not explicitly name alternatives or state when not to use it, so it stops short of full usage guidance.

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