record_fix

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

No annotations are provided, so the description must disclose behavioral traits. It indicates a write operation but lacks details on side effects, overwriting behavior, permissions, or rate limits. The added context about AI learning is helpful but insufficient for full 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?

Two sentences, front-loaded with the action and object, followed by a valuable purpose statement. No redundant or unnecessary text.

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?

The output schema is present (not shown but known), so return value explanation is not required. However, for a write operation, preconditions (e.g., project and node must exist) and behavior on duplicate records are not mentioned. Adequate but could be more complete.

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% with all parameters described. The description adds little beyond the schema, only mentioning 'component and error pattern'. Baseline is 3 due to high schema coverage; no additional value from description.

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 action 'Record a successful fix' and the resource ('component and error pattern'). It also explains the purpose of helping AI learn, which distinguishes it from sibling tools that are primarily analytical.

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 usage when a fix has been made, but does not explicitly state when not to use or mention alternatives like get_fix_suggestions. Siblings are mostly read/analysis tools, so this is moderately clear.

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