repair_dataset

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

With no annotations, the description carries the full burden and does well: it discloses that the input is never modified, that output is a copy plus a changelog, and that unsafe out_dir values are refused. It leaves out what happens on refusal (error vs. no-op) and nothing about the result payload.

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 dense sentences, front-loaded with the write target and followed by the safety constraints. No filler, and every clause carries a constraint the schema does not express.

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?

Covers the write-safety profile and output location, which is the critical part for a mutation tool with no annotations. But with no output schema and undocumented config_path, the description does not say how a repair is configured or what the caller gets back.

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 0%, so the description must compensate. It gives strong semantics for out_dir (new, non-input, empty) and implies path is the input dataset via 'Never modifies the input', but config_path is never mentioned at all, leaving one of three parameters opaque.

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?

States a specific verb and resource: writes a repaired COPY of the dataset plus changelog into a NEW folder. That is far more specific than the read-only siblings (inspect_dataset, find_issues, compare_runs), though it never explicitly contrasts itself with them or explains what 'repaired' means.

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?

Gives clear guardrails on when the call is valid: out_dir must be a new folder, must not equal the input's folder, and must not already contain files. It does not name alternatives or say what workflow precedes a repair (e.g. after find_issues/explain_issue).

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