Fix Encoding

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

Annotations declare idempotentHint=true, destructiveHint=false, and readOnlyHint=false. The description adds context that it repairs 27+ patterns for specific languages, which goes beyond annotations. No contradictions.

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 extremely concise: one sentence for purpose, a compact list of arguments, and a one-liner about patterns. Every word adds value; no 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?

Given the low complexity (3 parameters, no output schema), the description is adequate: it explains the tool's purpose, parameters, and supported patterns. Could mention that it modifies files in-place (destructiveHint=false but still writes), but completeness is high for the scope.

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 100%, so the schema already documents parameters. The description briefly mentions the three params (path, dry_run, create_backup) but adds no extra context beyond what is in the schema.

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 'Repairs encoding errors (Mojibake, double UTF-8)' which is a specific verb-resource pair. It clearly distinguishes from siblings like cc_fix_json or cc_fix_umlauts by focusing on encoding issues.

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 implicitly suggests use for encoding errors but gives no explicit guidance on when to use vs alternatives like cc_fix_umlauts or cc_scan_emoji. No when-not or exclusion criteria provided.

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