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

Annotations already declare readOnly, idempotent, non-destructive and openWorld. The description adds real behavioral detail beyond them: conflict resolution across sources, deduplication, and a field-level change log as the output artifact. It stops short of saying how conflicts are resolved (precedence rules) or that this is deterministic.

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?

One dense sentence with no filler, and the resource and transformations are front-loaded. Slightly overstuffed but every clause conveys substance.

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?

An output schema exists, so the change log needn't be explained, and annotations cover the safety profile. For a tool with a near-identical sibling, though, the description should clarify the boundary and note any input prerequisites; that routing information is the missing piece.

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?

Single parameter with 100% schema description coverage, so the schema already carries the burden. The description only restates 'from multiple ATS or HR systems' and adds no format, size, or validation guidance beyond what the schema says ('JSON or delimited text').

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+resource: 'cleans and normalizes candidate records from multiple ATS or HR systems', and names the concrete operations (conflict resolution, deduplication, standardized output). It does not differentiate from the sibling normalize_hr_data_with_lov, which an agent could easily confuse with this tool.

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?

No statement of when to use this versus normalize_hr_data_with_lov or the extraction tools (extract_resume_data, extract_job_data) that feed it. The only implied usage is 'raw records from multiple systems', with no explicit preconditions or exclusions.

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