parse_resume

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

Annotations indicate readOnlyHint=true, matching the non-destructive parse operation. The description adds behavioral context beyond annotations: 'algorithmic pre-analysis' and specific extraction capabilities. No contradictions with annotations.

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 sentence, front-loaded with the main action and supported formats. Every word is meaningful; no wasted 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?

Given 2 parameters and no output schema, the description covers input options and output features reasonably well. However, it does not specify the return format (e.g., JSON structure). Slightly incomplete for an agent.

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%, so baseline is 3. The description adds that content can be base64 or URL and lists file types, but this information is already present in the schema. No additional parameter semantics beyond 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 clearly states the tool's action ('Parse a resume file') and resources (PDF, DOCX, TXT, MD, or URL) and lists specific outputs (keyword extraction, metrics detection, section identification, experience estimation). It effectively distinguishes from siblings like batch_parse_resumes or extract_keywords.

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 for initial resume parsing and extraction of pre-analysis features, but does not explicitly state when to use versus alternatives (e.g., extract_keywords, extract_skills_structured). No when-not or context exclusions are provided.

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