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otp_parse_resume

Parses raw resume text into a structured OTP extraction template with annotations, field confidence, and identified information gaps.

Instructions

Produce a structured OTP extraction template from raw resume text. Returns a document skeleton with EXTRACT* annotations, a fieldConfidence list (high/medium/low per field), and a gaps list of information not typically on resumes. The calling agent should fill in the skeleton using its reasoning over the text, then call otp_validate_profile to verify the result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesRaw resume text (plain text, markdown, or extracted PDF text).
Behavior3/5

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

No annotations are provided, so the description carries full burden. It describes the output (skeleton with annotations, confidence list, gaps list) but does not explicitly state whether the tool is read-only or has side effects. For a parsing tool, this is acceptable but could be more transparent about non-destructiveness.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is one paragraph of three sentences, front-loaded with the main purpose. Every sentence is necessary and contributes useful information. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the single parameter and no output schema, the description covers the output structure (three parts) and the follow-up step. It could mention potential constraints like text length limits, but overall it is complete for an agent to use correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single parameter 'text', which already describes it as 'Raw resume text (plain text, markdown, or extracted PDF text)'. The tool description adds context about processing steps but does not add new semantics for the parameter beyond alignment with the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Produce' and the resource 'structured OTP extraction template from raw resume text'. It distinguishes from siblings by specifying the output elements (document skeleton, fieldConfidence list, gaps list) and mentions the follow-up tool otp_validate_profile, which is listed as a sibling but for a different purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit context: the calling agent should fill in the skeleton after using this tool, then call otp_validate_profile. It does not explicitly state when not to use this tool, but the process is clear and no alternative tools are suggested.

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

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