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get_cv_tailoring_prompt

Aligns CV bullets to medical writing job requirements, incorporates keywords, strengthens achievement language, and identifies gaps for ATS optimization.

Instructions

[PRO] Tailor a CV/resume to a medical writing job posting for ATS alignment. Aligns bullets to requirements, incorporates keywords, strengthens achievement language, and identifies gaps.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_postingYes
current_resume_bulletsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The actual tool handler function for 'get_cv_tailoring_prompt'. It takes job_posting and current_resume_bullets as input and returns a tailored prompt string for ATS-aligned CV/resume tailoring to a medical writing job posting.
    def get_cv_tailoring_prompt(job_posting: str, current_resume_bullets: str) -> str:
        """
        [PRO] Tailor a CV/resume to a medical writing job posting for ATS alignment.
        Aligns bullets to requirements, incorporates keywords, strengthens achievement language,
        and identifies gaps.
        """
        return f"""Review my resume and the following job posting and suggest specific edits to:
    1. Align my bullet points with the job's key requirements
    2. Incorporate relevant keywords from the posting (for ATS)
    3. Strengthen achievement-based language (quantify where possible)
    4. Identify gaps between my experience and the role requirements
    
    Job posting:
    {job_posting}
    
    My current resume / key bullet points:
    {current_resume_bullets}
    
    Pro tip: ATS systems scan for exact keyword matches — don't paraphrase the job requirements, mirror them."""
  • The input schema is defined via the function signature: job_posting (str) and current_resume_bullets (str) are required parameters. The return type is str.
    def get_cv_tailoring_prompt(job_posting: str, current_resume_bullets: str) -> str:
        """
        [PRO] Tailor a CV/resume to a medical writing job posting for ATS alignment.
        Aligns bullets to requirements, incorporates keywords, strengthens achievement language,
        and identifies gaps.
        """
  • server.py:1001-1001 (registration)
    Tool is registered in the 'list_all_tools' directory listing under pro_tools with description 'Tailor CV to medical writing job posting'.
    ("get_cv_tailoring_prompt", "Tailor CV to medical writing job posting"),
Behavior3/5

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

With no annotations, the description carries the full burden of behavioral transparency. It lists actions: 'Aligns bullets to requirements, incorporates keywords, strengthens achievement language, and identifies gaps.' This provides useful behavioral detail but does not disclose side effects, permissions, or whether the tool is read-only. The stated behaviors are sufficient but not exhaustive.

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

Conciseness4/5

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

The description is concise: a single sentence with a bullet list. It front-loads the purpose and then enumerates specific actions. Every part adds value, though the bullet list could be integrated more smoothly. No unnecessary 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 tool has an output schema (not shown), the description does not need to explain return values. It covers the main transformation actions succinctly. The description is likely sufficient for an AI agent to invoke the tool correctly, though it could add parameter-specific details.

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 0%, so the description must compensate. It mentions 'bullets' and 'requirements', which map to 'current_resume_bullets' and 'job_posting' respectively. However, it does not explicitly define each parameter, their formats, or constraints. The description adds partial meaning but leaves room for ambiguity.

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 tool's purpose: 'Tailor a CV/resume to a medical writing job posting for ATS alignment.' The verb is specific ('Tailor'), the resource is identified ('CV/resume'), and the domain is constrained ('medical writing job posting'). This distinguishes it from sibling tools that focus on other types of prompts.

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

Usage Guidelines2/5

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

The description does not provide any guidance on when to use this tool versus alternatives. There are many sibling prompt tools, but no mention of conditions, prerequisites, or scenarios where this tool is preferred. The '[PRO]' prefix hints at a professional version but is not explained.

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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