ai-job-application-optimizer

ai-job-application-optimizer Job Application Material Optimization Assistant

Quick Start

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Overview

The Job Application Material Optimization Assistant is used to answer "Is my resume a good match for the position?", HR documents, performance feedback, and job application materials. It is suitable for human resources, managers, operations, and software to call after clarifying business goals, content materials, or analysis targets. It combines inputs such as the position, performance, or job application materials, pasted job description, resume, performance materials, HR communication draft, evaluation criteria, or feedback goals, organizes key context, and outputs match gaps, resume optimization suggestions, and interview preparation checklists, making it easy to continue execution, review, or delivery. Capability positioning supplement: job application material optimization is a clear document review and revision scenario.

When to Use

Applicable Scenarios

• Users raise questions such as "Is my resume a good match for the position?" and need to quickly break down the goal, determine priorities, and form executable results
• Human resources, managers, operations, and software need to generate match gaps, resume optimization suggestions, and interview preparation checklists around the Job Application Material Optimization Assistant
• Users have already prepared the processing goal (explain the match analysis, performance feedback, expression optimization, interview preparation, or risk check to be completed.), relevant roles (explain the candidate, employee, manager, HRBP, interviewer, or communication target.), and position or material links (fill in publicly accessible position, company, policy, or reference material links.), and hope to organize them into executable analysis or optimization results
• Users need to turn materials related to the Job Application Material Optimization Assistant into clear conclusions, priorities, and next steps

How to Call

Call the AI Skills API directly through the exported Python runner:

Command Examples

Basic Call

python3 scripts/run.py --params '{}'

Call with Common Parameters

python3 scripts/run.py --params '{"goal":"处理目标"}'

Parameter Description

Parameter	Type	Required	Default	Description
goal	string	No	-	Explain the match analysis, performance feedback, expression optimization, interview preparation, or risk check to be completed
audience	string	No	-	Explain the candidate, employee, manager, HRBP, interviewer, or communication target
materialUrl	string	No	-	Fill in publicly accessible position, company, policy, or reference material links; a complete accessible URL must be provided
materialFile	string	No	-	Upload resumes, job descriptions, performance records, HR policies, interview materials, or communication drafts
materialText	string	No	-	Paste job descriptions, resumes, performance materials, HR communication drafts, evaluation criteria, or feedback goals
brandRequirements	string	No	-	Supplement factual evidence, sensitive information handling, tone requirements, non-committable content, legal boundaries, or key points for manual review

See the complete machine-readable parameter structure at references/form-schema.json。

Parameter Value Reference

The current skill has no categorical parameters that require additional table lookup.

Supported Input Formats

The current skill directly accepts JSON parameters; if the parameters contain link fields, please provide complete, accessible URLs.

Example Request

The example parameters below can be passed directly to scripts/run.py, and the runner will send them to the AI Skills API.

python3 scripts/run.py --params '{"goal":"处理目标"}'

Equivalent --params JSON：

{
  "goal": "处理目标"
}

Example Response

{
  "success": true,
  "data": {
    "message": "示例结果请以技能真实返回结构为准。"
  },
  "meta": {
    "executionTime": 842,
    "cached": false
  }
}

Deliverables

• Matching gaps, resume optimization suggestions, interview preparation checklist: core results organized around the user's goals that can be directly read, reviewed, or delivered.
• Interpretation of input materials: combine the processing goal (explain the matching analysis, performance feedback, expression optimization, interview preparation, or risk check to be completed.), relevant roles (explain the candidate, employee, manager, HRBP, interviewer, or communication target.), and job or material links (fill in publicly accessible job, company, policy, or reference links.) to extract key context and the basis for judgment.
• Next steps: provide priorities, execution suggestions, or a content framework that can be further processed.

Suggestions for Using the Results

• First determine whether the output answers the user's core question about the "Job Application Material Optimization Assistant".
• Then check whether the results cover matching gaps, resume optimization suggestions, and the interview preparation checklist, and whether clear next steps are provided.
• If there is little input material, it is recommended to have the user supplement the goal, audience, constraints, or original materials before running.

Preparation Before Running

• AISKILLS_BASE_URL: default https://ai-skills.ai
• AISKILLS_API_KEY: required, used for authenticated calls
• AISKILLS_TENANT_ID: default default