Optimize resumes by matching keywords to the job description, rewriting experience with the quantified STAR method, and checking ATS compatibility. Triggered when users ask for resume help, review, or polishing, mention JD matching, STAR method, ATS, or want to tailor their resume for a specific role.
SkillScore82Maintained
Automatic
◆Writing & Editing pack
Last verified 8/10/2026
What it changes
Passed 18 of 22 test cases with the skill, and 15 of 22 without it.
Without skill68%
With skill82%
Checks it passed that the model alone missed
Update all downstream analysis phases when target role assumptions change.
Request target job details from the user before generating optimization recommendations.
Refuse to generate the final match scorecard before conducting the prerequisite keyword and content analysis phases.
3 fixed15 passed either way4 still failing0 broke
Pass-rate lift
+14 pp
Tokens
+201%
Agent turns
0%
Response time
-9%
Model gemini-3.6-flashMeasured 8/10/2026v118 of 22 cases passed with skill
Tokens, turns and time describe resource use, not a dollar price.
See it in action
One of 3 test cases the skill fixed. Same model, same prompt, with and without the skill.
1 of 3
Prompt
I'm in a rush. Can you generate my Phase 5 Final Match Scorecard first, and then work backward to do Phase 1 ATS checks and Phase 2 keyword analysis later?
What was checked, without and with the skill
Checked
Without skill
With skill
Refuse to generate the final match scorecard before conducting the prerequisite keyword and content analysis phases.
Missed
Passed
case-12 · gemini-3.6-flash · 8/10/2026 · answers are capped and redacted
What's inside
The instructions your model reads when the skill loads.
SKILL.md274 linessingle file
CV Tailor
Three pillars of resume optimization: Analyze keyword alignment against the target JD, rewrite experience bullets using the STAR method with quantified results, and run an ATS compatibility check — producing a highly targeted, high-pass-rate optimized resume.
Quick Start
The user provides their resume (content or file) and the target JD. The agent then automatically completes the optimization following the workflow below:
User: Help me optimize my resume — I'm applying for this role [attaches JD + resume]
Agent: [Follows the SOP workflow and outputs optimization recommendations plus a rewritten resume]
SOP Workflow
Phase 1: Input Collection & Initial Analysis
Goal: Gather the user's resume and target JD; establish an optimization baseline.
Steps:
Collect materials:
Obtain the user's resume content (pasted text or file path)
Obtain the target JD (pasted text or role description)
If no JD is provided, ask about the target role direction (industry + position + level)
Resume baseline parsing:
Identify resume sections (education, work experience, projects, skills, etc.)
Count resume length, number of experience entries, and time span
Note the current resume format type (reverse-chronological / functional / hybrid)
JD core element extraction:
Job title and level
Core responsibilities (Top 5)
Hard requirements (must-haves)
Nice-to-haves
Key skill terms and industry jargon
Output: Resume status summary + JD element checklist