Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add serejaris/kimi-skills --skill cv-tailorgit clone --depth 1 https://github.com/serejaris/kimi-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/serejaris/kimi-skills/cv-tailor)<a href="https://agentmods.dev/skills/serejaris/kimi-skills/cv-tailor"><img src="https://agentmods.dev/badge/skills/serejaris/kimi-skills/cv-tailor/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/serejaris/kimi-skills/cv-tailor"><img src="https://agentmods.dev/badge/skills/serejaris/kimi-skills/cv-tailor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.02816 |
| Opus 5 | $0.00030 | $0.01408 |
| Sonnet 5 | $0.00012 | $0.00563 |
| Haiku 4.5 | $0.00006 | $0.00282 |
Grade A, and why
cv-tailor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to cv-tailor — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 281 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
Phase 2: JD Keyword Match Analysis
Goal: Systematically compare keyword coverage between the resume and JD to identify match gaps.
Steps:
-
Categorized keyword extraction: Extract three categories of keywords from the JD:
Category Description Examples Hard skill keywords Tech stack, tools, methodologies Python, SQL, A/B testing, Scrum Soft skill keywords Competency requirements Cross-team collaboration, data-driven, project management Industry/domain keywords Domain-specific terminology DAU, conversion rate, user growth, SaaS
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 281 lines · 61 tokens per session scan A e652967572a2
cv-tailor is a skill published in the GitHub repository serejaris/kimi-skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 61 tokens to every session and 2,816 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to cv-tailor, differing in 0 lines, and is treated as a copy.
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