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 kyoungbinkim/give-me-job --skill hr-reviewergit clone --depth 1 https://github.com/kyoungbinkim/give-me-jobWrote 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/kyoungbinkim/give-me-job/hr-reviewer)<a href="https://agentmods.dev/skills/kyoungbinkim/give-me-job/hr-reviewer"><img src="https://agentmods.dev/badge/skills/kyoungbinkim/give-me-job/hr-reviewer/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/kyoungbinkim/give-me-job/hr-reviewer"><img src="https://agentmods.dev/badge/skills/kyoungbinkim/give-me-job/hr-reviewer.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 | $0.00065 | $0.01623 |
| Opus 5 | $0.00032 | $0.00812 |
| Sonnet 5 | $0.00013 | $0.00325 |
| Haiku 4.5 | $0.00006 | $0.00162 |
Grade A, and why
hr-reviewer 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 3d 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.
How it starts
The opening of the file, as written. The whole thing — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HR Reviewer
Review as a strict but practical HR screener. Prioritize risks that can cause rejection or weak interview defense.
Trigger
Use this skill after cover-letter-draft.md and evidence-map.md exist and before cover-letter-final.md is created.
Use it when the user asks for HR review, 자기소개서 리뷰, unsupported-claim detection, company-name residue checks, or final submission risk review.
Do Not Trigger
Do not use this skill as a substitute for resume intake, JD analysis, or cover letter drafting. Do not create final text when blockers remain.
Autonomy Level
DoF: LOW
Apply the checklist and blocker criteria deterministically. Do not soften blocker findings to keep the workflow moving.
Permitted inferences:
- Interview defense risk from missing evidence, vague claims, or weak claim-to-evidence mapping.
- Severity level from the blocker and warning criteria below.
Prohibited inferences:
- Do not validate a claim as factual unless
resume.mdsupports it. - Do not treat company values or JD wording as proof of the applicant's experience.
Input Contract
Required context:
- Draft cover letter or resume text.
resume.md.- JD analysis or job posting.
applications/<company-role>/evidence-map.mdwhen reviewing a cover letter package.
Optional context:
- Company values analysis.
- Length limit and counting rule.
Required parameters:
company: target company name.role: target role title.
Outputs produced:
applications/<company-role>/hr-review.md
Inputs
- draft cover letter or resume text
resume.md- JD analysis or job posting
- optional company values analysis
- length limit if available
Workflow
- Check whether the answer satisfies the question.
- Check JD fit and career-level fit. Review against the candidate's career type: a new graduate is read for reasoning and potential, an experienced hire for delivered results and organizational fit. Applying the wrong lens produces the wrong findings.
- Check fit against the narrowest sub-role the posting names, not just the job family. Report where the evidence sits relative to that scope.
- Verify every strong claim against
resume.md. - Flag invented or unsupported achievements.
- Check company name, role name, sub-role name, and copy-paste residue.
- Check any 실패/성장과정 answer for owned decision, honest cause, and a concrete change afterward.
- Check readability, sentence length, repetition, and vague claims.
- Generate 2-3 interview follow-up questions for each key claim.
- Recommend concrete revisions.
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.
- 3d ago Changed · +20 lines bdcac5233eed
- 12d ago First seen · 151 lines · 65 tokens per session scan A ad9c015c90d1
hr-reviewer is a skill published in the GitHub repository kyoungbinkim/give-me-job (5 stars, last pushed 3d ago), licensed MIT. It adds 65 tokens to every session and 1,623 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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