hr-reviewer

hr-reviewer is a skill for Claude Code from kyoungbinkim/give-me-job. It costs 65 tokens per session (1,623 once invoked), scanned A, original, MIT.

An HR-focused review guide for resumes, cover letters, application packages, and evidence maps, which connect claims to supporting proof.

In plain words
What is it for?
Use it to check an application before submission and get risk-focused revision advice. It is for review, not for collecting resume details, analysing a job description, or writing the final letter.
Why use it?
It helps find unsupported claims, leftover company names, and other issues that could lead to rejection or make interview answers hard to defend.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the give-me-job plugin — 8 skills shipped together

Good fit Use it to check an application before submission and get risk-focused revision advice. It is for review, not for collecting resume details, analysing a job description, or writing the final letter.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kyoungbinkim/give-me-job/hr-reviewer
Install

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.

Any agent
npx skills add kyoungbinkim/give-me-job --skill hr-reviewer
Clone the repo
git clone --depth 1 https://github.com/kyoungbinkim/give-me-job

Made for: Claude Code.

Or install give-me-job, the plugin that ships this one along with the rest of its 8 skills.

Wrote 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.

agentmods badge for hr-reviewer

README.md
[![agentmods](https://agentmods.dev/badge/skills/kyoungbinkim/give-me-job/hr-reviewer/github.svg)](https://agentmods.dev/skills/kyoungbinkim/give-me-job/hr-reviewer)
Your own site
<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.

agentmods 80×15 button for hr-reviewer

Your own site · 80×15
<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>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,623 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 3d ago against content hash bdcac5233eed, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

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.

skills/hr-reviewer/SKILL.md · 171 lines

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.md supports 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.md when 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

  1. Check whether the answer satisfies the question.
  2. 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.
  3. Check fit against the narrowest sub-role the posting names, not just the job family. Report where the evidence sits relative to that scope.
  4. Verify every strong claim against resume.md.
  5. Flag invented or unsupported achievements.
  6. Check company name, role name, sub-role name, and copy-paste residue.
  7. Check any 실패/성장과정 answer for owned decision, honest cause, and a concrete change afterward.
  8. Check readability, sentence length, repetition, and vague claims.
  9. Generate 2-3 interview follow-up questions for each key claim.
  10. Recommend concrete revisions.

Read the full file on GitHub · 171 lines

Files

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.

Changes

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.

  1. 3d ago Changed · +20 lines bdcac5233eed
  2. 12d ago First seen · 151 lines · 65 tokens per session scan A ad9c015c90d1

Subscribe to this mod's changes

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.