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 jd-analyzergit 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/jd-analyzer)<a href="https://agentmods.dev/skills/kyoungbinkim/give-me-job/jd-analyzer"><img src="https://agentmods.dev/badge/skills/kyoungbinkim/give-me-job/jd-analyzer/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/jd-analyzer"><img src="https://agentmods.dev/badge/skills/kyoungbinkim/give-me-job/jd-analyzer.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 | $0.00120 | $0.00862 |
| Opus 5 | $0.00060 | $0.00431 |
| Sonnet 5 | $0.00024 | $0.00172 |
| Haiku 4.5 | $0.00012 | $0.00086 |
Grade A, and why
jd-analyzer 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JD Analyzer
Use this skill to convert a hiring post into practical selection criteria.
Trigger
Use this skill when the user provides a JD URL, pasted hiring post, normalized job record, or hiring notes that need Korean-market role analysis.
Do Not Trigger
Do not use this skill to draft cover letters, invent missing JD requirements, or analyze company culture pages that are not part of the hiring post.
Autonomy Level
DoF: MEDIUM
Separate deterministic parsing from conservative inference. Label every inferred evaluation criterion as inferred.
Permitted inferences:
- Hidden evaluation criteria that follow directly from explicit duties, tools, seniority, or hiring process language.
- Likely resume evidence categories needed to answer the JD.
Prohibited inferences:
- Do not add requirements absent from the JD or role context.
- Do not treat inferred criteria as explicit facts.
Input Contract
Required context:
- JD URL, JD text, normalized job record, or hiring-post notes.
Optional context:
resume.mdfor gap mapping.- Cover letter questions and length limits.
Required parameters:
source: URL, text, normalized job record, orunknown.
Outputs produced:
applications/<company-role>/jd-analysis.md
Workflow
- Accept a JD URL, pasted JD text, or mixed notes.
- Parse deterministic facts only:
- source URL or source type
- accessed date when browsing or checking a live posting
- company
- role
- seniority
- deadline
- required documents
- cover letter questions and length limits
- Analyze explicit requirements and inferred evaluation criteria in separate sections. Read the JD alone first; fix mandatory, core, and preferred importance and source excerpts before reading the resume. Do not adjust importance to suit the candidate.
- Gap map the JD against
resume.mdwhen resume evidence is available. Link each requirement to stable evidence IDs and original locations; classify it as met, partially met, unmet, or needs confirmation. - Identify the likely evidence needed from
resume.md. - Mark gaps where the resume evidence appears weak or missing.
- Keep inference conservative. Label inferred criteria as inferred.
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 · +9 lines 93614738b864
- 12d ago First seen · 101 lines · 120 tokens per session scan A 23f7e4a895ad
jd-analyzer is a skill published in the GitHub repository kyoungbinkim/give-me-job (5 stars, last pushed 2d ago), licensed MIT. It adds 120 tokens to every session and 862 once invoked, about $0.0006 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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