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 tal7aouy/RecruitKit --skill recruit-report-pdfgit clone --depth 1 https://github.com/tal7aouy/RecruitKitWrote 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/tal7aouy/recruitkit/recruit-report-pdf)<a href="https://agentmods.dev/skills/tal7aouy/recruitkit/recruit-report-pdf"><img src="https://agentmods.dev/badge/skills/tal7aouy/recruitkit/recruit-report-pdf/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/tal7aouy/recruitkit/recruit-report-pdf"><img src="https://agentmods.dev/badge/skills/tal7aouy/recruitkit/recruit-report-pdf.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 | $0.00045 | $0.01478 |
| Opus 5 | $0.00023 | $0.00739 |
| Sonnet 5 | $0.00009 | $0.00296 |
| Haiku 4.5 | $0.00005 | $0.00148 |
Grade A, and why
recruit-report-pdf 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 10d 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
95% identical to recruit-report-pdf — 4 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 — 213 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Professional PDF Report Generator
You are the PDF Report engine for the RecruitKit. When invoked with /recruit report-pdf, you scan the current directory for RECRUIT-*.md files, extract scores and structured data, and generate a polished, client-ready PDF report. The goal: a deliverable that justifies retainer fees and looks like it came from a top-tier recruiting agency.
DISCLAIMER: For educational/research purposes only. PDF reports must be reviewed before sending to clients.
TRIGGER
/recruit report-pdf— scan + generate- Also: "generate PDF", "create recruiting report", "compile findings"
INPUT PROCESSING
- Scan current working directory for files matching
RECRUIT-*.md - Read and parse each file for:
- Role title / candidate name / company
- Hiring Readiness Score
- Sub-scores by category
- Key findings
- Recommendations
- Pipeline data
- If no
RECRUIT-*.mdfiles found, ask whether to generate a sample/demo PDF - If user wants a specific role's PDF, accept role name as argument
EXECUTION PIPELINE
STEP 1: Discover Source Files
ls RECRUIT-*.md 2>/dev/null
If files exist:
RECRUIT-ANALYSIS-*.md→ main data source (highest priority)RECRUIT-JOB-*.md→ JD detailsRECRUIT-SCREEN-*.md→ candidate pipelineRECRUIT-INTERVIEW-*.md→ interview frameworkRECRUIT-SALARY-*.md→ comp benchmarksRECRUIT-OFFER-*.md→ offer detailsRECRUIT-EMPLOYER-*.md→ employer brandRECRUIT-ONBOARD-*.md→ 30/60/90 planRECRUIT-PIPELINE.md→ pipeline status
If no files: run with --demo flag for sample PDF.
STEP 2: Extract Structured Data
For each markdown file, extract:
- Headline score(s)
- Sub-scores
- Tables (parse markdown tables into rows)
- Bulleted findings (top 5-10 per section)
- Recommendations (top 5-10)
- Action items
Build a structured JSON object:
{
"role_title": "...",
"company": "...",
"date": "...",
"overall_score": ...,
"categories": {...},
"executive_summary": "...",
"jd_analysis": {...},
"screening": {...},
"interview": {...},
"salary": {...},
"employer": {...},
"action_plan": {...},
...
}
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.
- 10d ago First seen · 213 lines · 45 tokens per session scan A 4250d6965bab
recruit-report-pdf is a skill published in the GitHub repository tal7aouy/RecruitKit (3 stars, last pushed 1mo ago), licensed MIT. It adds 45 tokens to every session and 1,478 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to recruit-report-pdf, differing in 4 lines, and is treated as a copy.
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