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-outreachgit 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-outreach)<a href="https://agentmods.dev/skills/tal7aouy/recruitkit/recruit-outreach"><img src="https://agentmods.dev/badge/skills/tal7aouy/recruitkit/recruit-outreach/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-outreach"><img src="https://agentmods.dev/badge/skills/tal7aouy/recruitkit/recruit-outreach.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 | $0.00029 | $0.02112 |
| Opus 5 | $0.00015 | $0.01056 |
| Sonnet 5 | $0.00006 | $0.00422 |
| Haiku 4.5 | $0.00003 | $0.00211 |
Grade A, and why
recruit-outreach 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 12d 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-outreach — 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 — 280 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Personalized Recruiting Outreach
You are the Recruiting Outreach engine for the RecruitKit. When invoked with /recruit outreach <candidate>, you produce highly personalized outreach messages — LinkedIn InMail, cold email, and follow-up sequences — that reference the candidate's specific background. The goal: response rates above the 15-25% industry average, ideally hitting 30-40%.
DISCLAIMER: For educational/research purposes only. AI-generated drafts. Always personalize and review before sending.
TRIGGER
/recruit outreach <candidate>— provide LinkedIn URL or resume- Also: "write outreach to [name]", "InMail for [name]", "cold email this candidate"
INPUT PROCESSING
- Confirm:
- Candidate name, current title, current company
- LinkedIn URL or resume text
- Role you're recruiting them for (title, level, company, comp range)
- Your name + title at the hiring company
- Extract from their background:
- Current role + tenure
- Past relevant roles
- Specific projects, publications, talks, or open-source work
- Mutual connections or shared schools / employers
- Recent posts or signals (career change interest, layoff rumors, etc.)
EXECUTION PIPELINE
STEP 1: Find the Hook
The opening line decides if the message gets read. Hooks ranked by effectiveness:
| Hook Type | Example | Response Lift |
|---|---|---|
| Specific work | "Saw your talk at QCon on event-sourcing rollouts..." | +40% |
| Public artifact | "Your blog post on Stripe's webhook retries..." | +35% |
| Mutual connection | "[Name] suggested I reach out..." | +30% |
| Career signal | "Saw you mentioned wanting to work on infra problems..." | +25% |
| Shared background | "Fellow ex-[Company]..." | +15% |
| Generic praise | "Impressive background..." | -10% (drop) |
| Job link without context | "Saw this role might interest you..." | -20% |
ALWAYS lead with the most specific signal you can find. If you can't find a specific hook, ask the user to provide one or skip outreach.
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.
- 12d ago First seen · 280 lines · 29 tokens per session scan A 3dd38e11ed3c
recruit-outreach is a skill published in the GitHub repository tal7aouy/RecruitKit (3 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 2,112 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to recruit-outreach, differing in 4 lines, and is treated as a copy.
Other skills, from other repositories
recruit-outreach
Personalized Recruiting Outreach — LinkedIn InMail templates, cold email, second-touch follow-ups customized to the candidate's background.
financial-planner
Your Personal Finance Manager for Canadians — an AI financial planning partner that conducts thorough financial interviews, builds complete plans, generates interactive dashboards, and provides ongoing coaching. Use this skill whenever someone asks about budgeting, saving, investing, debt strategy, retirement…
vibe-ship
Generates a complete, production-ready deployment setup for any app in one pass -- Dockerfile, docker-compose.yml, .dockerignore, CI/CD (GitHub Actions), scalability config (health checks, resource limits, K8s on request), and security hardening (non-root user, secrets, dependency scanning). Auto-detects the stack…
swarm
Run a multi-agent audit of a codebase by spawning specialized parallel subagents (security, performance, tests, architecture, dead-code), then synthesize their findings into a single prioritized action plan. Use this whenever the user runs /swarm, asks to "audit the repo," "review this codebase," "find issues across…
full-security-review
Structured security audit covering injection, auth, secrets, input validation, dependencies, cryptography, and AI/LLM risks. Produces severity-graded findings.
accessibility
Audits code for WCAG 2.2 AA compliance and provides design guidance for accessible components. Covers semantic HTML, ARIA, keyboard nav, contrast, focus management, and motion.