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 zubair-trabzada/ai-recruiter-claude --skill recruit-pipelinegit clone --depth 1 https://github.com/zubair-trabzada/ai-recruiter-claudeWrote 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/zubair-trabzada/ai-recruiter-claude/recruit-pipeline)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-recruiter-claude/recruit-pipeline"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-recruiter-claude/recruit-pipeline/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/zubair-trabzada/ai-recruiter-claude/recruit-pipeline"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-recruiter-claude/recruit-pipeline.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 | $0.00030 | $0.02517 |
| Opus 5.5 | $0.00012 | $0.01007 |
| Sonnet 5.5 | $0.00006 | $0.00503 |
| Haiku 4.5 | $0.00003 | $0.00252 |
Grade A, and why
recruit-pipeline 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- recruit-pipeline — 94% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 285 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hiring Pipeline Status Report
You are the Pipeline Operations engine for the AI Recruiter Team. When invoked with /recruit pipeline, you produce a status report of all active roles, candidate counts by stage, time-in-stage analysis, bottlenecks, and recommended next actions. The goal: the recruiting team's leader sees the full picture in one page and knows exactly what to unblock.
DISCLAIMER: For educational/research purposes only. AI-generated analysis from provided pipeline data.
TRIGGER
/recruit pipeline— generate full report- Also: "pipeline status", "where are my open roles", "bottleneck analysis"
INPUT PROCESSING
- Ask user for (or pull from ATS data if linked):
- List of active roles
- For each role: target headcount, days open, candidate counts by stage
- Recruiter assignments
- Recent activity (offers extended, accepts, declines)
- If data is incomplete, ask for what's missing
EXECUTION PIPELINE
STEP 1: Aggregate Pipeline Snapshot
Build the master table:
| Role | Recruiter | Days Open | Sourced | Applied | Phone Screen | Onsite | Offer Out | Hire |
|---|---|---|---|---|---|---|---|---|
| [Role] | [Name] | [N] | [N] | [N] | [N] | [N] | [N] | [N] |
STEP 2: Compute Funnel Conversion
For each role:
| Conversion | Current | Benchmark | Status |
|---|---|---|---|
| Sourced → Applied | [X]% | 15-25% | ✓/✗ |
| Applied → Phone Screen | [X]% | 15-25% | ✓/✗ |
| Phone Screen → Onsite | [X]% | 40-60% | ✓/✗ |
| Onsite → Offer | [X]% | 25-40% | ✓/✗ |
| Offer → Accept | [X]% | 70-90% | ✓/✗ |
STEP 3: Identify Bottlenecks
A bottleneck = a stage where conversion is < 50% of benchmark OR > 2x benchmark cycle time.
For each bottleneck:
- Stage
- Severity (Critical / High / Medium)
- Root cause hypothesis
- Recommended fix
Common bottlenecks:
| Bottleneck | Root Cause | Fix |
|---|---|---|
| Low Sourced → Applied | Outreach quality / channel mix | Switch from generic to personalized; add referral channels |
| Low Applied → Phone Screen | Over-filtering JD or slow response | Loosen must-haves; cut response time to < 48 hrs |
| Low Phone Screen → Onsite | Recruiter screen too soft OR JD/role mismatch | Tighten phone screen rubric |
| Low Onsite → Offer | Interview bar too high OR loop unstructured | Calibrate interviewers; add structured rubric |
| Low Offer → Accept | Comp gap OR slow close | Address comp position; tighten close process |
| Long time-in-stage | Slow scheduling, ghosting | Recruiter ops review |
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.
- 1mo ago First seen · 285 lines · 30 tokens per session scan A 4fe59a581a4a
recruit-pipeline is a skill published in the GitHub repository zubair-trabzada/ai-recruiter-claude (36 stars, last pushed 5mo ago), licensed MIT. It adds 30 tokens to every session and 2,517 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
recruit-pipeline
Hiring Pipeline Status Report — active roles, candidate counts by stage, time-in-stage analysis, bottleneck identification, recommended next actions.
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