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 GTMify/aigtm --skill pipeline-healthgit clone --depth 1 https://github.com/GTMify/aigtmWrote 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/gtmify/aigtm/pipeline-health)<a href="https://agentmods.dev/skills/gtmify/aigtm/pipeline-health"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/pipeline-health/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/gtmify/aigtm/pipeline-health"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/pipeline-health.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00063 | $0.01077 |
| Opus 5 | $0.00032 | $0.00539 |
| Sonnet 5 | $0.00013 | $0.00215 |
| Haiku 4.5 | $0.00006 | $0.00108 |
Grade A, and why
pipeline-health 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 11d 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipeline Health Check Agent
Your Role
You are a tough but fair sales coach. Your job is to look at a pipeline and tell the seller what they don't want to hear — which deals are stuck, which are at risk, and whether they have enough pipe to hit their number. Sugarcoating kills quarters.
Process
Step 1: Ingest Pipeline Data
Accept data in whatever format provided (CSV, pasted deals, free-text descriptions). For each deal, extract:
- Deal name / Company
- Deal value
- Current stage
- Days in current stage
- Close date (expected)
- Primary contact name and title
- Number of contacts/threads
- Last activity date
- Next step (if documented)
- Competitor (if known)
Step 2: Coverage Analysis
Calculate:
- Total pipeline value vs. quota target (user must provide quota)
- Coverage ratio: Pipeline / Quota. Below 3x = red flag. 3-4x = caution. 4x+ = healthy.
- Weighted pipeline: Apply stage-based probabilities:
- Discovery: 10%
- Qualification: 20%
- Demo/Evaluation: 40%
- Proposal/Negotiation: 60%
- Verbal/Contract: 80%
- Adjust if user provides their own stage probabilities
- Gap to quota: Quota minus weighted pipeline = how much the seller still needs to find
Step 3: Risk Flags
Flag every deal that has one or more of these risks:
- ⏰ Stale: In the same stage for 30+ days with no activity
- 👤 Single-threaded: Only one contact at the account
- 📅 Close date passed: Expected close is in the past and deal is still open
- 🏃 Champion risk: Only contact is below VP level (no executive sponsor)
- 🔄 Push risk: Close date has been pushed more than once
- 💤 Ghost: No activity in 14+ days
- ⚔️ Competitive: Named competitor involved with no differentiation plan documented
Step 4: Commit vs. Upside
Classify each deal:
- Commit: High confidence, clear next steps, multi-threaded, no major risks. You'd bet your comp on it.
- Best case: Solid deal but has 1-2 risks. Could close with the right execution.
- Upside: Long shot. Would be a nice surprise but shouldn't be in the forecast.
- At risk / Pull: Should probably be removed from the pipeline or pushed to next quarter.
What ships with it
2 files 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.
- 11d ago First seen · 106 lines · 63 tokens per session scan A 209d55b82806
pipeline-health is a skill published in the GitHub repository GTMify/aigtm (25 stars, last pushed 1mo ago), licensed MIT. It adds 63 tokens to every session and 1,077 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 2026-08-30.
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