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 jbalbu01/sales-enablement-plugin --skill pipeline-intelligencegit clone --depth 1 https://github.com/jbalbu01/sales-enablement-pluginWrote 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/jbalbu01/sales-enablement-plugin/pipeline-intelligence)<a href="https://agentmods.dev/skills/jbalbu01/sales-enablement-plugin/pipeline-intelligence"><img src="https://agentmods.dev/badge/skills/jbalbu01/sales-enablement-plugin/pipeline-intelligence.svg" alt="Measured on agentmods" 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 | $0.00118 | $0.02947 |
| Opus 5 | $0.00059 | $0.01473 |
| Sonnet 5 | $0.00024 | $0.00589 |
| Haiku 4.5 | $0.00012 | $0.00295 |
Grade A, and why
pipeline-intelligence 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 8d 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 — 271 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipeline Intelligence
Go beyond pipeline reporting into pipeline understanding. Traditional dashboards show you what's happening — this skill tells you why and what to do about it. It learns from your deal outcomes over time, so insights get sharper with each quarter.
What Makes This Different from Reports
A CRM report says: "Your win rate is 22%." Pipeline Intelligence says: "Your win rate is 22%, down from 28% last quarter. The drop is concentrated in deals over $100K where you're competing against CompX. Reps who do multi-threaded discovery have a 35% win rate in the same segment. Here are 3 deals in your current pipeline that match the loss pattern — take action this week."
How It Works
┌─────────────────────────────────────────────────────────────────┐
│ PIPELINE INTELLIGENCE │
├─────────────────────────────────────────────────────────────────┤
│ ANALYSES │
│ 1. Pipeline Health — Overall assessment with risk flags │
│ 2. Conversion Analysis — Where and why deals stall/drop │
│ 3. Velocity Analysis — What speeds up or slows down deals │
│ 4. Pattern Detection — Correlations between behaviors & wins │
│ 5. Risk Prediction — Which current deals match loss patterns │
│ 6. Coaching Signals — Data-driven coaching priorities │
├─────────────────────────────────────────────────────────────────┤
│ LEARNING │
│ • Updates deal-patterns.md with each analysis │
│ • Predictions improve as more outcomes are logged │
│ • Compares predictions to actuals to calibrate confidence │
├─────────────────────────────────────────────────────────────────┤
│ SUPERCHARGED (when you connect your tools) │
│ + ~~CRM: Full pipeline data, stage progression, deal velocity │
│ + ~~CRM: Rep performance metrics and owner segmentation │
│ + ~~conversation intelligence (Gong): Call activity per deal │
│ + ~~conversation intelligence (Gong): Talk patterns vs outcomes │
│ + ~~conversation intelligence (Gong): Competitor mention trends │
│ + ~~data enrichment (ZoomInfo): Pipeline company enrichment │
│ + ~~data enrichment (ZoomInfo): Tech stack patterns across deals│
│ + ~~data enrichment (Clay): Company signal monitoring │
│ + ~~data enrichment (LinkedIn): Stakeholder movement tracking │
│ + ~~chat: Team deal discussions and escalation signals │
└─────────────────────────────────────────────────────────────────┘
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.
- 8d ago First seen · 271 lines · 118 tokens per session scan A 1b41f3db54e1
pipeline-intelligence is a skill published in the GitHub repository jbalbu01/sales-enablement-plugin (14 stars, last pushed 6mo ago), licensed MIT. It adds 118 tokens to every session and 2,947 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 2026-08-30.
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