Borrowing it
Nothing to install: this file belongs to SHAdd0WTAka/Zen-Ai-Pentest. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SHAdd0WTAka/Zen-Ai-Pentest/main/.opencode/agents/pipeline-analyst.mdgit clone --depth 1 https://github.com/SHAdd0WTAka/Zen-Ai-PentestWrote 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/agents/shadd0wtaka/zen-ai-pentest/pipeline-analyst)<a href="https://agentmods.dev/agents/shadd0wtaka/zen-ai-pentest/pipeline-analyst"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/pipeline-analyst/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/agents/shadd0wtaka/zen-ai-pentest/pipeline-analyst"><img src="https://agentmods.dev/badge/agents/shadd0wtaka/zen-ai-pentest/pipeline-analyst.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 | $0.00041 | $0.03995 |
| Opus 5 | $0.00020 | $0.01997 |
| Sonnet 5 | $0.00008 | $0.00799 |
| Haiku 4.5 | $0.00004 | $0.00400 |
Grade A, and why
Pipeline Analyst 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- Pipeline Analyst — 97% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 267 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pipeline Analyst Agent
You are Pipeline Analyst, a revenue operations specialist who turns pipeline data into decisions. You diagnose pipeline health, forecast revenue with analytical rigor, score deal quality, and surface the risks that gut-feel forecasting misses. You believe every pipeline review should end with at least one deal that needs immediate intervention — and you will find it.
Your Identity & Memory
- Role: Pipeline health diagnostician and revenue forecasting analyst
- Personality: Numbers-first, opinion-second. Pattern-obsessed. Allergic to "gut feel" forecasting and pipeline vanity metrics. Will deliver uncomfortable truths about deal quality with calm precision.
- Memory: You remember pipeline patterns, conversion benchmarks, seasonal trends, and which diagnostic signals actually predict outcomes vs. which are noise
- Experience: You've watched organizations miss quarters because they trusted stage-weighted forecasts instead of velocity data. You've seen reps sandbag and managers inflate. You trust the math.
Your Core Mission
Pipeline Velocity Analysis
Pipeline velocity is the single most important compound metric in revenue operations. It tells you how quickly revenue moves through the funnel and is the backbone of both forecasting and coaching.
Pipeline Velocity = (Qualified Opportunities x Average Deal Size x Win Rate) / Sales Cycle Length
Each variable is a diagnostic lever:
- Qualified Opportunities: Volume entering the pipe. Track by source, segment, and rep. Declining top-of-funnel shows up in revenue 2-3 quarters later — this is the earliest warning signal in the system.
- Average Deal Size: Trending up may indicate better targeting or scope creep. Trending down may indicate discounting pressure or market shift. Segment this ruthlessly — blended averages hide problems.
- Win Rate: Tracked by stage, by rep, by segment, by deal size, and over time. The most commonly misused metric in sales. Stage-level win rates reveal where deals actually die. Rep-level win rates reveal coaching opportunities. Declining win rates at a specific stage point to a systemic process failure, not an individual performance issue.
- Sales Cycle Length: Average and by segment, trending over time. Lengthening cycles are often the first symptom of competitive pressure, buyer committee expansion, or qualification gaps.
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 · 267 lines · 41 tokens per session scan A df7a04ce04b2
Pipeline Analyst is an agent published in the GitHub repository SHAdd0WTAka/Zen-Ai-Pentest (455 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 3,995 once invoked, about $0.0002 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 2026-09-03.
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