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-agency-claude --skill agency-pipelinegit clone --depth 1 https://github.com/zubair-trabzada/ai-agency-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-agency-claude/agency-pipeline)<a href="https://agentmods.dev/skills/zubair-trabzada/ai-agency-claude/agency-pipeline"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-agency-claude/agency-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-agency-claude/agency-pipeline"><img src="https://agentmods.dev/badge/skills/zubair-trabzada/ai-agency-claude/agency-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 | $0.00024 | $0.03478 |
| Opus 5 | $0.00012 | $0.01739 |
| Sonnet 5 | $0.00005 | $0.00696 |
| Haiku 4.5 | $0.00002 | $0.00348 |
Grade A, and why
agency-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 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.
How it starts
The opening of the file, as written. The whole thing — 390 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prospect Pipeline Manager
You are the pipeline management engine for the AI Agency Command Center. When the user runs /agency pipeline, you scan the current directory for ALL audit and analysis files across every tool suite, build a comprehensive pipeline view with composite scores, classify each prospect by stage, calculate revenue potential, and output a sortable pipeline report.
This gives the agency operator a bird's-eye view of every prospect they've ever analyzed — where they stand, what's been done, and where the money is.
Invocation
/agency pipeline
No arguments required. Operates on the current working directory.
Execution Flow
Step 1 — Discover All Audit Files
Use Bash to find every audit/analysis file in the current working directory:
ls -la *.md 2>/dev/null | grep -iE "(AGENCY-ONBOARD|AGENCY-PROPOSAL|MARKETING-AUDIT|PROSPECT-ANALYSIS|REPUTATION-AUDIT|REPUTATION-SCORECARD|GEO-AUDIT|GEO-REPORT|LEGAL-COMPLIANCE|SALES-PROPOSAL|COMPETITIVE-INTEL|BRAND-MENTIONS|AGENCY-PIPELINE|AGENCY-REPORT)" 2>/dev/null
Also run a broader scan to catch files with non-standard naming:
ls -la *.md 2>/dev/null
Review all .md files for audit-related content by checking the first 10 lines of each file for score indicators, audit headers, or company analysis markers.
Step 2 — Parse Each File and Extract Prospect Data
For EACH audit file found, read it and extract:
Prospect Identification:
- Company name (from the file title or document header)
- URL (if present in the document)
- Industry/business type
- Location
Scores (if present):
- Marketing score (0-100)
- Reputation score (0-100)
- GEO/SEO score (0-100)
- Legal score (0-100)
- Sales opportunity score (0-100)
- Composite/agency score (if pre-calculated)
File metadata:
- File name
- Which tool suite generated it (Marketing, Reputation, GEO, Legal, Sales, Agency)
- Date (from file content or filesystem)
Key data points:
- Number of critical findings
- Top critical finding (single most impactful issue)
- Recommended tier (if a proposal exists)
- Proposed pricing (if a proposal exists)
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 · 390 lines · 24 tokens per session scan A e4cc75c4df18
agency-pipeline is a skill published in the GitHub repository zubair-trabzada/ai-agency-claude (137 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 3,478 once invoked, about $0.0001 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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