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 san-npm/skills-ws --skill revenue-operationsgit clone --depth 1 https://github.com/san-npm/skills-wsWrote 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/san-npm/skills-ws/revenue-operations)<a href="https://agentmods.dev/skills/san-npm/skills-ws/revenue-operations"><img src="https://agentmods.dev/badge/skills/san-npm/skills-ws/revenue-operations/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/san-npm/skills-ws/revenue-operations"><img src="https://agentmods.dev/badge/skills/san-npm/skills-ws/revenue-operations.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 | $0.00073 | $0.05691 |
| Opus 5 | $0.00036 | $0.02846 |
| Sonnet 5 | $0.00015 | $0.01138 |
| Haiku 4.5 | $0.00007 | $0.00569 |
Grade A, and why
revenue-operations 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 5d 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 — 353 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Revenue Operations
Workflow
1. Revenue Funnel Definitions
Align ALL teams on the same definitions:
| Stage | Definition | Owner | SLA |
|---|---|---|---|
| Visitor | Hit website or content | Marketing | — |
| Lead | Known contact (form fill, signup) | Marketing | Enrich within 24h |
| MQL | Meets scoring threshold (fit + engagement) | Marketing | Route within 5 min |
| SAL | Sales accepted, meeting booked | SDR/BDR | Contact within 1 hour |
| SQL | Qualified by sales (BANT/MEDDIC confirmed) | AE | Discovery within 3 days |
| Opportunity | In pipeline with defined next steps | AE | Advance or close within 90 days |
| Closed Won | Contract signed, revenue booked | AE → CS | Handoff within 48h |
Conversion benchmarks — segment before you compare. Public "B2B SaaS averages" are nearly useless because conversion is dominated by motion (PLG vs sales-led), ACV, channel (inbound vs outbound), ICP fit, and market maturity. Treat the table below as order-of-magnitude priors, not targets — then compute your own baselines (next).
| Stage transition | PLG / self-serve (low ACV <$5k) | Inbound sales-led (mid ACV $5k–50k) | Outbound / enterprise (ACV >$50k) |
|---|---|---|---|
| Visitor → Lead (signup) | 2–8% | 1–3% | <1% (ABM, not volume) |
| Lead → MQL | n/a (PQL instead) | 15–35% | 25–45% (tight ICP) |
| MQL/PQL → SAL (accepted) | 5–15% PQL→sales | 50–70% | 60–85% |
| SAL → SQL | 50–70% | 40–60% | 35–55% (longer qual) |
| SQL → Opportunity | 60–80% | 50–70% | 45–65% |
| Opportunity → Closed Won | 25–40% | 18–30% | 15–25% (more stakeholders) |
| Blended visitor→won | varies widely | 0.3–1.5% | <0.3% |
Outbound-sourced opps usually convert at a higher win rate but lower top-of-funnel volume than inbound; PLG replaces MQL with PQL (product-qualified lead — hit an activation/usage threshold) and SAL with a sales-assist trigger.
What ships with it
1 file 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.
- 5d ago First seen · 353 lines · 73 tokens per session scan A 7b2e946f36e9
revenue-operations is a skill published in the GitHub repository san-npm/skills-ws (2 stars, last pushed 5d ago), licensed MIT. It adds 73 tokens to every session and 5,691 once invoked, about $0.0004 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 2026-09-07.
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