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 elie222/atom-eve --skill revenue-pulsegit clone --depth 1 https://github.com/elie222/atom-eveWrote 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/elie222/atom-eve/revenue-pulse)<a href="https://agentmods.dev/skills/elie222/atom-eve/revenue-pulse"><img src="https://agentmods.dev/badge/skills/elie222/atom-eve/revenue-pulse/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/elie222/atom-eve/revenue-pulse"><img src="https://agentmods.dev/badge/skills/elie222/atom-eve/revenue-pulse.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 | $0.00033 | $0.00880 |
| Opus 5 | $0.00016 | $0.00440 |
| Sonnet 5 | $0.00007 | $0.00176 |
| Haiku 4.5 | $0.00003 | $0.00088 |
Grade A, and why
revenue-pulse scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 101 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Revenue & churn pulse workflow
You produce a grounded weekly revenue & churn pulse. All numbers come from CLIs
you run in the sandbox with bash. Never invent a figure.
0. Window
Compute the lookback window in Unix seconds. Default 7 days:
UNTIL=$(date +%s); SINCE=$(( UNTIL - 7*86400 ))
1. Stripe facts (stripe CLI)
Auth comes from STRIPE_API_KEY (a restricted, read-only key) in the env.
Every command returns JSON — pipe through jq. Add --live for live data
(default is test mode). Use --limit and paginate with --starting-after.
- New / active subscriptions in the window:
stripe subscriptions list --status active --created "gte=$SINCE" --limit 100 - Cancellations (churn) in the window — read the events, not just current state:
stripe events list --type "customer.subscription.deleted" --created "gte=$SINCE" --limit 100 - Failed payments / dunning risk:
stripe invoices list --status open --created "gte=$SINCE" --limit 100 stripe events list --type "invoice.payment_failed" --created "gte=$SINCE" --limit 100 - At-risk subscriptions (set to cancel, or past_due):
stripe subscriptions list --status past_due --limit 100 stripe get /v1/subscriptions -d "status=active" -d "limit=100" \ | jq '.data[] | select(.cancel_at_period_end == true)'
MRR: derive it from the subscription items' recurring prices
(items.data[].price.unit_amount * quantity, normalized to monthly). Sum across
active subscriptions; do not guess. Compare against the prior window the same way.
stripe get / stripe post give raw API access for anything a resource
sub-command doesn't surface directly.
2. Engagement cross-reference (posthog-cli)
For each at-risk customer, check product engagement. Auth via
POSTHOG_CLI_API_KEY and POSTHOG_CLI_PROJECT_ID.
Use the posthog-cli api workflow. Do not guess tool names or schemas:
posthog-cli api search query
posthog-cli api info <tool>
posthog-cli api call read-data-schema '<json>'
posthog-cli api call <tool> '<json>'
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 · 101 lines · 33 tokens per session scan A 4892177cc033
revenue-pulse is a skill published in the GitHub repository elie222/atom-eve (49 stars, last pushed 2mo ago), licensed MIT. It adds 33 tokens to every session and 880 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 2026-08-30.
Other skills, from other repositories
cost-efficiency-analyzer
Analyzes cost structure, cost efficiency, and expense management from P&L data. Use when the user asks about costs, expenses, COGS, operating expenses, cost ratios, cost control, spending efficiency, margin compression from cost side, or wants to understand where money is going. Also use for "are we spending too…
tinker-training-cost
Calculates training costs for Tinker fine-tuning jobs. Use when estimating costs for Tinker LLM training, counting tokens in datasets, or comparing Tinker model training prices. Tokenizes datasets using the correct model tokenizer and provides accurate cost estimates.
onboarding
First-time user onboarding to set up investment profile, watchlists, portfolio, and preferences.
chart-annotation
Draw price lines, trendlines, zones, and event markers directly on a stock's price chart — reach for it whenever you'd otherwise describe a level, pattern, or event in prose. Renders live on MarketView and as a clickable preview card in any other chat.
check-deck
Investment deck QC: number consistency, data-narrative alignment, IB language, formatting audit.
check-model
Financial model audit: structural checks, formula validation, integrity testing.