Ops Revenue logo

Ops Revenue

Organization
Lifecycle-Innovations-Limited
ops-revenue

OPS on-demand: This skill should be used when the user asks to "burn rate", "runway", or…

Overview

PublisherLifecycle-Innovations-Limited
Repositoryclaude-ops
Skill nameops-revenue
Stars
543
Forks
64
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Lifecycle-Innovations-Limited on GitHub. Read the source before you install it.

Installation

Install the Ops Revenue AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Lifecycle-Innovations-Limited/claude-ops/tree/main/claude-ops/skills/ops-revenue
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Lifecycle-Innovations-Limited/claude-ops.git /tmp/claude-ops
mkdir -p .claude/skills
cp -r /tmp/claude-ops/claude-ops/skills/ops-revenue .claude/skills/ops-revenue
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ops Revenue in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ops Revenue on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ops Revenue is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OPS ► REVENUE & COSTS

Load ops-rules before acting. Public repo (no personal data). Outbound: one draft → one approval → one send. If AskUserQuestion / Workflow are missing, follow Rule 10 in ops-rules (Hermes: numbered options / two-turn Telegram card; delegate_task).

Runtime Context

Before executing, load available context:

  1. Preferences: Read ${CLAUDE_PLUGIN_DATA_DIR:-$HOME/.claude/plugins/data/ops-ops-marketplace}/preferences.json

    • timezone — display all timestamps correctly
  2. Daemon health: Read ${CLAUDE_PLUGIN_DATA_DIR}/daemon-health.json

    • If action_needed is not null → surface it before the cost report
  3. Secrets: AWS Cost Explorer requires credentials.

    Secret Resolution

    • AWS: check $AWS_PROFILE / $AWS_ACCESS_KEY_ID → doppler secrets get AWS_ACCESS_KEY_ID --plain → vault query cmd from prefs
    • If no credentials available, report "AWS costs unavailable — credentials not configured" and show only the revenue pipeline from registry

CLI/API Reference

AWS burn doctrine (CRITICAL — 2026-07-22)

Never report plain UnblendedCost / NetUnblendedCost totals as "spend". Startup credits, SPP discounts, and Savings Plan negation make those nets ≈ $0 while real Usage burn is hundreds/day. Always use RECORD_TYPE=Usage for burn, pace, spikes, runway, and Bedrock. Show credits only as a mask line.

Canonical helper (prefer this over raw aws ce):

${CLAUDE_PLUGIN_ROOT}/scripts/aws-usage-cost.sh snapshot 2>/dev/null || echo '{}'
${CLAUDE_PLUGIN_ROOT}/scripts/aws-usage-cost.sh all 2>/dev/null || true
CommandUsageOutput
scripts/aws-usage-cost.sh snapshotMTD/prev Usage burn + 7d daily + top services + credit maskJSON
scripts/aws-usage-cost.sh daily 7Last N days Usage totalsJSON array
scripts/aws-usage-cost.sh by-service mtdMTD Usage by serviceJSON array
scripts/aws-usage-cost.sh record-typesCredit / Usage / SP breakdown (mask only)JSON array
aws ce get-cost-and-usage … --filter '{"Dimensions":{"Key":"RECORD_TYPE","Values":["Usage"]}}'Raw Usage-only CE (fallback if helper missing)Cost JSON
aws ce list-savings-plans-purchase-recommendationSavings plan recommendationsJSON

Phase 1 — Gather financial data in parallel

FinOps dashboard — canonical revenue + burn

If FINOPS_DASHBOARD_URL and FINOPS_OPS_API_TOKEN are configured, the dashboard is the single source of truth for per-project MRR, 30d revenue, and current burn. Per-DBA breakdown comes from the Stripe revenue snapshots ingested via /api/ops/revenue. Falls open to {} if unset — the per-source AWS / RevenueCat queries below run as fallback.

If the dashboard current_month_spend is ≈ $0 while Usage burn from aws-usage-cost.sh is material, trust the helper (dashboard may still be credit-masked or ingest-empty). Always dual-check with the Usage helper.

${CLAUDE_PLUGIN_ROOT}/scripts/finops-bridge.sh snapshot 2>/dev/null || echo "{}"
${CLAUDE_PLUGIN_ROOT}/scripts/finops-bridge.sh revenue project 2>/dev/null || echo "{}"

When the dashboard returns data, render the per-project MRR section from groups[] rather than from RevenueCat-only data.

AWS costs — Usage burn (authoritative)

${CLAUDE_PLUGIN_ROOT}/scripts/aws-usage-cost.sh snapshot 2>/dev/null || echo '{}'

Fallback if helper missing:

bash
USAGE_FILTER='{"Dimensions":{"Key":"RECORD_TYPE","Values":["Usage"]}}'
aws ce get-cost-and-usage \
  --time-period "Start=$(date +%Y-%m-01),End=$(date +%Y-%m-%d)" \
  --granularity MONTHLY \
  --metrics "UnblendedCost" \
  --filter "$USAGE_FILTER" \
  --group-by "Type=DIMENSION,Key=SERVICE" \
  --output json 2>/dev/null

AWS costs (last 3 months Usage trend)

bash
USAGE_FILTER='{"Dimensions":{"Key":"RECORD_TYPE","Values":["Usage"]}}'
aws ce get-cost-and-usage \
  --time-period "Start=$(date -v-3m +%Y-%m-01 2>/dev/null || date -d '3 months ago' +%Y-%m-01),End=$(date +%Y-%m-%d)" \
  --granularity MONTHLY \
  --metrics "UnblendedCost" \
  --filter "$USAGE_FILTER" \
  --output json 2>/dev/null

AWS credits / discount mask (not spend)

${CLAUDE_PLUGIN_ROOT}/scripts/aws-usage-cost.sh record-types 2>/dev/null || echo '[]'
bash
aws ce list-savings-plans-purchase-recommendation --output json 2>/dev/null || echo '{}'
aws ce get-credits --output json 2>/dev/null || echo "credits API unavailable"

AWS cost forecast (end of month)

Note: CE forecasts are often net-of-credits. Prefer eom_pace from aws-usage-cost.sh snapshot (7d Usage avg × days in month) as the burn forecast.

bash
aws ce get-cost-forecast \
  --time-period "Start=$(date +%Y-%m-%d),End=$(date +%Y-%m-28)" \
  --metric "UNBLENDED_COST" \
  --granularity MONTHLY \
  --output json 2>/dev/null

Project registry (revenue stage)

bash
cat "${CLAUDE_PLUGIN_ROOT}/scripts/registry.json" 2>/dev/null | jq '[.projects[] | {alias, name, stage: (.revenue_stage // .revenue.stage // "pre-revenue"), mrr: (.mrr // 0), source: (.source // "git"), type: (.type // "repo")}]'

External project revenue (Shopify, custom SaaS)

${CLAUDE_PLUGIN_ROOT}/bin/ops-external 2>/dev/null || echo '[]'

For Shopify projects showing status: "healthy", pull GMV via Shopify Admin API:

bash
# For each Shopify project in registry with valid credentials:
STORE_URL="[from project.shopify.store_url]"
TOKEN="[from env var named in project.shopify.credential_key]"
curl -s -H "X-Shopify-Access-Token: $TOKEN" \
  "https://$STORE_URL/admin/api/2024-10/orders.json?status=any&created_at_min=$(date -v-30d +%Y-%m-%dT00:00:00Z 2>/dev/null)&limit=250" 2>/dev/null

Include Shopify GMV in the revenue pipeline table with source=shopify.


Phase 2 — Render dashboard

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 OPS ► REVENUE & COSTS — [month]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

AWS USAGE BURN (RECORD_TYPE=Usage — not credit-masked net)
 This month usage:    $[X]     ← from aws-usage-cost.sh mtd_usage
 Forecast (EOM pace): $[X]     ← eom_pace (7d Usage avg × days)
 Last month usage:    $[X]
 MoM change:          [+/-X%]
 7d avg/day:          $[X]

 Top services (Usage):
 [service]  $[X]  ([%] of usage)
 [service]  $[X]
 ...

CREDITS / MASK (do not report as low spend)
 Credits applied MTD:    $[X]  (record_types Credit)
 Discounts MTD:          $[X]
 Net after mask:         ~$0 is EXPECTED when credits cover burn
 Credits remaining:      $[X] (if API available)
 Expires:                [date]
 Months cover at pace:   [N]

REVENUE PIPELINE
 PROJECT        SOURCE     STAGE           MRR/GMV    STATUS
 ──────────────────────────────────────────────────────────────
 [project]      git        [stage]         $[X]       [status]
 [project]      shopify    [stage]         $[X] GMV   [status]
 [project]      custom     [stage]         $[X]       [status]
 ...
 ──────────────────────────────────────────────────────────────
 TOTAL MRR                                 $[X]
 TOTAL SHOPIFY GMV (30d)                   $[X]

RUNWAY ESTIMATE
 Monthly burn (AWS):  $[X]
 Total MRR:           $[X]
 Net burn:            $[X/month]
 Credits cover:       [N months]
 Cash runway:         [depends on external data]

──────────────────────────────────────────────────────

Use batched AskUserQuestion calls (max 4 options each):

AskUserQuestion call 1:

  [Drill into AWS costs by service]
  [Show cost anomalies (spike detection)]
  [Export cost report]
  [More...]

AskUserQuestion call 2 (only if "More..."):

  [Update project revenue stage]
  [Set budget alert]

Route by $ARGUMENTS

ArgumentAction
costsShow only AWS cost breakdown
creditsShow only credits and expiry
revenueShow only revenue pipeline
runwayCalculate and show runway
(empty)Show full dashboard

Use AskUserQuestion after the dashboard for next action.


Native tool usage

WebFetch — billing API fallback

When aws ce commands fail or return incomplete data, use WebFetch to query the AWS Cost Explorer API directly. Also useful for fetching Stripe/billing provider data if configured.

Write — export reports

When user selects "Export cost report" (option c), use Write to save the report as a dated file:

Write(file_path: "/tmp/ops-revenue-[date].md", content: "[formatted report]")

Frequently asked questions

What does the Ops Revenue AI skill do?

OPS on-demand: This skill should be used when the user asks to "burn rate", "runway", or…

Why use Ops Revenue on TypingMind?

Because you install it once and use it with any model. Ops Revenue is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ops Revenue in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Lifecycle-Innovations-Limited/claude-ops/tree/main/claude-ops/skills/ops-revenue. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ops Revenue?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ops Revenue?

As many as you like. As long as a model supports skills, you can use Ops Revenue with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ops Revenue AI skill free?

Yes. It is published on GitHub by Lifecycle-Innovations-Limited under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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