--- name: growth-engine-c9c115ce18d6 description: "Open-source AI marketing skills for Claude Code \u2014 growth experiments, sales pipeline, content ops, outbound, SEO, and finance automation" --- # Growth Engine ## Preamble (runs on skill start) ```bash # Version check (silent if up to date) python3 telemetry/version_check.py 2>/dev/null || true # Telemetry opt-in (first run only, then remembers your choice) python3 telemetry/telemetry_init.py 2>/dev/null || true ``` > **Privacy:** This skill logs usage locally to `~/.ai-marketing-skills/analytics/`. Remote telemetry is opt-in only. No code, file paths, or repo content is ever collected. See `telemetry/README.md`. --- Autonomous growth experimentation framework based on Karpathy's autoresearch pattern applied to marketing. Creates experiments with hypotheses, logs data points, runs statistical analysis (bootstrap CI + Mann-Whitney U), auto-promotes winners to a living playbook, and suggests next experiments. Supports batch mode (up to 10 variants simultaneously). ## Usage Use this skill when: - Creating or managing A/B or multivariate experiments for any marketing channel - Logging experiment data points after content is published or campaigns run - Scoring experiments to determine statistical winners - Checking the playbook for proven best practices before creating new content - Generating weekly scorecards across all channels - Monitoring campaign pacing and health Do NOT use for: - One-off content creation (use the playbook output as input, but don't run the engine) - Non-experiment analytics or reporting - Campaign setup in external platforms (this tracks experiments, not campaign config) ## Commands ### Create an experiment ```bash python3 experiment-engine.py create \ --agent \ --hypothesis "What you expect to happen" \ --variable "" \ --variants '["variant_a", "variant_b"]' \ --metric "" \ --cycle-hours 24 ``` Add `--batch-mode` for 3-10 variant tests. Add `--min-samples N` to override auto-detection. ### Log a data point ```bash python3 experiment-engine.py log \ --agent \ --experiment-id \ --variant "" \ --metrics '{"metric_name": value}' ``` ### Score an experiment ```bash python3 experiment-engine.py score --agent --experiment-id ``` Statuses: `running` → `trending` → `keep` (winner) or `discard` (loser) Winners auto-promote to the playbook. Requires p < 0.05 AND ≥ 15% lift. ### List experiments ```bash python3 experiment-engine.py list --agent [--status running|trending|keep|discard] ``` ### Check the playbook ```bash python3 experiment-engine.py playbook --agent ``` Always check the playbook before creating new content to apply proven best practices. ### Suggest next experiments ```bash python3 experiment-engine.py suggest --agent ``` ### Generate weekly scorecard ```bash python3 autogrowth-weekly-scorecard.py [--weeks N] [--output file.md] ``` ### Check campaign pacing ```bash python3 pacing-alert.py [--json] ``` Exit code 0 = on pace, 1 = alerts present. ## Workflow 1. Before creating content: `playbook` → apply proven rules 2. When publishing: `log` → record which variant was used and its metrics 3. Periodically: `score` → check if experiments have reached statistical significance 4. Weekly: `autogrowth-weekly-scorecard.py` → review all channels 5. After completing experiments: `suggest` → pick the next variable to test ## Configuration ### Required Environment Variables | Variable | Description | |----------|-------------| | `GROWTH_ENGINE_DATA_DIR` | Data directory (default: `./data/experiments`) | | `GROWTH_ENGINE_AGENTS` | Comma-separated agent names (default: `content,email,linkedin,seo,blog`) | ### Optional Tuning | Variable | Default | Description | |----------|---------|-------------| | `HIGH_VOLUME_AGENTS` | `content,email` | Agents needing only 10 samples/variant | | `LOW_VOLUME_AGENTS` | `seo,linkedin,blog` | Agents needing 30 samples/variant | | `P_WINNER` | `0.05` | p-value threshold for winner | | `P_TREND` | `0.10` | p-value threshold for trending | | `LIFT_WIN` | `15.0` | Minimum % lift for keep decision | | `BOOTSTRAP_ITERATIONS` | `1000` | Bootstrap resamples for CI | | `BATCH_MODE_MAX_VARIANTS` | `10` | Max variants in batch mode | ### Pacing Alert Variables | Variable | Description | |----------|-------------| | `PIPELINE_API_URL` | Pipeline/CRM API endpoint | | `PIPELINE_AUTH_TOKEN` | Bearer token for pipeline API | | `RECRUITING_API_URL` | Recruiting API endpoint | | `RECRUITING_AUTH_TOKEN` | Bearer token for recruiting API | | `EMAIL_API_URL` | Email platform API base URL | | `EMAIL_AUTH_TOKEN` | Bearer token for email platform | | `OUTBOUND_CAMPAIGNS` | JSON: `{"name": "campaign-id"}` | | `RECRUITING_CAMPAIGNS` | JSON: `{"name": "campaign-id"}` | | `DAILY_LEAD_TARGET` | Leads/day target (default: 10) | | `WEEKLY_CANDIDATE_TARGET` | Candidates/week target (default: 400) | ### Dependencies ``` pip install numpy scipy ``` --- Source attribution: ericosiu Original project: https://github.com/ericosiu/ai-marketing-skills/blob/8088e1a167804d5615f6e982f62e5b4b6ff8f2f1/growth-engine/SKILL.md License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Single Grain Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: ericosiu Original project: https://github.com/ericosiu/ai-marketing-skills/blob/8088e1a167804d5615f6e982f62e5b4b6ff8f2f1/growth-engine/SKILL.md Attribution basis: Source repository record Fields of work: Marketing Roles: Content Marketer, Growth Marketer, Marketing Analyst, Product Marketer, SEO Specialist Specialties: API Tools: Python Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: 26c61868a9138bfd4f5763efa4f7270b49e79d9405caf4fcb5b914a12aaae23e