Measure GTM with the metrics that matter (net developer retention, DREAM funnel) instead of vanity numbers. Use when the founder has dashboards full of stars and pageviews but can't tell if go-to-market is working, or is optimizing acquisition over a leaky bucket.
npx skills add https://github.com/AIDevGTM/gtm-cofounder --skill know-if-its-working
> The only early metric that matters is net developer retention. Without it, you're not running a funnel; you're running a colander.
Use this when: you're tracking GitHub stars and pageviews and still can't answer "is GTM working?", or you're pouring effort into acquisition while new users quietly churn.
Acquisition is worthless if users don't come back. Prove retention first; only then does spending on acquisition make sense. Most early founders optimize the top of the funnel while the bottom leaks. Fix that order.
> Of all the developers who first used the product in Month 1, how many used it in Month 2? Month 3?
Measure one honest number per stage, not pageviews, not stars.
| Stage | The metric that counts |
|---|---|
| Discovery | unique human visitors / month |
| Research | newsletter subs + community joins + follows |
| Evaluation | free-tier signups / downloads / active free users |
| Activation | monthly active users · frequency · session depth |
| Membership | community members *actively* posting & answering |
The gate before all of it, the weekend test: can a new developer get to first value over a weekend from docs + Stack Overflow, no support call? Time-to-value target: < 1 hour ideal, 1 day max. If Evaluation/Activation fails here, no channel work will save you.
Developer marketing is hard to attribute and that's normal. A dev sees your HN post, reads a tutorial, lurks for two months, then signs up direct.
Is month-2 cohort retention healthy (users come back)?
├─ NO → STOP optimizing acquisition. Fix Evaluation/Activation (the weekend test, time-to-value).
└─ YES → is a channel reliably producing retained users?
├─ YES → pour more in (and only now consider paid to amplify).
└─ NO → go back to first-50-users; find the channel before scaling spend.
Built from real dev-tool GTM experience, with frameworks from Adam Frankl (*The Developer-Facing Startup*) and Jakub Czakon (*markepear.dev*).
When a framework can't make the call, that's what a human is for: The DevTool GTM Company.
Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas
Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like \"the xlsx in my downloads\") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.
Picks random winners from lists, spreadsheets, or Google Sheets for giveaways, raffles, and contests. Ensures fair, unbiased selection with transparency.
Query openFDA API for drugs, devices, adverse events, recalls, regulatory submissions (510k, PMA), substance identification (UNII), for FDA regulatory data analysis and safety research.
MATLAB and GNU Octave numerical computing for matrix operations, data analysis, visualization, and scientific computing. Use when writing MATLAB/Octave scripts for linear algebra, signal processing, image processing, differential equations, optimization, statistics, or creating scientific visualizations. Also use when the user needs help with MATLAB syntax, functions, or wants to convert between MATLAB and Python code. Scripts can be executed with MATLAB or the open-source GNU Octave interpreter.
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
Creating interactive data visualisations using d3.js. This skill should be used when creating custom charts, graphs, network diagrams, geographic visualisations, or any complex SVG-based data visualisation that requires fine-grained control over visual elements, transitions, or interactions. Use this for bespoke visualisations beyond standard charting libraries, whether in React, Vue, Svelte, vanilla JavaScript, or any other environment.
Access AlphaFold 200M+ AI-predicted protein structures. Retrieve structures by UniProt ID, download PDB/mmCIF files, analyze confidence metrics (pLDDT, PAE), for drug discovery and structural biology.
Take aidevgtm/know-if-its-working from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.