Pnpm Engine
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Help external users integrate Databuddy into their own apps.
Install Databuddy
$ npx skills add databuddy-analytics/Databuddy --skill databuddy -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install databuddy-analytics/Databuddy databuddy --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/databuddy-analytics/Databuddy.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/databuddy .claude/skills/databuddy && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "databuddy" agent skill from https://github.com/databuddy-analytics/Databuddy/tree/main/.agents/skills/databuddy into .claude/skills/databuddy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databuddy", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/databuddy-analytics/Databuddy/tree/main/.agents/skills/databuddyType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add databuddy-analytics/Databuddy --skill databuddy -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install databuddy-analytics/Databuddy databuddy --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/databuddy-analytics/Databuddy.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/databuddy .agents/skills/databuddy && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "databuddy" agent skill from https://github.com/databuddy-analytics/Databuddy/tree/main/.agents/skills/databuddy into .agents/skills/databuddy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databuddy", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add databuddy-analytics/Databuddy --skill databuddy -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install databuddy-analytics/Databuddy databuddy --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/databuddy-analytics/Databuddy.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/databuddy .cursor/skills/databuddy && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "databuddy" agent skill from https://github.com/databuddy-analytics/Databuddy/tree/main/.agents/skills/databuddy into .cursor/skills/databuddy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databuddy", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/databuddy-analytics/Databuddy.git --path .agents/skills/databuddy--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add databuddy-analytics/Databuddy --skill databuddy -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install databuddy-analytics/Databuddy databuddy --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/databuddy-analytics/Databuddy.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/databuddy .gemini/skills/databuddy && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "databuddy" agent skill from https://github.com/databuddy-analytics/Databuddy/tree/main/.agents/skills/databuddy into .gemini/skills/databuddy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databuddy", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install databuddy-analytics/Databuddy databuddyInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add databuddy-analytics/Databuddy --skill databuddy -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/databuddy-analytics/Databuddy.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/databuddy .github/skills/databuddy && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "databuddy" agent skill from https://github.com/databuddy-analytics/Databuddy/tree/main/.agents/skills/databuddy into .github/skills/databuddy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databuddy", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add databuddy-analytics/Databuddy --skill databuddy -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install databuddy-analytics/Databuddy databuddy --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/databuddy-analytics/Databuddy.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/databuddy .opencode/skills/databuddy && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "databuddy" agent skill from https://github.com/databuddy-analytics/Databuddy/tree/main/.agents/skills/databuddy into .opencode/skills/databuddy/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "databuddy", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
databuddy- GitHub stars
- 1.2k
- Token cost
- ~2k tokens
- SKILL.md length
- 915 words
- Files
- 10 (incl. references)
- Skills in repo
- 8
- Repo updated
- First seen
- Licence
- AGPL-3.0
At a glance
Help external users integrate Databuddy into their own apps.
- Works in 5 steps: Identify the user's runtime and target… → Prefer the highest-level supported SDK… → Infer the minimum credential, or ask for… → …
- React/Vue/vanilla browser tracking
- SKILL.md covers Choose The Surface, Credential And Endpoint Rules, Workflow and Custom Event Rules, plus 2 more sections
- Reaches api.databuddy.cc and basket.databuddy.cc; needs DATABUDDY_API_KEY
What it does
Databuddy is an agent skill from databuddy-analytics/Databuddy. Help external users integrate Databuddy into their own apps. Use for SDK setup, React/Vue/vanilla browser tracking, Node/server event tracking, custom event planning, attribution, feature flag evaluation, experiments, Databuddy DevTools, REST analytics queries, and event ingestion. Do not use for Databuddy monorepo implementation work; use databuddy-internal.
Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including reference files (for example `agents/openai.yaml`, `references/devtools.md` and `references/event-design.md`).
It sits in Development, covering Product analytics and Monorepo tooling. It works with React, Vue.js and Next.js. The repository describes itself as: Open-source product analytics for startups: track visitors, events, funnels, and goals without cookies, and ask Databunny, the built-in AI analyst. Uptime, feature flags, and… The licence is AGPL-3.0.
When your agent uses it
- React/Vue/vanilla browser tracking
- Node/server event tracking
- Custom event planning
- Feature flag evaluation
Example prompts
- “/databuddy”
Requirements
- A credential in DATABUDDY_API_KEY
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- Identify the user's runtime and target surface.
- Prefer the highest-level supported SDK over raw HTTP.
- Infer the minimum credential, or ask for only the missing one.
- Give a short install/env/code path plus one verification step.
- For custom instrumentation, define question -> metric -> event -> properties -> source -> placement -> verification before adding code.
What it can do on your machine
Read from SKILL.md and the folder at commit 5f63610. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
api.databuddy.ccbasket.databuddy.cccdn.databuddy.cc
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
DATABUDDY_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Databuddy loads about 2k tokens when it runs, and up to ~12k if it reads all its reference files. Until then it costs about 93 tokens; SKILL.md has 915 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from databuddy-analytics/Databuddy at commit 5f63610, republished under its AGPL-3.0 licence (© databuddy-analytics). 915 words, ~1,972 tokens.
Download SKILL.mdSave it as
.claude/skills/databuddy/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.- name
- databuddy
- description
- Help external users integrate Databuddy into their own apps. Use for SDK setup, React/Vue/vanilla browser tracking, Node/server event tracking, custom event planning, attribution, feature flag evaluation, experiments, Databuddy DevTools, REST analytics queries, and event ingestion. Do not use for Databuddy monorepo implementation work; use databuddy-internal.
Databuddy
Use this skill for people adopting Databuddy in their own app or backend. Optimize for a working public integration or instrumentation plan: the right package, credential, endpoint, events, placement, and verification step.
Do not expose DATABUDDY_API_KEY in browser code. Browser integrations use a public website clientId; server/API integrations use an API key.
Choose The Surface
- React or Next.js browser analytics:
@databuddy/sdk/react; mount<Databuddy />near the app root. - Vue or Nuxt browser analytics:
@databuddy/sdk/vue; mount<Databuddy />once nearRouterView/NuxtPageand translate props to kebab-case in templates. - Vanilla HTML, CMS, or GTM: CDN script
https://cdn.databuddy.cc/databuddy.jswithdata-client-id. - Browser custom events:
track(...)from@databuddy/sdkafter the tracker is installed. - Browser helper utilities: use
trackError,flush,clear,getTrackingIds,getTrackingParams,getAnonymousId,getSessionId,isTrackerAvailable, andgetTrackerfrom@databuddy/sdkwhen users need manual errors, navigation safety, logout reset, attribution handoff, or advanced checks. - Server-side events:
@databuddy/sdk/node; callflush()before a serverless/short-lived runtime exits. - Feature flags: React/Vue flag helpers or
createServerFlagsManagerfrom@databuddy/sdk/node; use stable user context, handle loading/pending states, and callwaitForInit()before first server read. - DevTools:
@databuddy/devtools; use for local/preview inspection of tracker status, IDs, queues, event calls, flags, overrides, diagnostics, and flag management. - REST analytics: query API under
https://api.databuddy.cc/v1. - Raw event ingestion:
POST https://basket.databuddy.cc/track; prefer SDKs unless the user explicitly wants HTTP.
Do not recommend @databuddy/sdk/ai/vercel; the public SDK currently exports only core, React, Vue, and Node entry points.
If the user says "API", determine whether they mean analytics queries, event ingestion, or feature flags before writing code.
Read public-surfaces.md when you need exact env vars, routes, scopes, snippets, or framework routing.
Read frameworks.md for React, Next.js, Vue, Nuxt, and vanilla browser setup.
Read server-events.md for browser helpers, Node/server events, raw /track, and attribution handoff.
Read feature-flags.md for client flags, server flags, rollouts, experiments, flag metrics, and flag debugging.
Read devtools.md for @databuddy/devtools setup, capabilities, flag overrides, diagnostics, and flag management.
Read event-design.md when the user asks what custom events to add, which properties matter, or how to avoid noisy/high-cardinality tracking.
Read instrumentation-planning.md when the user asks what to track, how to design metrics, how to wire attribution across client/server, or where to place tracking calls.
Read troubleshooting.md for CSP, blockers, wrong hosts, auth, missing events, and flag/debug failures.
Credential And Endpoint Rules
| Use | Host/path | Credential | Scope |
|---|---|---|---|
| Browser analytics | https://basket.databuddy.cc via SDK/CDN | clientId | none |
| Server events | POST https://basket.databuddy.cc/track | DATABUDDY_API_KEY | track:events |
| REST analytics | https://api.databuddy.cc/v1/query... | DATABUDDY_API_KEY | read:data |
| Feature flag evaluation | https://api.databuddy.cc/public/v1/flags... | clientId | none |
- API auth accepts
x-api-key: dbdy_...orAuthorization: Bearer dbdy_...; preferx-api-keyfor examples unless docs for that endpoint use Bearer. websiteIdin event tracking means the public website client id, the same kind of value used bydata-client-id; it is not necessarily an internal UUID.- For server-side attribution, collect
{ anonId, sessionId }in the browser withgetTrackingIds(), pass them to your backend, then map them to Node SDK fieldsanonymousIdandsessionId. - Visitor ID privacy is configured with
anonymizeVisitorIds(true/omitted = anonymized,false= keeps raw IDs,"auto"= raw only in Databuddy's conservative country allowlist); avoid internal wording like storage or hashing in public examples. - Do not invent a Databuddy
identify()helper or endpoint. If an app has an identify route, treat it as the user's own backend code carrying Databuddy tracking IDs. - Feature flag evaluation uses the main API host, not basket. It needs a website
clientId, not API-key-only auth. - Feature flag management uses
manage:flagswithx-api-key; do not expose that key in browser source. DevTools accepts it at runtime for local/preview flag management. DATABUDDY_API_URLis endpoint-specific. Do not reuse a basket root for query API or flags.- Strict CSP sites need
script-srcforhttps://cdn.databuddy.ccandconnect-srcforhttps://basket.databuddy.cc; addhttps://api.databuddy.ccwhen using flags.
Show full SKILL.md (316 more words)Show less
Workflow
- Identify the user's runtime and target surface.
- Prefer the highest-level supported SDK over raw HTTP.
- Infer the minimum credential, or ask for only the missing one.
- Give a short install/env/code path plus one verification step.
- For custom instrumentation, define
question -> metric -> event -> properties -> source -> placement -> verificationbefore adding code.
Custom Event Rules
- Track user intent, product milestones, and operational outcomes, not every click.
- Use stable
snake_casenames and low-cardinality property keys. - Do not track PII, secrets, raw tokens, full exception stacks, or large payloads.
- Prefer one event with useful properties over many near-duplicate event names.
- Use backend tracking for authoritative outcomes such as account creation, imports, webhooks, and jobs.
- Start with the fewest events that answer the user's question; add more only for funnel steps, important variants, or failure states.
- Do not track the same outcome in both browser and backend. Use browser events for intent and backend events for completed or failed outcomes.
Verification
- Browser SDK:
- confirm the script loads and requests reach
basket.databuddy.cc - confirm the expected
clientIdis configured - check CSP, ad-blockers, and registered/allowed domain settings if requests never leave the browser
- confirm the script loads and requests reach
- Node SDK:
- send one test event
- call
flush()before exit - confirm no auth or queue errors
- REST API:
- start with
GET /v1/query/websites - then run the scoped query or event send
- start with
- Feature flags:
- wait for initialization
- test with a known flag key and user context
- use DevTools to inspect readiness, evaluated values, variants, and overrides
- Custom instrumentation:
- verify the event appears under the intended website
- confirm attribution IDs are present when a server event belongs to a browser session
- confirm the event can power the intended funnel, goal, segment, or reliability metric
Response Style
- Default to practical integration guidance and working examples
- Avoid internal monorepo details unless the user is debugging Databuddy itself.
- Keep answers short unless the user asks for a migration or full instrumentation plan.
© databuddy-analytics, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 9 other files (references) in .agents/skills/databuddy of databuddy-analytics/Databuddy.
- SKILL.md
- agents/openai.yaml
- references/devtools.md
- references/event-design.md
- references/feature-flags.md
- references/frameworks.md
- references/instrumentation-planning.md
- references/public-surfaces.md
- references/server-events.md
- references/troubleshooting.md
Open the folder on GitHubat commit 5f63610
Compare with similar skills
Databuddy next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Databuddy this skilldatabuddy-analytics/Databuddy | 1.2k | — | ~2k | Automated safety check: Pass | AGPL-3.0 | |
| Pnpm Engineteambit/bit | 18k | — | ~1.9k | Automated safety check: Pass | Custom licence | |
| Project Guidelinesmirumee/nimara-ecommerce | 129 | — | ~4.8k | Automated safety check: Pass | BSD-3-Clause | |
| Any Tdf Developmentany-tdf/any-tdf | 779 | — | ~1.1k | Automated safety check: Pass | MIT | |
| LobeHub Project Maplobehub/lobehub | 83k | — | ~1.8k | Automated safety check: Pass | Custom licence | |
| Scaffold ProjectMarve10s/Better-Fullstack | 752 | — | ~716 | Automated safety check: Pass | MIT |
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Questions about Databuddy
What does Databuddy do?
Help external users integrate Databuddy into their own apps. Databuddy is an agent skill from databuddy-analytics/Databuddy. Help external users integrate Databuddy into their own apps.
When should I use Databuddy?
Databuddy fits situations like: React/Vue/vanilla browser tracking; Node/server event tracking; custom event planning; feature flag evaluation.
How do I install Databuddy in Claude Code?
Run `npx skills add databuddy-analytics/Databuddy --skill databuddy -a claude-code`. Or copy the skill folder (.agents/skills/databuddy in databuddy-analytics/Databuddy) into .claude/skills/databuddy in your project. Claude Code loads it when a task matches its description.
How do I install Databuddy in Codex?
Run `npx skills add databuddy-analytics/Databuddy --skill databuddy -a codex`. Or copy the skill folder (.agents/skills/databuddy in databuddy-analytics/Databuddy) into .agents/skills/databuddy in your project. Codex loads it when a task matches its description.
Can I use Databuddy in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add databuddy-analytics/Databuddy --skill databuddy -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/databuddy, .gemini/skills/databuddy, .github/skills/databuddy and .opencode/skills/databuddy in your project.
What does Databuddy need to run?
Going by SKILL.md and its folder, Databuddy needs credentials named DATABUDDY_API_KEY. Our summary lists: A credential in DATABUDDY_API_KEY.
Does Databuddy access the network?
SKILL.md names 3 domains. In commands or code: api.databuddy.cc, basket.databuddy.cc and cdn.databuddy.cc; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.
Is Databuddy safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Databuddy use?
Databuddy is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Databuddy use?
About 2k tokens (SKILL.md is roughly 7.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 10k tokens, read only when the agent opens those files.
What are the alternatives to Databuddy?
Skills that share tags, products or a category with Databuddy: Pnpm Engine (teambit/bit, 18k stars), Project Guidelines (mirumee/nimara-ecommerce, 129 stars), Any Tdf Development (any-tdf/any-tdf, 779 stars) and LobeHub Project Map (lobehub/lobehub, 83k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Databuddy?
databuddy-analytics (a GitHub organization) maintains it in databuddy-analytics/Databuddy, which has 1,177 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on October 7, 2026.
Source: databuddy-analytics/Databuddy on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.