frontend-starter-kit
Skill4 starsChanged 10 days agoMITView on GitHub
Bootstrap the frontend toolchain, lint, quality gates, React stack, data stack, and CI.
In this repository117 other files it gives its agents.
- AGENTS.mdAGENTS.md
- CLAUDE.mdCLAUDE.md
- accessibilitySkill
- agent-watchdogSkill
- aipSkill
- animateSkill
- animation-performanceSkill
- animation-vocabularySkill
- ask-benSkill
- ask-sonnerSkill
- bazelSkill
- bend-lawsSkill
- blast-radiusSkill
- brain-dumpSkill
- break-uiSkill
- ci-fixesSkill
- codebase-designSkill
- codex-compatSkill
- codexSkill
- commit-push-prSkill
- connect-querySkill
- create-verification-skillSkill
- demoSkill
- development-lifecycleSkill
- diagnosing-bugsSkill
- docsSkill
- dogfoodSkill
- domain-modelingSkill
- e2e-testingSkill
- effect-tsSkill
- effect-v3-to-v4Skill
- efficient-frontierSkill
- eli5Skill
- excalidraw-diagramSkill
- extend-harnessSkill
- frontend-invariantsSkill
- full-sendSkill
- gesturesSkill
- golang-reviewSkill
- golangSkill
- goSkill
- grillingSkill
- handoffSkill
- hook-auditSkill
- implement-specSkill
- improve-animationsSkill
- improve-codebase-architectureSkill
- improveSkill
- launchdarklySkill
- lie-detectorSkill
- maintain-verification-skillSkill
- make-pr-easy-to-reviewSkill
- mobile-nativeSkill
- plan-arbiterSkill
- plow-aheadSkill
- postgresqlSkill
- primeSkill
- productSkill
- protobufSkill
- prototypeSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
2 rules. About 0 are common, 1 is distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
full: default: canonical stack in REFERENCE.md, using the order below.
- Very specific: line 15
<tool>: only that reference.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Bootstrap idempotently. Read only requested references/<tool>/README.md and linked guides. Hook copies are no-ops in plugins; bare repos need export-harness copies.
Profiles
- full default: canonical stack in REFERENCE.md, using the order below.
- minimal: toolchain, biome, quality gate, env validation, conventional commits.
- redpanda: full plus
references/redpanda/README.md, taxonomy,REDPANDA_KIT=1. <tool>: only that reference.
Full order
| Tool | Purpose |
toolchain | references/toolchain/: bun, TS 7 tsc/tsrs, destructive-command guards |
tanstack-intent | version-matched guidance/edit gates |
biome | Biome, Ultracite, auto-fix hook |
quality-gate | script, CI, Stop hook, bundle guard |
agent-config | AI_AGENT=1, output truncation |
react-compiler | Compiler, memoization check |
zustand | create<T>()(), useShallow, persist |
react-rules | raw HTML, TS escape, XSS, barrel bans |
env-validation | t3-env/zod, noProcessEnv |
conventional-commits | type(scope): description |
react-doctor | changed-diagnostic gate, Stop hook |
ci-pipeline | Actions, coverage, cache |
redpanda | registry workflow/taxonomy |
Runtime skills, not setup: /accessibility, /tanstack-router, /connect-query, /e2e-testing, /registry-workflow, /ux-copy. Optional slash-only infra: /setup-routines, /setup-atlassian-workflow.
Steps
- Confirm profile; for full, process the table sequentially and lazily.
- Set
REACT_RULES_BAN_USEEFFECT=1only for repos choosing strict effects. - Auto-setup safeguards in every consumer; honor the endpoint.
- Workflow skills already ship in the plugin; install nothing extra.
Verify
.claude/settings.jsonhas hooks, including TanStack Intent when packages exist;biome.jsoncandsrc/env.tsexist.- Scripts: lint, lint:fix, type:check, test, quality:gate.
.github/workflows/quality-gate.ymlexists; hooks executable.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

