start
Skill22 starsChanged 5 months agoMITView on GitHub
Guided, jargon-free starting point for people with no schema and no database yet — a short 7-question wizard that turns "I want to build an app" into a concrete engine recommendation and a first data model. Zero artifacts required. Use when the user has nothing to audit, asks how to begin, says they're not technical, or doesn't know what database or schema they need.
130 other projects use a version of this.
Adopted by
Most recently taken up by
- ansvisor/ansvisortheir own version, first seen Nov 8, 2026
- dsifry/metaswarmtheir own version, first seen Nov 8, 2026
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tooltheir own version, first seen Nov 8, 2026
- paulocsb/worldcup-fifa-pooltheir own version, first seen Nov 8, 2026
- srinator22/New-Projecttheir own version, first seen Nov 8, 2026
- Memolok/Claude-plugintheir own version, first seen Nov 6, 2026
Used with
Projects with it also use setup-engine, team-audio and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
CoralGameSkillsetup-engine
Configure the project's game engine and version. Pins the engine in CLAUDE.md, detects knowledge gaps, and populates engine reference docs via WebSearch when the version is beyond the LLM's training data.
Also in 13 projects that use this
- CoralGameSkill
team-audio
Orchestrate audio team: audio-director + sound-designer + technical-artist + gameplay-programmer for full audio pipeline from direction to implementation.
Also in 13 projects that use this
lilangMaxSkillcreate-stories
Break a single epic into implementable story files. Reads the epic, its GDD, governing ADRs, and control manifest. Each story embeds its GDD requirement TR-ID, ADR guidance, acceptance criteria, story type, and test evidence path. Run after /create-epics for each epic.
Also in 11 projects that use this
- lilangMaxSkill
story-done
End-of-story completion review. Reads the story file, verifies each acceptance criterion against the implementation, checks for GDD/ADR deviations, prompts code review, updates story status to Complete, and surfaces the next ready story from the sprint.
Also in 11 projects that use this
- +5 more from CoralGame
- +3 more from lilangMax
Other versions130 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 130
- anthropics/knowledge-work-plugins★ 35ksame name
- Donchitos/Claude-Code-Game-Studios★ 27ksame name
- openai/plugins★ 7.8ksame name
- SterlingChin/marvin-template★ 1ksame name
- educlopez/ui-craft★ 441same name
- ai-search-guru/getcito-worlds-first-open-source-aio-aeo-or-geo-tool★ 432same name
- dsifry/metaswarm★ 426same name
- pixel-cellar/Claude-Code-Game-Studios★ 324same name
- ansvisor/ansvisor★ 233same name
- alexeykrol/claude-code-starter★ 194same name
120 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository36 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- auditSkill
- checklistSkill
- db-antipatternsSkill
- db-concurrencySkill
- db-connection-poolingSkill
- db-constraintsSkill
- db-defaults-generatedSkill
- db-engine-selectionSkill
- db-index-hygieneSkill
- db-indexingSkill
- db-keysSkill
- db-migration-safetySkill
- db-multitenancySkill
- db-namingSkill
- db-normalizationSkill
- db-orchestratorSkill
- db-partitioning-shardingSkill
- db-platform-fitSkill
- db-query-patternsSkill
- db-referential-integritySkill
- db-replicas-viewsSkill
- db-security-accessSkill
- db-specialized-fitSkill
- db-storage-bloatSkill
- db-temporal-historySkill
- db-types-precisionSkill
- designSkill
- explainSkill
- fixSkill
- introspectSkill
- migrateSkill
- nextSkill
- scoreSkill
- seedSkill
- stack-detectSkill
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 2 are distinctive, and 1 is very specific to this project.
0
Common
Most of the 117 edited versions we read keep these.
2
Distinctive
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
- Very specific: line 16
Follow the 7-question wizard in references/design-wizard.md (the canonical question set and the mapping from answers → paradigm/engine).
- Distinctive: line 31
Never fabricate prices, performance numbers, or row counts.
- Distinctive: line 32
If an answer is missing, ask — don't assume.
“Common” is measured: kept by at least 6 in 10 of the 117 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
<!-- Copyright (c) 2026 Enrique Rocha (@soyenriquerocha) · tododeia.com · id er-f37b7121 -->/claude-db:start
The front door for someone with zero artifacts — no schema, no migrations, no database. It asks a short, plain-language wizard and ends with a concrete recommendation. No jargon: no "normalization", "cardinality", or "partition key" in the questions.
$ARGUMENTS = an optional one-line description. If present, pre-fill what you can and skip questions already answered.
How to run it
Follow the 7-question wizard in references/design-wizard.md (the canonical question set and the mapping from answers → paradigm/engine). Ask the questions conversationally, one cluster at a time, in plain words — roughly:
- What are you building, in one sentence?
- What are the main things you'll store (people, orders, messages, posts…)?
- How do those things relate to each other?
- What will you do most — look one thing up, list/search many, or crunch numbers over lots of rows?
- How much data and how many users, roughly (a hobby project, a startup, or huge)?
- Any hard rules — must never lose a record, must be fast above all, has to handle money or personal data?
- What are you comfortable running or paying for (managed/serverless vs self-hosted)?
What to produce
- A plain-language recommendation: which database to start with, in one sentence, and why — defaulting to the boring, safe choice (usually Postgres) unless an answer genuinely points elsewhere.
- A starter data model for the main things named, with the obvious relationships and the few constraints/keys that keep data clean — described in words, with a simple diagram.
- A clear next step: "Save this as your schema, then run
/claude-db:auditto score it" or "Run/claude-db:designfor the full technical layer."
Honesty
- Never fabricate prices, performance numbers, or row counts; describe trade-offs in plain qualitative terms.
- If an answer is missing, ask — don't assume. Respond in the user's language (EN/ES).
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.