engineering-skills
CLAUDE.md0 starsChanged 5 months agoMITView on GitHub
A collection of engineering skills for AI coding agents, packaged as a Claude Code plugin. This file guides work on this repository itself (authoring and maintaining skills). - Define: idea-shaping, product-brief, spec-first - Plan: work-planning, product-grooming - Build: incremental-delivery, test-first, ux-design, mobile-patterns, i18n-l10n, context-curation, source-first, ui-craft, micro-interactions, accessibility, react-patterns, interface-design, design-handoff, resilience, data-modeling, caching-strategy, llm-feature-engineering - Verify: browser-checks, e2e-testing, fault-recovery - Review: review-gate, simplify, hardening, perf-budget, dependency-hygiene, version-upgrade - Ship: git-flow, pipeline-ops, migration-path, decision-docs, technical-writing, launch-readiness - Operate: observability, incident-response,…
In this repository68 other files it gives its agents.
- AGENTS.mdAGENTS.md
- .github/copilot-instructions.mdCopilot instructions
- .cursor/rules/engineering-skills.mdcCursor rule
- marketing-routerSkill
- accessibilitySkill
- agent-guardrailsSkill
- agent-memorySkill
- agent-verificationSkill
- autonomous-loopsSkill
- browser-checksSkill
- caching-strategySkill
- context-curationSkill
- contract-testingSkill
- data-modelingSkill
- decision-docsSkill
- dependency-hygieneSkill
- design-handoffSkill
- e2e-testingSkill
- experimentationSkill
- fault-recoverySkill
- feature-flagsSkill
- finops-budgetSkill
- git-flowSkill
- hardeningSkill
- i18n-l10nSkill
- idea-shapingSkill
- incident-responseSkill
- incremental-deliverySkill
- interface-designSkill
- launch-campaignSkill
- launch-readinessSkill
- llm-feature-engineeringSkill
- long-running-agentsSkill
- community-engagementSkill
- content-marketingSkill
- email-nurtureSkill
- growth-strategySkill
- paid-adsSkill
- referral-loopSkill
- seo-growthSkill
- social-distributionSkill
- micro-interactionsSkill
- migration-pathSkill
- mobile-patternsSkill
- observabilitySkill
- orchestrated-deliverySkill
- parallel-subagentsSkill
- perf-budgetSkill
- pipeline-opsSkill
- product-briefSkill
- product-discoverySkill
- product-groomingSkill
- react-patternsSkill
- resilienceSkill
- review-gateSkill
- simplifySkill
- skill-creatorSkill
- skill-harvestSkill
- skill-routerSkill
- source-firstSkill
- The first 60 shown.
The file
We split this CLAUDE.md into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
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 40
Every skill has: overview, When to Use, Process, Common Rationalizations, Red Flags, Verification.
- Very specific: line 47
Every SKILL.md has valid YAML frontmatter with name and description.
- Distinctive: line 53
Always: follow the skill-anatomy format for new or edited skills.
- Distinctive: line 54
Never: add a skill that's vague advice instead of an actionable process.
≈ “Common” is an estimate: at least 1 in 5 of the 26,980 CLAUDE.md 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
engineering-skills
A collection of engineering skills for AI coding agents, packaged as a Claude Code plugin. This file guides work on this repository itself (authoring and maintaining skills).
Structure
skills/ → One SKILL.md per skill (marketing under skills/marketing/)
agents/sdlc/ → SDLC personas (marketing under agents/marketing/)
marketing/ → Marketing team guide, router (SKILL.md), references
prompts/ → Copy-paste agent prompts + skill-loading instructions
commands/ → Slash commands (/spec, /plan, /build, /test, /review, /ship)
hooks/ → Session lifecycle hooks (guardrails + skill-router injected on session start)
references/ → Engineering checklists (testing, performance, security, accessibility)
docs/ → Getting-started and skill-authoring guides
.claude-plugin/ → Plugin + marketplace manifestsSkills by phase
- Define: idea-shaping, product-brief, spec-first
- Plan: work-planning, product-grooming
- Build: incremental-delivery, test-first, ux-design, mobile-patterns, i18n-l10n, context-curation, source-first, ui-craft, micro-interactions, accessibility, react-patterns, interface-design, design-handoff, resilience, data-modeling, caching-strategy, llm-feature-engineering
- Verify: browser-checks, e2e-testing, fault-recovery
- Review: review-gate, simplify, hardening, perf-budget, dependency-hygiene, version-upgrade
- Ship: git-flow, pipeline-ops, migration-path, decision-docs, technical-writing, launch-readiness
- Operate: observability, incident-response, finops-budget
- Grow:
skills/marketing/— growth-strategy, content-marketing, social-distribution, seo-growth, community-engagement (team guide:marketing/) - Meta: agent-guardrails (always on), skill-router, skill-creator
Conventions
- A skill lives in
skills/<name>/SKILL.md; the directory name equals the frontmattername. - Frontmatter has
nameanddescription; the description says what the skill does, then when to use it. - Every skill has: overview, When to Use, Process, Common Rationalizations, Red Flags, Verification.
- Supporting files only when a section truly exceeds ~100 lines; otherwise fold it in.
- Link related skills with
[[name]]. Don't duplicate content across skills — reference instead. - Full format spec: docs/skill-anatomy.md.
Validating a change
- Every
SKILL.mdhas valid YAML frontmatter withnameanddescription. - Each directory name matches its skill's
name. - Plugin manifests in
.claude-plugin/remain valid JSON.
Boundaries
- Always follow the skill-anatomy format for new or edited skills.
- Never add a skill that's vague advice instead of an actionable process.
- Never duplicate prose between skills — link to the other skill.
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.

