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ecc-recipes

Map a described workflow to the right ECC command-GROUP with run-order and stop condition, and browse all command-group recipe families. Adds a family-grouping + run-order + when-to-stop layer on top of the flat command catalog. Advisory only. TRIGGER when the user says which commands for X, what command group runs X, show ECC recipes, list ECC pipelines, or how do I run a workflow with ECC. DO NOT TRIGGER when the user wants the task executed directly, wants a single-command deep doc (use ecc-guide), or wants a draft prompt rewritten (use prompt-optimizer).

Was ist ecc-recipes?

ecc-recipes is a Claude Code agent skill that map a described workflow to the right ECC command-GROUP with run-order and stop condition, and browse all command-group recipe families. Adds a family-grouping + run-order + when-to-stop layer on top of the flat command catalog. Advisory only. TRIGGER when the user says which commands for X, what command group runs X, show ECC recipes, list ECC pipelines, or how do I run a workflow with ECC. DO NOT TRIGGER when the user wants the task executed directly, wants a single-command deep doc (use ecc-guide), or wants a draft prompt rewritten (use prompt-optimizer).

Funktioniert mitClaude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/ecc-recipes

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Dokumentation

ECC Recipes

One entry point for "which group of ECC slash-commands runs my workflow, in what order, and when do I stop." Also browses every command-group recipe family.

Fills the gap between two existing skills:

  • ecc-guide — lists commands and where to read docs, but as a flat catalog.
  • prompt-optimizer — matches a task to components, but outputs a single prompt, not a multi-command group with run-order and stop condition.

This skill adds: family grouping + run-order + stop condition.

When to Activate

  • "Which command group do I run for ?"
  • "What's the command sequence to build an MVP / fix a defect / refactor?"
  • "Show me all ECC command-group recipes" (catalog mode)
  • "How many workflow pipelines does ECC have?"
  • User invokes /ecc-recipes with or without a description.

Do Not Use When

  • User wants the task done now — route to the actual command, don't describe it.
  • User wants deep docs for ONE command — use ecc-guide.
  • User wants a draft prompt rewritten — use prompt-optimizer.

Core Principle

Answer from current files, not memory. The command set changes; never hardcode counts or member lists. Read the live commands/ directory each run, then classify into families.

Live reads

Resolve the commands directory (first that exists), then list names:

for D in \
  "$HOME"/.claude/plugins/marketplaces/ecc/commands \
  "$HOME"/.claude/plugins/cache/ecc/ecc/*/commands \
  ./commands \
  ./.claude/commands \
  "$HOME"/.claude/commands; do
  [ -d "$D" ] && CMD_DIR="$D" && break
done
[ -z "${CMD_DIR:-}" ] && { echo "No ECC commands directory found."; return 1; }
find "$CMD_DIR" -maxdepth 1 -name '*.md' -exec basename {} .md \; | sort

Optionally read manifests/install-*.json if present for richer grouping. Use the smallest set of reads needed.

Family Classification (by prefix)

Group command names by leading prefix; map known singletons by hand. Families are derived live — the table below is the classification rule, not a frozen list.

Family prefixRecipe meaningTypical run-order
orch-*gated Research, Plan, TDD, Review, Commit per task typepick one orch-* by task kind; it runs its own internal phases
multi-*multi-model workflowmulti-plan then multi-execute then review (or multi-workflow end-to-end)
prp-*PRD to plan to implement to PR pipelineprp-prd then prp-plan then prp-implement then prp-commit then prp-pr
epic-*large multi-unit epic, parallelepic-decompose then epic-claim then epic-validate then epic-review then epic-unblock then epic-sync then epic-publish
loop-*managed autonomous loop and monitorloop-start <pattern> then watch with loop-status
gan-*generator and evaluator loopgan-build (code) or gan-design (UI); self-looping
*-build / *-review / *-testper-language CI triad<lang>-test (TDD) then <lang>-build (fix) then <lang>-review
hookify-*behavior-hook managementhookify then hookify-list then hookify-configure
learn / instinct-* / evolve / promote / prunecontinuous-learninglearn then instinct-status then evolve then promote
singletonssanta-loop, plan, plan-prd, pr, code-review, checkpoint, etc.standalone or glue between groups

Any command not matching a prefix rule → list it under singletons with its one-line description.

How It Works

1. Live-read command names from CMD_DIR.
2. Classify into families by prefix and a singleton map.
3. If a workflow description was given -> MATCH MODE.
   If none -> CATALOG MODE.
4. Advisory only: print the plan. Never run the matched commands.

Catalog mode (no description)

Output the family table: each family, member count, members, one-line meaning, typical run-order. End with the total command count and a prompt to describe a workflow for a matched recipe.

Match mode (description given)

  1. Restate the workflow in one sentence.
  2. Pick the best 1-2 families; say WHY in one line each.
  3. Run-order block — exact command sequence for the matched family.
  4. Stop condition — always explicit (max-runs, completion-signal, review-passes, or single-shot). For autonomous loops, warn about subscription burn and recommend a backstop bound.
  5. Where to read — the commands/<name>.md path plus /ecc-guide <name>.

Output Template (match mode)

Workflow: <one-sentence restatement>

Best fit: <family> — <why>
(Alt: <family> — <why>)

Run-order:
  /<cmd1>   # job
  /<cmd2>   # job
  /<cmd3>   # job
  STOP when: <condition>
  WARNING (autonomous loops only): an unbounded loop burns subscription/credits —
  add a max-iteration or max-cost backstop alongside the completion signal.

Read full docs:
  commands/<cmd1>.md   (or: /ecc-guide <cmd1>)

Examples

Catalog: /ecc-recipes → prints the family table and total count.

Match: /ecc-recipes plan a whole app upfront then auto-build with adversarial review until done → Best fit: loop-* (autonomous) wrapping gan-* or santa-loop (adversarial). Run-order: plan-prd then loop-start rfc-dag --mode safe then monitor loop-status; STOP when all units pass review N consecutive times (add a max-iteration backstop to bound burn).

Match: /ecc-recipes fix a bug in my Go service → Best fit: orch-fix-defect (reproduce, fix, review, commit). Alt: go-test then go-build then go-review. STOP: regression test green and review pass.

Non-Goals

  • Not an executor — advisory only.
  • Not per-command deep docs — that's ecc-guide.
  • Not prompt rewriting — that's prompt-optimizer.
  • Never hardcode command counts or member lists — always live-read.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

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