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ECC/AGENTS.md
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5a2453e167 feat: add council-multi-model skill (heterogeneous Codex review) (#2281)
* feat: add council-multi-model skill (heterogeneous Codex review)

Rebased onto latest main to resolve the merge conflict (the branch had gone
DIRTY as main advanced). Trimmed to just the skill files (no top-level
README/AGENTS edits), mirroring the merged #2381. Previously reviewed
favorably by greptile/coderabbit/daltino.

* feat: add Entry B (independent parallel propose + aggregate, MoA-style) alongside Entry A (review)

Splits the skill into two entries depending on what already exists:
Entry A (unchanged) reviews an existing draft. New Entry B has every
voice (Claude x3 + Codex if available) answer the same question fully
independently and in parallel, then aggregates without collapsing
disagreement or blending incompatible approaches into one hybrid.
For the heaviest decisions the two chain: B first, then A's review
step on the aggregation -- with an explicit honesty caveat when Codex
already proposed in B and so cannot independently judge the result.

* feat: prefer Codex MCP tool over the SDK script when available

mcp__codex__codex is now the primary path for both Entry A's
heterogeneous review and Entry B's independent proposal -- zero relay,
talks directly to OpenAI's backend, no temp file or shell escaping
needed. The openai-codex SDK script becomes the fallback for sessions
without that MCP tool configured; behavior and guardrails (read-only,
verbatim quoting, explicit 'absent' labeling) are unchanged.

* fix: register council-multi-model install path

* docs: sync skill catalog count

* fix: publish council-multi-model skill

* fix: harden council multi-model fallback

* docs: sync remaining skill count

* fix: narrow multi-model council to bounded review

* fix: address council adapter review feedback

* fix(council-multi-model): enforce tool-less Codex review

* fix(council-multi-model): close Codex tool boundary

---------

Co-authored-by: haelyra <49814733+haelyra@users.noreply.github.com>
2026-08-11 16:30:04 -04:00

8.6 KiB

Everything Claude Code (ECC) — Agent Instructions

This is a production-ready AI coding plugin providing 68 specialized agents, 287 skills, 94 commands, and automated hook workflows for software development.

Version: 2.2.0

Core Principles

  1. Agent-First — Delegate to specialized agents for domain tasks
  2. Test-Driven — Write tests before implementation, 80%+ coverage required
  3. Security-First — Never compromise on security; validate all inputs
  4. Immutability — Always create new objects, never mutate existing ones
  5. Plan Before Execute — Plan complex features before writing code

Available Agents

Agent Purpose When to Use
planner Implementation planning Complex features, refactoring
architect System design and scalability Architectural decisions
tdd-guide Test-driven development New features, bug fixes
code-reviewer Code quality and maintainability After writing/modifying code
security-reviewer Vulnerability detection Before commits, sensitive code
spec-miner Brownfield spec extraction Onboarding brownfield projects to spec-driven development
build-error-resolver Fix build/type errors When build fails
e2e-runner End-to-end Playwright testing Critical user flows
refactor-cleaner Dead code cleanup Code maintenance
doc-updater Documentation and codemaps Updating docs
cpp-reviewer C/C++ code review C and C++ projects
cpp-build-resolver C/C++ build errors C and C++ build failures
fsharp-reviewer F# functional code review F# projects
docs-lookup Documentation lookup via Context7 API/docs questions
go-reviewer Go code review Go projects
go-build-resolver Go build errors Go build failures
kotlin-reviewer Kotlin code review Kotlin/Android/KMP projects
kotlin-build-resolver Kotlin/Gradle build errors Kotlin build failures
database-reviewer PostgreSQL/Supabase specialist Schema design, query optimization
python-reviewer Python code review Python projects
django-reviewer Django code review Django apps, DRF APIs, ORM, migrations
django-build-resolver Django build, migration, and setup errors Django startup, dependency, migration, collectstatic failures
java-reviewer Java and Spring Boot code review Java/Spring Boot projects
java-build-resolver Java/Maven/Gradle build errors Java build failures
loop-operator Autonomous loop execution Run loops safely, monitor stalls, intervene
harness-optimizer Harness config tuning Reliability, cost, throughput
rust-reviewer Rust code review Rust projects
rust-build-resolver Rust build errors Rust build failures
pytorch-build-resolver PyTorch runtime/CUDA/training errors PyTorch build/training failures
mle-reviewer Production ML pipeline review ML pipelines, evals, serving, monitoring, rollback
rag-pipeline-reviewer RAG pipeline review Retrieval quality, chunking, reranking, RAGAS evaluation coverage
typescript-reviewer TypeScript/JavaScript code review TypeScript/JavaScript projects

Agent Orchestration

Use agents proactively without user prompt:

  • Complex feature requests → planner
  • Code just written/modified → code-reviewer
  • Bug fix or new feature → tdd-guide
  • Architectural decision → architect
  • Security-sensitive code → security-reviewer
  • Brownfield project onboarding → spec-miner
  • Autonomous loops / loop monitoring → loop-operator
  • Harness config reliability and cost → harness-optimizer
  • RAG/retrieval pipeline changes → rag-pipeline-reviewer

Use parallel execution for independent operations — launch multiple agents simultaneously.

Security Guidelines

Before ANY commit:

  • No hardcoded secrets (API keys, passwords, tokens)
  • All user inputs validated
  • SQL injection prevention (parameterized queries)
  • XSS prevention (sanitized HTML)
  • CSRF protection enabled
  • Authentication/authorization verified
  • Rate limiting on all endpoints
  • Error messages don't leak sensitive data

Secret management: NEVER hardcode secrets. Use environment variables or a secret manager. Validate required secrets at startup. Rotate any exposed secrets immediately.

If security issue found: STOP → use security-reviewer agent → fix CRITICAL issues → rotate exposed secrets → review codebase for similar issues.

Coding Style

Immutability (CRITICAL): Always create new objects, never mutate. Return new copies with changes applied.

File organization: Many small files over few large ones. 200-400 lines typical, 800 max. Organize by feature/domain, not by type. High cohesion, low coupling.

Error handling: Handle errors at every level. Provide user-friendly messages in UI code. Log detailed context server-side. Never silently swallow errors.

Input validation: Validate all user input at system boundaries. Use schema-based validation. Fail fast with clear messages. Never trust external data.

Code quality checklist:

  • Functions small (<50 lines), files focused (<800 lines)
  • No deep nesting (>4 levels)
  • Proper error handling, no hardcoded values
  • Readable, well-named identifiers

Testing Requirements

Minimum coverage: 80%

Test types (all required):

  1. Unit tests — Individual functions, utilities, components
  2. Integration tests — API endpoints, database operations
  3. E2E tests — Critical user flows

TDD workflow (mandatory):

  1. Write test first (RED) — test should FAIL
  2. Write minimal implementation (GREEN) — test should PASS
  3. Refactor (IMPROVE) — verify coverage 80%+

Troubleshoot failures: check test isolation → verify mocks → fix implementation (not tests, unless tests are wrong).

Development Workflow

  1. Plan — Use planner agent, identify dependencies and risks, break into phases
  2. TDD — Use tdd-guide agent, write tests first, implement, refactor
  3. Review — Use code-reviewer agent immediately, address CRITICAL/HIGH issues
  4. Capture knowledge in the right place
    • Personal debugging notes, preferences, and temporary context → auto memory
    • Team/project knowledge (architecture decisions, API changes, runbooks) → the project's existing docs structure
    • If the current task already produces the relevant docs or code comments, do not duplicate the same information elsewhere
    • If there is no obvious project doc location, ask before creating a new top-level file
  5. Commit — Conventional commits format, comprehensive PR summaries

Workflow Surface Policy

  • skills/ is the canonical workflow surface.
  • New workflow contributions should land in skills/ first.
  • commands/ is a legacy slash-entry compatibility surface and should only be added or updated when a shim is still required for migration or cross-harness parity.

Git Workflow

Commit format: <type>: <description> — Types: feat, fix, refactor, docs, test, chore, perf, ci

PR workflow: Analyze full commit history → draft comprehensive summary → include test plan → push with -u flag.

Architecture Patterns

API response format: Consistent envelope with success indicator, data payload, error message, and pagination metadata.

Repository pattern: Encapsulate data access behind standard interface (findAll, findById, create, update, delete). Business logic depends on abstract interface, not storage mechanism.

Skeleton projects: Search for battle-tested templates, evaluate with parallel agents (security, extensibility, relevance), clone best match, iterate within proven structure.

Performance

Context management: Avoid last 20% of context window for large refactoring and multi-file features. Lower-sensitivity tasks (single edits, docs, simple fixes) tolerate higher utilization.

Build troubleshooting: Use build-error-resolver agent → analyze errors → fix incrementally → verify after each fix.

Project Structure

agents/          — 68 specialized subagents
skills/          — 287 workflow skills and domain knowledge
commands/        — 94 slash commands
hooks/           — Trigger-based automations
rules/           — Always-follow guidelines (common + per-language)
scripts/         — Cross-platform Node.js utilities
mcp-configs/     — 14 MCP server configurations
tests/           — Test suite

commands/ remains in the repo for compatibility, but the long-term direction is skills-first.

Success Metrics

  • All tests pass with 80%+ coverage
  • No security vulnerabilities
  • Code is readable and maintainable
  • Performance is acceptable
  • User requirements are met