Navigate ECC by checking its current files to find suitable skills, commands, and configuration options. Get focused guidance on installation, reset procedures, project setup, and troubleshooting duplicate installs, with concrete files and next steps to inspect.
Answer questions about ECC by reading the live repo surface — agents, skills, commands, hooks, rules, install profiles, and docs — instead of memory. Use when the user asks what ECC includes, how to install or reset it, which skill or command fits a task, or how project onboarding works.
Review the instructions the agent will receive before you install.
Use this skill when a user needs help understanding, navigating, installing, or choosing parts of ECC.
Use this skill when the user:
Answer from current files, not memory. ECC changes quickly, so hard-coded catalog counts, feature lists, and install instructions go stale.
When the ECC repository is available, inspect the relevant files before giving a concrete answer:
node scripts/ci/catalog.js --json
find skills -maxdepth 2 -name SKILL.md | sort
find commands -maxdepth 1 -name '*.md' | sort
find agents -maxdepth 1 -name '*.md' | sort
node scripts/install-plan.js --list-profiles
node scripts/install-plan.js --list-components --json
Use the smallest set of reads needed for the user's question.
README.md: install paths, uninstall/reset guidance, public positioning, FAQsAGENTS.md: contributor guidance and project structureagent.yaml: exported gitagent surface and command listcommands/: maintained slash-command compatibility shimsskills/*/SKILL.md: reusable workflows and domain playbooksagents/*.md: delegated subagent role promptsrules/: language and harness ruleshooks/README.md, hooks/hooks.json, scripts/hooks/: hook behavior and safety gatesmanifests/install-*.json: selective install modules, components, profiles, and target supportdocs/: harness guides, architecture notes, translated docs, release docsLead with the answer, then give the next action. Most users do not need a full catalog dump.
Good first response shape:
Avoid:
Give a short menu:
Point to README.md for install/reset and /project-init for project-specific onboarding.
For "what should I use for X?":
skills/, commands/, and agents/.Useful searches:
rg -n "<query>" skills commands agents docs
find skills -maxdepth 2 -name SKILL.md | sort
Use managed install paths:
node scripts/install-plan.js --list-profiles
node scripts/install-plan.js --profile minimal --target claude --json
node scripts/install-apply.js --profile minimal --target claude --dry-run
For specific skill installs:
node scripts/install-plan.js --skills <skill-id> --target claude --json
node scripts/install-apply.js --skills <skill-id> --target claude --dry-run
Warn users not to stack plugin installs and full manual/profile installs unless they intentionally want duplicate surfaces.
Use /project-init when the user wants ECC configured for a target repo. The expected sequence is:
CLAUDE.md and settings filesAsk for the target harness and install path first, then inspect:
.claude/, .cursor/, .codex/, .gemini/, .opencode/, .codebuddy/, .joycode/, or .qwen/hooks/hooks.jsonFor repo health, suggest:
npm run harness:audit -- --format text
npm run observability:ready
npm test
Use <skill-or-command>. It fits because <reason>.
Canonical file: <path>
Verify with: <command>
Next: <one concrete action>
Best matches:
- <path>: <why it matters>
- <path>: <why it matters>
Recommendation: <which one to use first and why>
Detected: <stack evidence>
Target: <harness>
Plan: <profile/modules/skills>
Dry run: <command>
Would change: <paths>
Needs approval before apply: <yes/no>
/project-init: stack-aware onboarding plan for a target repo/harness-audit: deterministic readiness scorecard/skill-health: skill quality review/skill-create: generate a new skill from local git history/security-scan: inspect Claude/OpenCode configuration securityNo reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Design and audit interfaces for Web, iOS, and Android using WCAG 2.2 accessibility guidance. Check screen-reader labels, keyboard navigation, contrast, and control sizes to identify barriers and guide implementation for people using assistive technology.
Investigate unreliable AI agents across 12 layers, including instructions, memory, tool execution, and display. Use code and logs to trace failures, rank findings by severity, and produce an ordered repair plan that prioritizes code changes.
Compare coding agents on tasks from your own codebase. Define success checks, run agents in separate Git working directories, and report pass rates, available API costs, completion time, and consistency across repeated trials.
Design and refine an AI agent’s available actions, tool inputs, and result formats. Define recovery steps for errors, manage the information kept in context, and evaluate changes through completion rates, retries, and cost per successful task.
Diagnose AI agent runs that fail repeatedly, loop through tools, or lose track of the task. Capture errors and environment details, test a focused recovery action, and produce a report explaining the evidence and outcome.
Diagnose failed AI agent runs by capturing errors, checking likely causes, and choosing small, reversible recovery actions. The workflow produces a structured report of the failure, recovery steps, and evidence, helping explain repeated retries or stalled progress.