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Install and use the Everything Claude Code (ECC) agent harness assets in this project. Use for ECC hooks, skills, plugins, commands, and agents, and for refreshing the vendored ECC snapshot.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | ecc |
| description | Install and use the Everything Claude Code (ECC) agent harness assets in this project. Use for ECC hooks, skills, plugins, commands, and agents, and for refreshing the vendored ECC snapshot. |
This project integrates selected assets from affaan-m/ECC for OpenAI Codex.
Only these upstream directories are selected:
hooks/skills/plugins/commands/agents/The synchronized snapshot belongs under .codex/ecc/upstream/. Do not copy unrelated ECC configuration into the project root.
Run:
bash .codex/ecc/install-ecc.sh
The installer performs a sparse checkout of the upstream main branch and atomically replaces the selected snapshot. It records the source commit in .codex/ecc/ECC_COMMIT.
.codex/ecc/upstream/skills/ before applying an ECC workflow.Upstream: https://github.com/affaan-m/ECC, branch main.
Profile and explore a dataset to understand its shape, quality, and patterns. Use when encountering a new table or file, checking null rates and column distributions, spotting data quality issues like duplicates or suspicious values, or deciding which dimensions and metrics to analyze.
QA an analysis before sharing -- methodology, accuracy, and bias checks. Use when reviewing an analysis before a stakeholder presentation, spot-checking calculations and aggregation logic, verifying a SQL query's results look right, or assessing whether conclusions are actually supported by the data.
Write optimized SQL for your dialect with best practices. Use when translating a natural-language data need into SQL, building a multi-CTE query with joins and aggregations, optimizing a query against a large partitioned table, or getting dialect-specific syntax for Snowflake, BigQuery, Postgres, etc.
Apply statistical methods including descriptive stats, trend analysis, outlier detection, and hypothesis testing. Use when analyzing distributions, testing for significance, detecting anomalies, computing correlations, or interpreting statistical results.
Generate or improve a company-specific data analysis skill by extracting tribal knowledge from analysts. BOOTSTRAP MODE - Triggers: "Create a data context skill", "Set up data analysis for our warehouse", "Help me create a skill for our database", "Generate a data skill for [company]" → Discovers schemas, asks key questions, generates initial skill with reference files ITERATION MODE - Triggers: "Add context about [domain]", "The skill needs more info about [topic]", "Update the data skill with [metrics/tables/terminology]", "Improve the [domain] reference" → Loads existing skill, asks targeted questions, appends/updates reference files Use when data analysts want Claude to understand their company's specific data warehouse, terminology, metrics definitions, and common query patterns.
Build an interactive HTML dashboard with charts, filters, and tables. Use when creating an executive overview with KPI cards, turning query results into a shareable self-contained report, building a team monitoring snapshot, or needing multiple charts with filters in one browser-openable file.