Jeecg System
jeecgboot/skills
JeecgBoot 系统主数据查询与管理。Use when user asks to query/create/manage system master data, or says "查询角色", "查询用户", "查询部门", "查询字典", "创建字典", "创建角色", "查岗位", "查职务", "查租户", "查数据源", "查定时任务", "系统主数据", "query…
Data leadership advisor on data strategy, governance, quality, and platform decisions.
Install Chief Data Officer Advisor
$ npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install borghei/Claude-Skills chief-data-officer-advisor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/c-level-advisor/chief-data-officer-advisor .claude/skills/chief-data-officer-advisor && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "chief-data-officer-advisor" agent skill from https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-data-officer-advisor into .claude/skills/chief-data-officer-advisor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chief-data-officer-advisor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-data-officer-advisorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install borghei/Claude-Skills chief-data-officer-advisor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/c-level-advisor/chief-data-officer-advisor .agents/skills/chief-data-officer-advisor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "chief-data-officer-advisor" agent skill from https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-data-officer-advisor into .agents/skills/chief-data-officer-advisor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chief-data-officer-advisor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install borghei/Claude-Skills chief-data-officer-advisor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/c-level-advisor/chief-data-officer-advisor .cursor/skills/chief-data-officer-advisor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "chief-data-officer-advisor" agent skill from https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-data-officer-advisor into .cursor/skills/chief-data-officer-advisor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chief-data-officer-advisor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/borghei/Claude-Skills.git --path c-level-advisor/chief-data-officer-advisor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install borghei/Claude-Skills chief-data-officer-advisor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/c-level-advisor/chief-data-officer-advisor .gemini/skills/chief-data-officer-advisor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "chief-data-officer-advisor" agent skill from https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-data-officer-advisor into .gemini/skills/chief-data-officer-advisor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chief-data-officer-advisor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install borghei/Claude-Skills chief-data-officer-advisorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/c-level-advisor/chief-data-officer-advisor .github/skills/chief-data-officer-advisor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "chief-data-officer-advisor" agent skill from https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-data-officer-advisor into .github/skills/chief-data-officer-advisor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chief-data-officer-advisor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install borghei/Claude-Skills chief-data-officer-advisor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/borghei/Claude-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/c-level-advisor/chief-data-officer-advisor .opencode/skills/chief-data-officer-advisor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "chief-data-officer-advisor" agent skill from https://github.com/borghei/Claude-Skills/tree/main/c-level-advisor/chief-data-officer-advisor into .opencode/skills/chief-data-officer-advisor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "chief-data-officer-advisor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
chief-data-officer-advisor- GitHub stars
- 886
- Token cost
- ~2.2k tokens
- SKILL.md length
- 1,012 words
- Files
- 7 (incl. scripts, references)
- Skills in repo
- 354
- Repo updated
- First seen
- Licence
- MIT
At a glance
Data leadership advisor on data strategy, governance, quality, and platform decisions.
- Works in 3 steps: Pull current state across the 5… → Run data_maturity_assessor.py against… → Translate prioritized gaps into a…
- Defining a data strategy
- SKILL.md covers When to use this skill, Inputs the advisor expects, Workflows and Decision frameworks, plus 5 more sections
- Runs Python scripts from its folder; calls python3
What it does
Chief Data Officer Advisor is an agent skill from borghei/Claude-Skills. Data leadership advisor on data strategy, governance, quality, and platform decisions. Use when defining a data strategy, scoring data maturity, auditing data governance, evaluating a data platform, or designing the data org.
Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts and reference files (for example `references/data-governance-and-quality.md`, `references/data-strategy-framework.md` and `references/data-team-and-platform.md`).
It sits in Data & Analytics, covering Data governance. The repository describes itself as: 385 AI skills, 77 expert agents, and 900 stdlib Python tools for every team: engineering, PM, marketing, C-level, compliance, business ops, research, and a LinkedIn toolkit… The licence is MIT.
When your agent uses it
- Defining a data strategy
- Scoring data maturity
- Auditing data governance
- Evaluating a data platform
Example prompts
- “/chief-data-officer-advisor”
Requirements
- Python 3
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Pull current state across the 5 dimensions (strategy, governance, quality, platform, people).
- Run data_maturity_assessor.py against the populated JSON.
- Translate prioritized gaps into a quarterly OKR for the data org.
What it can do on your machine
Read from SKILL.md and the folder at commit 4a698e8. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Chief Data Officer Advisor loads about 2.2k tokens when it runs, and up to ~9.8k if it reads all its reference files. Until then it costs about 63 tokens; SKILL.md has 1,012 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from borghei/Claude-Skills at commit 4a698e8, republished under its MIT licence (© borghei). 1,012 words, ~2,197 tokens.
Download SKILL.mdSave it as
.claude/skills/chief-data-officer-advisor/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- chief-data-officer-advisor
- description
- Data leadership advisor on data strategy, governance, quality, and platform decisions. Use when defining a data strategy, scoring data maturity, auditing data governance, evaluating a data platform, or designing the data org.
- license
- MIT + Commons Clause
- metadata.version
- 1.0.0
- metadata.author
- borghei
- metadata.category
- executive-leadership
- metadata.domain
- c-level-advisor
- metadata.updated
- 2026-05-27
- metadata.tags
- data, governance, quality, platform, monetization, dmbok, dama
Chief Data Officer Advisor
The agent acts as a fractional Chief Data Officer, providing data strategy and operating-model guidance grounded in DAMA-DMBOK, modern data-platform patterns, and regulated-industry expectations (GDPR, HIPAA, sector data governance regimes).
When to use this skill
- Defining or refreshing the data strategy for the next 12–24 months
- Designing the data operating model: central, federated, mesh, hybrid
- Building a data governance program that holds up to internal + regulator review
- Scoring data maturity across strategy, governance, quality, platform, and people
- Auditing the data quality program (use jointly with
engineering/data-quality-auditor) - Evaluating the data platform stack (warehouse, lake, lakehouse, governance)
- Building the case for data monetization: products, services, internal apps
- Preparing the data section of the board deck (assets, risks, returns, asks)
Inputs the advisor expects
- Company stage, sector, regulatory exposure (e.g., financial services, healthcare, public sector)
- Critical data domains (customer, product, transaction, employee, regulatory)
- Current data platform (warehouse, lake, ingestion, transformation, BI, governance, ML/AI)
- Data team composition (engineering, governance, analytics, stewardship, science)
- Existing policies (data classification, retention, residency, access)
- Spend posture: total data spend (people + platform + tooling), trailing year + plan
- Top frictions: stakeholders, breached SLAs, incidents, audit findings
Workflows
Workflow 1 — Score data maturity
- Pull current state across the 5 dimensions (strategy, governance, quality, platform, people).
- Run
data_maturity_assessor.pyagainst the populated JSON. - Translate prioritized gaps into a quarterly OKR for the data org.
python3 chief-data-officer-advisor/scripts/data_maturity_assessor.py \
--input company_data_state.json --format markdownWorkflow 2 — Audit the data governance program
- Inventory domains, policies, controls, owners, evidence.
- Run
data_governance_audit.pyto score against a DAMA-DMBOK-aligned control set. - Generate the remediation plan with owners and due dates.
python3 chief-data-officer-advisor/scripts/data_governance_audit.py \
--input governance_state.json --format markdownWorkflow 3 — Evaluate platform decisions
- Capture current platform footprint and proposed alternatives.
- Run
data_platform_evaluator.pyto compare against weighted criteria (TCO, time-to-value, openness, governance fit, AI readiness). - Use output to build the architecture decision record (ADR) and CFO submission.
python3 chief-data-officer-advisor/scripts/data_platform_evaluator.py \
--input platform_eval.json --format markdownDecision frameworks
Centralized vs federated vs data mesh
| Pattern | When it fits | Risk |
|---|---|---|
| Centralized platform team | Early maturity, small org, regulated industry | Bottleneck on the center |
| Federated (domain-aligned data teams) | Org with strong BU autonomy and consistent platform standards | Coordination overhead |
| Data mesh | Mature org, true domain ownership of data products, strong platform-as-product | Often misapplied; rarely the right call before ~500 engineers |
| Hub-and-spoke hybrid | Default for most ≥ Series C orgs | Requires clear standards from the hub |
The advisor will default to hub-and-spoke: a central platform + governance group (the hub) sets standards; domain teams (the spokes) own data products and quality for their domain.
Warehouse vs lake vs lakehouse
| Pattern | When it fits | When it breaks |
|---|---|---|
| Warehouse-first (Snowflake / BigQuery / Redshift) | Structured analytics is the primary use case | Heavy unstructured / ML training workloads |
| Lake-first (object store + open table format) | High volume of semi/unstructured data; ML training | BI users want fast SQL with strong governance |
| Lakehouse (Databricks / Iceberg + Snowflake) | Want both, willing to invest in the integration | Complexity; tool sprawl |
| Best-of-breed lake + warehouse | Strong reasons each domain needs its own | Data sync + cost duplication |
Start from use cases, not architecture. If 80% of value is BI on structured data, start warehouse-first. If 80% is ML training + cheap retention, start lake-first. Most companies eventually run both.
Build vs buy
Per capability, not company-wide.
| Capability | Default |
|---|---|
| Warehouse | Buy (Snowflake, BigQuery, Redshift, Synapse) |
| Lake storage | Buy (S3, GCS, ADLS) |
| Open table format | Open source (Iceberg, Delta, Hudi) |
| Ingestion | Buy for typical (Fivetran, Airbyte); build for proprietary sources |
| Transformation | Open source orchestration + SQL (dbt) |
| Reverse ETL | Buy (Hightouch, Census) |
| BI | Buy (Looker, Tableau, Mode, Hex) |
| Catalog / governance | Buy or open source; this is where lock-in hurts most |
| Quality | Open source (Great Expectations, Soda) + your wrapper |
| Lineage | Open source (OpenLineage) + buy where catalog includes it |
Common engagements
Show full SKILL.md (412 more words)Show less
"Help me build the case for centralizing data"
- Inventory the current spend, headcount, tooling, BU-by-BU.
- Identify the duplication: same source ingested 4 times, 6 BI tools, 12 quality frameworks.
- Quantify the TCO and time-to-insight gap vs a consolidated platform.
- Stage the migration: don't try to centralize everything in 6 months.
"Our data governance is failing audits"
- Pull the audit findings and root cause each (people, process, evidence).
- Run
data_governance_audit.pyto score against the standard control set. - Identify the top 5 controls to fix; assign owners and due dates.
- Stand up a quarterly internal audit before the next external audit.
"We need a chief data officer — am I one?"
- Map your scope today (platform, governance, analytics, science, monetization).
- Compare against the four flavors of CDO (architect, governor, monetizer, defensive).
- Be honest about which one your company actually needs.
- If you don't have full board access, you're not a CDO yet; you're a head of data.
Anti-patterns to avoid
- Data strategy that doesn't tie to a business outcome. "Be a data-driven company" is not a strategy.
- Catalog-as-policy. A catalog with no enforcement teeth is shelfware. Tie classifications to access controls, not just to documentation.
- Quality as one team's problem. Quality is owned by the domain that produces the data; the platform team provides the tooling.
- Replatforming as a strategy. "We're moving from Redshift to Snowflake" is a tactic, not a strategy.
- The 4-year data lake. If you can't ship value in 6 months, you've over-scoped.
- Hiring a CDO with no platform partner. Without a counterpart CTO or head of data platform, the CDO becomes a policy person no one listens to.
- Mistaking dashboards for data products. A dashboard with no SLA and no owner is not a product.
References
references/data-strategy-framework.md— strategy framing, target operating model, monetizationreferences/data-governance-and-quality.md— DAMA-DMBOK alignment, governance bodies, quality SLAsreferences/data-team-and-platform.md— org design, role definitions, platform stack patterns
Related skills
c-level-advisor/cto-advisor— for the broader tech platform decisionsc-level-advisor/ciso-advisor— for data classification and security controlsc-level-advisor/chief-ai-officer-advisor— for the AI ↔ data interfaceengineering/data-quality-auditor— for the deep DQ implementationengineering/senior-data-engineer— for pipeline implementationra-qm-team/gdpr-dsgvo-expert— for personal data governance under GDPR
Output expectations
When the advisor runs, you should walk away with:
- A clear point of view (no "it depends" without a decision criterion)
- 2–4 concrete next actions with owners and timelines
- Open questions that materially change the recommendation
- References to scripts and reference docs that deepen the analysis
© borghei, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts, references) in c-level-advisor/chief-data-officer-advisor of borghei/Claude-Skills.
- SKILL.md
- references/data-governance-and-quality.md
- references/data-strategy-framework.md
- references/data-team-and-platform.md
- scripts/data_governance_audit.py
- scripts/data_maturity_assessor.py
- scripts/data_platform_evaluator.py
Open the folder on GitHubat commit 4a698e8
Compare with similar skills
Chief Data Officer Advisor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Chief Data Officer Advisor this skillborghei/Claude-Skills | 886 | — | ~2.2k | Automated safety check: Pass | MIT | |
| Jeecg Systemjeecgboot/skills | 239 | — | ~3.2k | Automated safety check: Pass | Apache-2.0 | |
| Openalgo Chart Indicatormarketcalls/openalgo-charts | 144 | — | ~3.4k | Automated safety check: Notes | Apache-2.0 | |
| Data Quality Frameworkswshobson/agents | 40k | 11 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Research Data Feasibility and Leakage ChecksLight0305/Light-skills | 640 | — | ~4.9k | Automated safety check: Pass | MIT | |
| Annotating Task Lineageastronomer/agents | 451 | — | ~2.8k | Automated safety check: Pass | Apache-2.0 |
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Questions about Chief Data Officer Advisor
What does Chief Data Officer Advisor do?
Data leadership advisor on data strategy, governance, quality, and platform decisions. Chief Data Officer Advisor is an agent skill from borghei/Claude-Skills. Data leadership advisor on data strategy, governance, quality, and platform decisions.
When should I use Chief Data Officer Advisor?
Chief Data Officer Advisor fits situations like: defining a data strategy; scoring data maturity; auditing data governance; evaluating a data platform.
How do I install Chief Data Officer Advisor in Claude Code?
Run `npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a claude-code`. Or copy the skill folder (c-level-advisor/chief-data-officer-advisor in borghei/Claude-Skills) into .claude/skills/chief-data-officer-advisor in your project. Claude Code loads it when a task matches its description.
How do I install Chief Data Officer Advisor in Codex?
Run `npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a codex`. Or copy the skill folder (c-level-advisor/chief-data-officer-advisor in borghei/Claude-Skills) into .agents/skills/chief-data-officer-advisor in your project. Codex loads it when a task matches its description.
Can I use Chief Data Officer Advisor in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add borghei/Claude-Skills --skill chief-data-officer-advisor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chief-data-officer-advisor, .gemini/skills/chief-data-officer-advisor, .github/skills/chief-data-officer-advisor and .opencode/skills/chief-data-officer-advisor in your project.
What does Chief Data Officer Advisor need to run?
Going by SKILL.md and its folder, Chief Data Officer Advisor needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Chief Data Officer Advisor access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Chief Data Officer Advisor safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Chief Data Officer Advisor use?
Chief Data Officer Advisor is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Chief Data Officer Advisor use?
About 2.2k tokens (SKILL.md is roughly 8.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.6k tokens, read only when the agent opens those files.
What are the alternatives to Chief Data Officer Advisor?
Skills that share tags, products or a category with Chief Data Officer Advisor: Jeecg System (jeecgboot/skills, 239 stars), Openalgo Chart Indicator (marketcalls/openalgo-charts, 144 stars), Data Quality Frameworks (wshobson/agents, 40k stars) and Research Data Feasibility and Leakage Checks (Light0305/Light-skills, 640 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Chief Data Officer Advisor?
borghei (a GitHub user) maintains it in borghei/Claude-Skills, which has 886 GitHub stars. The repository holds 354 skills in this directory. The repository was last updated on October 7, 2026.
Source: borghei/Claude-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.