Name: chief-data-officer-advisor
Rating: 69.6 (1 reviews)
Author: alirezarezvani

chief-data-officer-advisor

Chief Data Officer advisory for startups: AI training data rights and consent provenance, data product strategy (warehouse vs lakehouse vs mesh, build-vs-buy), B2B customer-data-as-asset valuation and M&A readiness, data team org evolution. Use when deciding whether to train models on customer data, choosing data architecture, valuing data for fundraising or M&A, sequencing data hires, or when user mentions CDO, chief data officer, data strategy, data mesh, lakehouse, training data, data product, data monetization, or customer data asset. NOT a tactical data engineering skill — strategic decisions only.

Quality

85%

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The canonical home for this skill is chief-data-officer-advisor in alirezarezvani/claude-skills

Quality

Content

75%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A well-organized strategic skill body that leads with four crisp decisions, backs them with concrete tables, thresholds, and sequenced workflows, and appropriately defers detail to references. Its main weakness is that the referenced scripts and reference files are not actually bundled, which undercuts executability and navigation.

Suggestions

Bundle the referenced scripts/ and references/ files so the documented commands and 'See references/...' pointers resolve to real files.

De-duplicate the Quick Start commands that recur verbatim inside each Workflow, or have Workflows reference Quick Start rather than re-listing them.

Add an explicit validate/retry checkpoint to Workflow 1's batch audit (e.g., re-run the audit after remediation to confirm MITIGATE items move to GO) to satisfy the batch-operation feedback-loop expectation.

Dimension	Reasoning	Score
Conciseness	Dense and decision-oriented with no padding of basic concepts, using compact tables for the origin×consent×use-case, build-vs-buy, and stage-to-role matrices; minor redundancy exists where the Keywords list re-treads description triggers and Quick Start commands recur in the Workflows.	4 / 5
Actionability	Gives concrete CLI invocations ('python scripts/ai_training_data_audit.py sources.json'), named tools (Fivetran/Airbyte/dbt/Tecton), and specific numeric thresholds (k-anonymity ≥ 5, 1.2x–2x ARR uplift); the gap is that the referenced scripts/ and references/ files are not bundled, so the commands are not executable as-is.	4 / 5
Workflow Clarity	Four workflows each carry a goal, time estimate, numbered steps, and cross-checks to adjacent skills, with outcome branching in Workflow 1 (MITIGATE→remediation, NO-GO→document); it lacks a strict validate→retry feedback loop, so it sits just below the top anchor.	4 / 5
Progressive Disclosure	Clean overview structure with clearly signaled one-level-deep pointers ('See references/... for ...') and a dedicated References section; however the referenced references/.md and scripts/.py files are absent from the bundle, leaving navigation incomplete rather than merely having minor gaps.	4 / 5
	Total	16 / 20 Passed

Description

96%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong, well-structured description that concretely names four CDO decision areas, supplies explicit 'Use when' triggers with natural synonyms, and bounds scope with a NOT clause. Its only weakness is topical overlap with sibling c-level advisors on architecture, valuation, and contractual matters.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete capability areas with sub-detail — 'AI training data rights and consent provenance', 'data product strategy (warehouse vs lakehouse vs mesh, build-vs-buy)', 'B2B customer-data-as-asset valuation and M&A readiness', 'data team org evolution' — giving comprehensive coverage of the CDO decision space.	5 / 5
Completeness	Explicitly answers both 'what' (the four advisory areas) and 'when' ('Use when deciding whether... or when user mentions...'), and adds a 'NOT a tactical data engineering skill — strategic decisions only' boundary clause.	5 / 5
Trigger Term Quality	Comprehensive natural terms including abbreviation and full form ('CDO, chief data officer') plus decision-trigger phrases ('deciding whether to train models on customer data, choosing data architecture, valuing data for fundraising or M&A, sequencing data hires') and a 'user mentions...' list with synonyms.	5 / 5
Distinctiveness Conflict Risk	Clear CDO niche with an explicit NOT-clause narrowing scope, but topics like 'warehouse vs lakehouse vs mesh', 'build-vs-buy', and 'M&A readiness' overlap with adjacent CTO/CFO/general-counsel advisors, leaving minor conflict risk with closely related skills.	4 / 5
	Total	19 / 20 Passed

Validation

87%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
relative_links	Relative link issues: 4 missing	Warning
referenced_paths_exist	Referenced path issues: 16 missing	Warning

	Total	14 / 16 Passed

Repository: alirezarezvani/claude-skills
Path: .gemini/skills/skills-chief-data-officer-advisor/SKILL.md
Commit: 19392f7

Reviewed: ~16 hours ago

Table of Contents

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