Executive growth summary
Skill duandigi/duandigi-growth-marketing-skill/skills/executive-growth-summary
Evidence-first AI Agent Skills for growth marketing — multi-channel analytics (SEO, paid media, social, local search, CRM), secure account integration, AI evaluation, experimentation & approval-safe optimization for Claude Code.
npx -y skills add duandigi/duandigi-growth-marketing-skill --skill executive-growth-summaryAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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What its author says it does
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Use this skill when producing a daily alert, weekly growth review, monthly executive review, client report, or portfolio briefing from validated multi-channel evaluations and experiment results.
The file declares its own license as MIT. That is the author’s claim about this one file, and it is not the same thing as the license GitHub reports for the repository, which is listed with the other numbers below.
SKILL.md
3.4 KB, as published. Nobody here has run it
Executive Growth Summary
Purpose
Turn complex channel and funnel evidence into a concise decision brief for owners, executives, clients, and operators.
Inputs
- Validated project and portfolio evaluations
- Channel findings, anomalies, health scores, experiments, and approvals
- Business goals, audience, reporting period, and decision cadence
- Known data gaps, connection health, and previous commitments
If a required input is unavailable, label it unknown, state how it limits the decision, and create a collection, mapping, validation, or instrumentation task. Never invent credentials, assets, metrics, permissions, or business outcomes.
Workflow
- Define the audience, reporting period, comparison, and decisions required.
- Lead with customer value, qualified outcomes, revenue, efficiency, risk, and major changes.
- Summarize channel contributions without repeating every metric.
- Explain why material changes likely occurred and state confidence and alternatives.
- Report experiment decisions, unresolved issues, and learning that changes the playbook.
- Limit priorities to actions with an owner, expected mechanism, evidence, and approval state.
- Separate facts, interpretation, decisions, and appendices.
Required output
Return a concise, decision-oriented result containing:
- Executive summary and key decisions
- What changed, why, and business impact
- Portfolio and project priorities
- Channel and funnel highlights
- Experiment results, risks, approvals, and next actions
- Data-quality and confidence note
Label material statements as confirmed, calculated, inferred, assumed, or unknown. Include the data period, last complete period, source lineage, and confidence whenever they can change the decision.
Guardrails
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Do not bury critical tracking, compliance, spend, or revenue risks.
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Do not fill the report with channel metrics that do not affect a decision.
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Do not present AI interpretation as confirmed fact.
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Do not expose credentials, personal lead data, or confidential client details beyond the audience’s authorization.
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Do not claim guaranteed growth or present an estimate as observed fact.
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Do not reveal secrets, personal data, private provider payloads, or cross-project information.
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When an action can spend money, publish, contact people, alter access, modify production, or delete data, prepare an approval request instead of executing automatically.
Completion check
Before finishing, verify that the output:
- answers a specific business or implementation decision;
- uses the correct organization, project, asset, date range, time zone, and currency;
- separates performance problems from data, connection, and attribution problems;
- includes evidence, uncertainty, affected scope, and a measurable next step;
- respects least privilege, approval, audit, and rollback requirements;
- is no longer than necessary for the decision.