Distill Creator Playbook
Analyze public creator or brand-account content and distill reusable, ethical content patterns across positioning, topics, titles, openings, structures, proof, visuals, calls to action, comments, and publishing cadence. Use for 拆解博主, 对标账号, 内容蒸馏, 账号分析, 爆款结构, 创作者研究, 内容方法论, or converting public posts into an original execution playbook.
Install
$ agentstack add skill-shenyuannext-wepr-growth-skills-distill-creator-playbook ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-shenyuannext-wepr-growth-skills-distill-creator-playbook) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Distill Creator Playbook
Extract transferable decisions, not surface imitation.
Required inputs
Establish the platform, analysis target, whether it is a benchmark or the user's own account, analysis objective, sample window, and available public evidence. If a missing choice would materially change the result, ask for it; otherwise state a reasonable assumption.
Workflow
- Define the question the analysis must answer: positioning, topic selection, packaging, retention, conversion, or operating cadence.
- Build a traceable sample inventory with URL or identifier, date, format, title, topic, observable engagement, and evidence status.
- Separate observation from inference. Mark missing, inaccessible, deleted, or login-gated material.
- Code each item using the same dimensions: audience, job-to-be-done, hook, promise, structure, proof, emotion, visual device, CTA, and comment signal.
- Compare high-, middle-, and low-performing samples when comparable data exists. Do not infer causation from engagement alone.
- Identify recurring choices, controlled variations, exceptions, and possible confounders such as timing, paid distribution, celebrity, or prior audience size.
- Distill principles at three levels: stable positioning, reusable content modules, and testable packaging tactics.
- Translate principles into an original playbook with topic lanes, templates, examples, quality checks, and a 2–4 week test plan.
- Identify what must not be copied: wording, proprietary assets, personal stories, trademarks, signature characters, confidential data, or unverifiable claims.
- Return conclusions with evidence strength and unresolved questions.
Analysis discipline
- Use public content lawfully and respect access controls, privacy, copyright, and platform terms.
- Anonymize ordinary commenters and do not profile sensitive traits.
- Treat likes, saves, comments, and views as partial signals with different meanings.
- Do not call a pattern “爆款公式” unless repeated evidence supports it; prefer “working hypothesis.”
- Never invent inaccessible post content, comments, metrics, or account history.
Route by need
- Read [references/coding-framework.md](references/coding-framework.md) when analyzing samples.
- Read [references/playbook-output.md](references/playbook-output.md) when producing the final playbook or account comparison.
Deliverables
Return the relevant subset of: sample ledger, positioning map, topic architecture, title and opening patterns, content modules, proof and CTA patterns, visual system, comment insights, confidence notes, anti-copy boundaries, experiment backlog, and 30-day execution playbook.
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: ShenyuanNext
- Source: ShenyuanNext/wepr-growth-skills
- License: MIT
Install and usage instructions live in the source repository linked above.
Reviews
No reviews yet, be the first.
Write a review
Versions
- v0.1.0 Imported from the upstream source.