本文へ移動
cccskills
無料GitHub で公開

creator-profile-teardown

Analyze a creator, influencer, founder, competitor, or brand social account to explain its positioning, content pillars, winning posts, hooks, formats, series, calls to action, and audience response. Use when the user wants to understand why an account works and what patterns to test without copying it.

インストール方法を見る

含まれるファイル(2)

  • SKILL.md2.3 KB
  • skill.meta.json656 B

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Creator Profile Teardown

Turn a social profile into a sourced, repeatable content playbook.

Inputs

  • Profile URL or handle and platform.
  • Brand, audience, market, and the decision the teardown should inform.
  • Optional time window, sample size, Brand Core, and comparison account.

Workflow

  1. Confirm the official account and use scrapecreators-api to collect profile metadata, public links, and a representative recent-post sample.
  2. Use outlier-post-finder to compare posts against the account's own baseline. Separate repeatable outliers from giveaways, collaborations, paid distribution, and isolated viral events.
  3. Use transcript-intelligence on important videos and comment-mining where audience response affects the conclusion.
  4. Identify the account's audience promise, positioning, personality, content pillars, recurring series, formats, hooks, proof, calls to action, visual patterns, and cadence.
  5. Separate observed mechanics from inferred explanations. Explain several plausible drivers when causality is uncertain.
  6. Translate the strongest patterns into brand-specific tests. Adapt the mechanism and audience insight, not the creator's wording or identity.

Output

  • Positioning, promise, audience, voice, and profile-funnel summary.
  • Content-pillar and recurring-series table with sourced examples.
  • Ranked outlier posts with normalized lift and possible drivers.
  • Hook, format, proof, CTA, cadence, and audience-response patterns.
  • What to adapt, what not to copy, and five prioritized tests for the user's brand.
  • Coverage, source appendix, confidence, and limitations.

Guardrails

  • Do not reduce the teardown to a profile summary; identify repeatable mechanics.
  • Do not copy distinctive wording, private details, likeness, or personal identity.
  • Do not claim that a pattern caused performance when the evidence only shows correlation.
  • Preserve source links and clearly label inference.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Research supported advertising promises from a specific buyer's context, current product facts, customer language and observed ads. Turn them into static, video or copy ideas; match video ideas to actual recipes and save a product-scoped angle bank for write-video-ad-script. Product-led discovery can use verified facts without reviews. Reference persistence and reach are observations, not proof of performance.

日本語の概要は準備中です。原文の説明を表示しています。

gooseworks-ai/goose-skills1,2452026年10月13日 更新

Analyze ad campaign performance data (Google, Meta, LinkedIn) to identify what's working, what's wasting budget, and specific cut/scale/test recommendations. Runs statistical analysis, funnel diagnostics, and multi-channel budget reallocation with specific dollar-amount shift recommendations and scenario modeling.

日本語の概要は準備中です。原文の説明を表示しています。

gooseworks-ai/goose-skills1,2452026年10月13日 更新

For paid lead-gen and participant-recruitment ads, replaces vanity CPA with true CAC per qualified lead by joining ad-platform data with downstream funnel events, surfaces tracking gaps, and classifies every creative into Scale / Keep / Investigate / Cut.

日本語の概要は準備中です。原文の説明を表示しています。

gooseworks-ai/goose-skills1,2452026年10月13日 更新

The intake stage of a Meta ad harness. Researches the brand first, states what it assumes, and asks only what it cannot infer and what would change money, claims or legal exposure if guessed wrong — at most four questions a turn, in plain business language. Writes the brand's stable facts (ads/brand.md), the campaign brief, and a log of what was asked vs assumed. Use it when someone wants to run Meta ads and the brand's ad facts are not yet recorded.

日本語の概要は準備中です。原文の説明を表示しています。

gooseworks-ai/goose-skills1,2452026年10月13日 更新

Analyze the message match between your ads and landing pages. Checks if the promise in the ad copy carries through to the landing page headline, body, and CTA. Flags disconnects that kill conversion rates. Works with Google, Meta, and LinkedIn ads.

日本語の概要は準備中です。原文の説明を表示しています。

gooseworks-ai/goose-skills1,2452026年10月13日 更新

Turn a brand's facts, a campaign brief and the product into a one-minute Meta ad strategy with its reasoning — goal, audience, objective and placements, budget split, how many ads and how different they must be (generate 3x so the user can choose), the test frame, the success metric, and safety rules for the user to accept. Decides what launch-meta-ad-campaign then executes, and re-reads the strategy after a deep check to show which assumption changed. Use it after intake and before any creative is generated or any campaign is built.

日本語の概要は準備中です。原文の説明を表示しています。

gooseworks-ai/goose-skills1,2452026年10月13日 更新

gooseworks-ai のスキルをすべて見る

このスキルの問題を報告する