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outlier-post-finder

Use when the user wants to find posts, videos, reels, shorts, tweets, or social content that overperformed versus a creator, brand, or competitor baseline. Finds outliers, explains why they worked, extracts hooks and formats, and produces a practical swipe file.

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Prix non confirmé★ 2,165 Stars GitHubRegistre mis à jour · 8 sept. 2026agent-skill

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Outlier Post Finder

Overview

Find social posts that beat an account's normal performance. The goal is not just to sort by views. The goal is to identify posts that performed unusually well for that creator or brand, then explain the repeatable patterns.

Use ScrapeCreators as the data layer. Pull recent public posts, normalize engagement metrics, calculate each account's baseline, and produce an outlier report with source URLs and practical takeaways.

When to Use

Use this skill when the user asks to:

find outlier posts, viral posts, top posts, best reels, best shorts, best TikToks, or best tweets
analyze why a creator's content is working
find competitor posts worth copying or learning from
build a swipe file from high-performing social posts
compare performance across a creator's recent posts

Do not use this for raw endpoint lookup only. Use scrapecreators-api for direct API routing.

Data Sources

Prefer the platform-specific feed endpoint, then enrich individual posts only when needed.

Platform	Feed endpoint	Detail/enrichment endpoint
TikTok	`/v3/tiktok/profile/videos`	`/v2/tiktok/video`, `/v1/tiktok/video/transcript`
Instagram posts	`/v2/instagram/user/posts`	`/v1/instagram/post`, `/v2/instagram/media/transcript`
Instagram reels	`/v1/instagram/user/reels`	`/v1/instagram/post`, `/v2/instagram/media/transcript`
YouTube videos	`/v1/youtube/channel-videos`	`/v1/youtube/video`, `/v1/youtube/video/transcript`
YouTube Shorts	`/v1/youtube/channel/shorts`	`/v1/youtube/video`, `/v1/youtube/video/transcript`
Facebook	`/v1/facebook/profile/posts`, `/v1/facebook/profile/reels`	`/v1/facebook/post`, `/v1/facebook/post/transcript`
LinkedIn	`/v1/linkedin/company/posts`	`/v1/linkedin/post`, `/v1/linkedin/post/transcript`
X/Twitter	`/v1/twitter/user-tweets`	`/v1/twitter/tweet`, `/v1/twitter/tweet/transcript`
Threads	`/v1/threads/user/posts`	`/v1/threads/post`
Bluesky	`/v1/bluesky/user/posts`	`/v1/bluesky/post`

Before calling an endpoint, fetch its docs or per-endpoint OpenAPI spec if parameter names or response fields are uncertain.

Workflow

Clarify scope only if needed
- Platform(s)
- Handles or URLs
- Time/post count window
- Whether to include transcript/comment analysis
Fetch recent posts
- Pull at least 20 posts when available. More is better for baseline confidence.
- Paginate if the endpoint supports cursors and the user wants a larger window.
- Keep source URLs for citations.
Normalize metrics
- Capture whatever exists: views, plays, likes, comments, shares, reposts, saves.
- Build a combined engagement score only after preserving raw metrics.
- For video-first platforms, views/play count is usually the primary metric.
- For text-first platforms, likes + replies/comments + reposts/shares is usually better.
Calculate the account baseline
- Use median instead of mean so one viral post does not distort the baseline.
- Calculate per-platform and per-account baselines separately.
- If mixed formats exist, split by format when possible: reel vs carousel, short vs long video, text vs video.
Score outliers
- view_lift = post_views / median_views
- engagement_lift = post_engagement / median_engagement
- Label posts as:
  - Huge outlier: 5x+ baseline
  - Strong outlier: 2x-5x baseline
  - Mild outlier: 1.5x-2x baseline
- If sample size is under 10 posts, call confidence low.
Enrich the winners
- Fetch post details for top outliers.
- Fetch transcripts for video posts when useful.
- Optionally fetch comments to understand audience reaction.
Explain why they worked Look for:
- hook style
- topic/category
- format
- emotional trigger
- novelty/timeliness
- creator proof or authority
- controversy or debate
- comments showing confusion, desire, or buying intent

Output Format

# Outlier Posts Report: {creator_or_brand}

## Summary
- Sample: {n} posts from {platforms}
- Window: {window}
- Baseline: median {primary_metric} = {value}
- Confidence: High/Medium/Low

## Biggest Outliers
| Rank | Post | Platform | Date | Primary Metric | Lift | Why it likely worked |
|---:|---|---|---|---:|---:|---|
| 1 | [title/hook](url) | TikTok | 2026-01-01 | 1.2M views | 8.4x | Contrarian hook + clear before/after |

## Repeatable Patterns
1. **Pattern name** — evidence and examples.
2. **Pattern name** — evidence and examples.

## Hooks to Steal
- "Exact hook from caption or transcript"
- "Exact hook from caption or transcript"

## Content Ideas Based on the Outliers
1. ...
2. ...

## Notes and Caveats
- Public data only.
- Small samples are directional, not definitive.

Common Pitfalls

Do not call the highest raw-view post the best outlier if a huge account is being compared with a small one. Use lift versus each account's own baseline.
Do not average TikTok, Instagram, YouTube, and LinkedIn metrics into one baseline. Score each platform separately.
Do not invent transcript quotes. Fetch transcripts or quote only visible captions/text.
Do not overstate confidence from fewer than 10 posts.
Do not ignore old viral posts if the user asked for recent performance. Respect the requested window.

Voir la source ↗

Métadonnées du fichier

name: outlier-post-finder
description: Use when the user wants to find posts, videos, reels, shorts, tweets, or social content that overperformed versus a creator, brand, or competitor baseline. Finds outliers, explains why they worked, extracts hooks and formats, and produces a practical swipe file.
allowed-tools: Bash, Read, Write, WebFetch

version: 1.0.0
author: ScrapeCreators
license: MIT
homepage: https://scrapecreators.com
repository: https://github.com/ScrapeCreators/social-media-research-skills
metadata:
  openclaw:
    requires:
      env:
        - SCRAPECREATORS_API_KEY
    primaryEnv: SCRAPECREATORS_API_KEY
    homepage: https://scrapecreators.com
    tags:
      - social-media
      - research
      - scrapecreators

Voir le texte original

---
name: outlier-post-finder
description: Use when the user wants to find posts, videos, reels, shorts, tweets, or social content that overperformed versus a creator, brand, or competitor baseline. Finds outliers, explains why they worked, extracts hooks and formats, and produces a practical swipe file.
allowed-tools: Bash, Read, Write, WebFetch

version: 1.0.0
author: ScrapeCreators
license: MIT
homepage: https://scrapecreators.com
repository: https://github.com/ScrapeCreators/social-media-research-skills
metadata:
  openclaw:
    requires:
      env:
        - SCRAPECREATORS_API_KEY
    primaryEnv: SCRAPECREATORS_API_KEY
    homepage: https://scrapecreators.com
    tags:
      - social-media
      - research
      - scrapecreators
---

# Outlier Post Finder

## Overview

Find social posts that beat an account's normal performance. The goal is not just to sort by views. The goal is to identify posts that performed unusually well for that creator or brand, then explain the repeatable patterns.

Use ScrapeCreators as the data layer. Pull recent public posts, normalize engagement metrics, calculate each account's baseline, and produce an outlier report with source URLs and practical takeaways.

## When to Use

Use this skill when the user asks to:

- find outlier posts, viral posts, top posts, best reels, best shorts, best TikToks, or best tweets
- analyze why a creator's content is working
- find competitor posts worth copying or learning from
- build a swipe file from high-performing social posts
- compare performance across a creator's recent posts

Do not use this for raw endpoint lookup only. Use `scrapecreators-api` for direct API routing.

## Data Sources

Prefer the platform-specific feed endpoint, then enrich individual posts only when needed.

| Platform | Feed endpoint | Detail/enrichment endpoint |
|---|---|---|
| TikTok | `/v3/tiktok/profile/videos` | `/v2/tiktok/video`, `/v1/tiktok/video/transcript` |
| Instagram posts | `/v2/instagram/user/posts` | `/v1/instagram/post`, `/v2/instagram/media/transcript` |
| Instagram reels | `/v1/instagram/user/reels` | `/v1/instagram/post`, `/v2/instagram/media/transcript` |
| YouTube videos | `/v1/youtube/channel-videos` | `/v1/youtube/video`, `/v1/youtube/video/transcript` |
| YouTube Shorts | `/v1/youtube/channel/shorts` | `/v1/youtube/video`, `/v1/youtube/video/transcript` |
| Facebook | `/v1/facebook/profile/posts`, `/v1/facebook/profile/reels` | `/v1/facebook/post`, `/v1/facebook/post/transcript` |
| LinkedIn | `/v1/linkedin/company/posts` | `/v1/linkedin/post`, `/v1/linkedin/post/transcript` |
| X/Twitter | `/v1/twitter/user-tweets` | `/v1/twitter/tweet`, `/v1/twitter/tweet/transcript` |
| Threads | `/v1/threads/user/posts` | `/v1/threads/post` |
| Bluesky | `/v1/bluesky/user/posts` | `/v1/bluesky/post` |

Before calling an endpoint, fetch its docs or per-endpoint OpenAPI spec if parameter names or response fields are uncertain.

## Workflow

1. **Clarify scope only if needed**
   - Platform(s)
   - Handles or URLs
   - Time/post count window
   - Whether to include transcript/comment analysis

2. **Fetch recent posts**
   - Pull at least 20 posts when available. More is better for baseline confidence.
   - Paginate if the endpoint supports cursors and the user wants a larger window.
   - Keep source URLs for citations.

3. **Normalize metrics**
   - Capture whatever exists: views, plays, likes, comments, shares, reposts, saves.
   - Build a combined engagement score only after preserving raw metrics.
   - For video-first platforms, views/play count is usually the primary metric.
   - For text-first platforms, likes + replies/comments + reposts/shares is usually better.

4. **Calculate the account baseline**
   - Use median instead of mean so one viral post does not distort the baseline.
   - Calculate per-platform and per-account baselines separately.
   - If mixed formats exist, split by format when possible: reel vs carousel, short vs long video, text vs video.

5. **Score outliers**
   - `view_lift = post_views / median_views`
   - `engagement_lift = post_engagement / median_engagement`
   - Label posts as:
     - **Huge outlier:** 5x+ baseline
     - **Strong outlier:** 2x-5x baseline
     - **Mild outlier:** 1.5x-2x baseline
   - If sample size is under 10 posts, call confidence low.

6. **Enrich the winners**
   - Fetch post details for top outliers.
   - Fetch transcripts for video posts when useful.
   - Optionally fetch comments to understand audience reaction.

7. **Explain why they worked**
   Look for:
   - hook style
   - topic/category
   - format
   - emotional trigger
   - novelty/timeliness
   - creator proof or authority
   - controversy or debate
   - comments showing confusion, desire, or buying intent

## Output Format

```markdown
# Outlier Posts Report: {creator_or_brand}

## Summary
- Sample: {n} posts from {platforms}
- Window: {window}
- Baseline: median {primary_metric} = {value}
- Confidence: High/Medium/Low

## Biggest Outliers
| Rank | Post | Platform | Date | Primary Metric | Lift | Why it likely worked |
|---:|---|---|---|---:|---:|---|
| 1 | [title/hook](url) | TikTok | 2026-01-01 | 1.2M views | 8.4x | Contrarian hook + clear before/after |

## Repeatable Patterns
1. **Pattern name** — evidence and examples.
2. **Pattern name** — evidence and examples.

## Hooks to Steal
- "Exact hook from caption or transcript"
- "Exact hook from caption or transcript"

## Content Ideas Based on the Outliers
1. ...
2. ...

## Notes and Caveats
- Public data only.
- Small samples are directional, not definitive.
```

## Common Pitfalls

- Do not call the highest raw-view post the best outlier if a huge account is being compared with a small one. Use lift versus each account's own baseline.
- Do not average TikTok, Instagram, YouTube, and LinkedIn metrics into one baseline. Score each platform separately.
- Do not invent transcript quotes. Fetch transcripts or quote only visible captions/text.
- Do not overstate confidence from fewer than 10 posts.
- Do not ignore old viral posts if the user asked for recent performance. Respect the requested window.

Examiner la source

Prix et coûts d’utilisation

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L’utiliser: Prérequis non confirmés. Consultez les frais d’agent, d’API et de services à la source.
Licence: MIT
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Gratuit à obtenir ne signifie pas gratuit à utiliser. Le prix ne constitue pas une évaluation de sécurité. Soumettre un prix →

Source du skill enregistrée

Un chemin vers les instructions est enregistré. Cela ne constitue pas un test, une garantie de sécurité ou de compatibilité.

Réviser avant installation: Éviter l’installation automatique

Licence: MIT

Dependency or permission surface needs review
Permission surface may require sandboxing
SKILL.md excerpt is truncated in the review, but the provided content is sufficient for assessment.
The skill relies on an external API (ScrapeCreators) which may have rate limits or downtime; no error handling is described.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Ouvrir l’audit complet

Les outils sont des indications de métadonnées, pas une compatibilité testée. Les prompts sont des suggestions.

Commencer par une petite tâche

1Lisez la source et confirmez entrées, résultats, dépendances et permissions.
2Demandez un plan à l’agent. Approuvez la configuration et les coûts avant un test isolé.
3Vérifiez résultats et fichiers modifiés. Signalez uniquement ce qui a été exécuté et conservez la révision source.

Vérifiez les dépendances, clés API et frais externes dans la source. Un dépôt public ne rend pas tous les services gratuits.

Source et conseils d’utilisation

Répertorié

Métadonnées et examens sont indicatifs. Popularité, découverte et exécution réussie sont des faits distincts.

Dépôt source: ScrapeCreators/social-media-research-skills
Licence: MIT
Version: 1.0.0
Dernier push GitHub: 26 août 2026
Registre mis à jour: 8 sept. 2026
Chemin des instructions: skills/outlier-post-finder/SKILL.md @ 64ba7b4dea71

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

77/100

Solide

Confiance

60/100

Sandbox uniquement

Audit

77/100

Revue nécessaire

Ouvrir l’audit complet Voir le rapport d’évaluation

Dependency or permission surface needs review
Permission surface may require sandboxing
SKILL.md excerpt is truncated in the review, but the provided content is sufficient for assessment.
The skill relies on an external API (ScrapeCreators) which may have rate limits or downtime; no error handling is described.
Quality score needs review
Permission surface needs review: secrets or environment access, shell or command execution
Dependency/runtime risk: command execution surface, credential or environment access
Permission surface: secrets or environment access, shell or command execution

Verified installs: —
Résultats: —

Copier ne signifie pas installer. Les compteurs nécessitent un rapport de réussite et ne garantissent pas la qualité globale.

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Plus de détails

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    "risk_label": "Needs review",
    "warnings": [
      "Dependency or permission surface needs review",
      "Permission surface may require sandboxing",
      "SKILL.md excerpt is truncated in the review, but the provided content is sufficient for assessment.",
      "The skill relies on an external API (ScrapeCreators) which may have rate limits or downtime; no error handling is described.",
      "Quality score needs review",
      "Permission surface needs review: secrets or environment access, shell or command execution",
      "Dependency/runtime risk: command execution surface, credential or environment access",
      "Permission surface: secrets or environment access, shell or command execution"
    ]
  },
  "safety_gate": {
    "tier": "blocked",
    "label": "Blocked for auto-install",
    "auto_install_policy": "block",
    "auto_install_allowed": false,
    "human_review_required": true,
    "blocked": true,
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first."
  },
  "quality": {
    "score": 77,
    "label": "Strong"
  },
  "supply": {
    "track": "Design and creative production",
    "scenario": "Design and creative",
    "maintenance": "2mo since push",
    "risk": "Needs review"
  },
  "alternative_skills": [
    {
      "slug": "latent-spaces-brag-slim",
      "name": "brag-slim",
      "url": "https://www.openagentskill.com/skills/latent-spaces-brag-slim",
      "stars": 13807,
      "install_command": "npx skills add latent-spaces/brag --skill brag-slim",
      "trust_score": 81,
      "audit_score": 84
    },
    {
      "slug": "krillinai-krillinai-render-vertical",
      "name": "krillinai-render-vertical",
      "url": "https://www.openagentskill.com/skills/krillinai-krillinai-render-vertical",
      "stars": 12690,
      "install_command": "npx skills add krillinai/OpenCreator --skill krillinai-render-vertical",
      "trust_score": 83,
      "audit_score": 85
    }
  ],
  "do_not_use_when": [
    "teams that need a vendor-supported SLA",
    "production agents without a repository review",
    "SKILL.md excerpt is truncated in the review, but the provided content is sufficient for assessment.",
    "High-risk permission hints: Shell or command execution, Secrets or environment access",
    "Dependency or permission surface needs review",
    "Permission surface may require sandboxing",
    "The skill relies on an external API (ScrapeCreators) which may have rate limits or downtime; no error handling is described.",
    "Quality score needs review"
  ],
  "agent_contract": {
    "task_input": "Use outlier-post-finder in an agent workflow",
    "recommended_action": "Do not auto-install. Inspect the source, dependencies, and permission surface first.",
    "install_policy": "block",
    "minimum_review_before_use": [
      "Trust: 68/100 Manual review",
      "Audit: 77/100 Needs review",
      "Safety: 37/100 Avoid automatic install",
      "Review repository, license, install command, and permission surface before production use."
    ],
    "expected_agent_output": {
      "selected_skill": "scrapecreators-outlier-post-finder (outlier-post-finder)",
      "install_command": "npx skills add ScrapeCreators/social-media-research-skills --skill outlier-post-finder",
      "risk_summary": "Needs review; Blocked for auto-install; Review before production",
      "verification_result": "Report the smallest successful task, files touched, warnings, and any missing setup."
    }
  },
  "outcome_feedback": {
    "endpoint": "https://www.openagentskill.com/api/agent/outcome",
    "method": "POST",
    "requires_resolve_event_id": true,
    "event_id_source": "Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.",
    "expected_outcomes": [
      "success",
      "failed",
      "not_relevant",
      "blocked_by_risk",
      "setup_required"
    ],
    "payload_template": {
      "event_id": "<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>",
      "skill_slug": "scrapecreators-outlier-post-finder",
      "task": "Use outlier-post-finder in an agent workflow",
      "agent": "codex",
      "outcome": "success",
      "install_used": true,
      "risk_blocked": false,
      "setup_required": false,
      "task_success": true,
      "output_quality": 4,
      "error_type": null,
      "human_review_required": false,
      "workspace": "sandbox",
      "time_to_useful_ms": 120000,
      "notes": "Report the smallest successful task, setup friction, files touched, and risk notes."
    }
  },
  "endpoints": {
    "web": "https://www.openagentskill.com/skills/scrapecreators-outlier-post-finder",
    "api": "https://www.openagentskill.com/api/agent/skills/scrapecreators-outlier-post-finder",
    "audit": "https://www.openagentskill.com/skills/scrapecreators-outlier-post-finder/audit",
    "eval": "https://www.openagentskill.com/api/agent/evals?slug=scrapecreators-outlier-post-finder&task=Use%20outlier-post-finder%20in%20an%20agent%20workflow&max_risk=medium",
    "resolve": "https://www.openagentskill.com/api/agent/resolve?task=Use%20outlier-post-finder%20in%20an%20agent%20workflow&agent=codex&max_risk=medium",
    "receipt": "https://www.openagentskill.com/api/agent/receipt?task=Use%20outlier-post-finder%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text",
    "install": "https://www.openagentskill.com/api/skills/scrapecreators-outlier-post-finder/install",
    "manifest": "https://www.openagentskill.com/api/registry/manifest/scrapecreators-outlier-post-finder"
  }
}

Pour le créateur

Source de la fiche

Indexé par Registry

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Cette fiche a été indexée à partir de sources publiques et n’est pas marquée officielle tant qu’une revendication de mainteneur n’est pas approuvée.

Créateur: ScrapeCreators
Source: ScrapeCreators/social-media-research-skills
Indexé par: Index communautaire OpenAgentSkill

L’attribution renvoie au dépôt public ou au profil du créateur. Les créateurs peuvent revendiquer la fiche pour mettre à jour les signaux de propriété.

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