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Social data

Skill Orkas-AI/Orkas-Awesome-AgentSkills/data/skills/social-data

Curated Orkas agents and skills for education, product development, content creation, data analysis, office automation, and e-commerce workflows.

Install
npx -y skills add Orkas-AI/Orkas-Awesome-AgentSkills --skill social-data

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Fetch public social posts and analyze social/campaign metrics. Use this skill whenever the user asks to collect public social discussion, analyze social sentiment inputs, calculate engagement/CTR/ROI, compare platforms/content, or turn social samples into traceable findings.

SKILL.md

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Social Data

Use this skill for two related jobs:

  • fetch: collect public social posts from a specified platform and return structured, deduplicated items.
  • analyze: calculate and interpret metrics from user-provided social posts, campaign exports, or fetched social samples.

Keep the two steps distinct. Fetching returns evidence samples; analysis turns user-provided or fetched data into metrics and recommendations.

When To Use

  • The user asks what people are saying about a brand, product, competitor, topic, or pain point on Xiaohongshu, X/Twitter, Reddit, YouTube, or Bilibili.
  • The user provides social post/campaign data and asks for engagement rate, CTR, ROI, ROAS, CPC, CPE, CPM, CPA, top/bottom posts, platform comparison, or content recommendations.
  • The user wants social evidence for reputation, buzz, user complaints, market feedback, campaign performance, or next content experiments.

Do not use for:

  • Private messages, login-gated content, paid API bypassing, scraping restricted pages, or non-public data.
  • Claiming that zero fetched results means no discussion exists.
  • Treating benchmark comparisons as facts without user-provided or current benchmark context.
  • Replacing platform analytics exports when the user needs complete official reporting.

How To Call

  1. Choose the mode:

    • fetch: user needs public posts or discussion samples.
    • analyze: user already has post/campaign data or wants metrics/recommendations from fetched samples.
    • fetch_then_analyze: user asks for a topic analysis and no data is provided.

  2. For fetch mode:

    • Follow references/fetching.md.
    • One platform per script call: xhs, twitter, reddit, youtube, or bilibili.
    • Expand the user's topic into 3-8 short divergent keyword groups unless the user explicitly restricts keywords.
    • Report diag.status, failures, empty results, and platform dependency limits.

  3. For analysis mode:

    • Follow references/metrics.md.
    • Validate fields before calculating.
    • Label evidence as direct calculation, limited inference, or assumption.
    • Separate organic and paid performance when possible.

  4. Use scripts only when useful:

    • Fetch public samples: $ORKAS_NODE $ORKAS_PC_DIR/bin/run-skill.cjs social-data fetch -- <platform> <keywords> [options]
    • Calculate metrics from JSON: $ORKAS_NODE $ORKAS_PC_DIR/bin/run-skill.cjs social-data calculate_metrics -- data.json
    • Analyze performance from JSON: $ORKAS_NODE $ORKAS_PC_DIR/bin/run-skill.cjs social-data analyze_performance -- data.json

  5. Return traceable conclusions.

    • Tie claims back to item URLs, post IDs, comments, or user-provided rows.
    • Include data quality warnings and next tests.
    • Do not synthesize sample posts when fetch fails.

Default Output

For fetched discussion:

# Social Data Fetch Result

## Scope
- Platform:
- Topic:
- Keywords:
- Status:

## Sample Summary
- Items:
- Top repeated themes:
- Notable examples:

## Diagnostics
- Raw hits:
- Deduplicated:
- Failed:
- Limits:

## Next Analysis
- ...

For performance analysis:

# Social Performance Analysis

## Bottom Line

## Data Quality
- Sample size:
- Missing fields:
- Abnormal values:
- Confidence:

## Key Metrics
| Metric | Value | Meaning | Evidence |
|---|---:|---|---|

## Top / Bottom Content
| Rank | Post | Platform | Format | Metric | Possible reason |
|---|---|---|---|---:|---|

## ROI And Cost
- Spend:
- Revenue / value:
- ROI:
- ROAS:
- CPC / CPE / CPA:

## Recommendations
1. ...

External Dependencies

  • Python 3 for bundled scripts.
  • Fetch mode may need requests, browser_cookie3, curl_cffi, xreach, yt-dlp, or a local Xiaohongshu proxy depending on platform.
  • Analysis mode needs user-provided JSON, table data, or exported platform/campaign metrics.

Limits And Known Issues

  • Fetch coverage varies by platform, login state, rate limits, anti-bot behavior, and local dependencies.
  • Public fetches are samples, not complete platform analytics.
  • Anonymous Reddit/Bilibili recall can be weak; browser login cookies may improve results.
  • Xiaohongshu requires an external local proxy service at http://localhost:18060.
  • ROI estimates based on engagement value are assumptions unless the user provides real revenue, conversion value, or lead value.
  • Benchmark values can become stale and should be treated as rough context, not a pass/fail truth.

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