Die Oberfläche ist lokalisiert; Skill-Beschreibungen und -Dokumente werden per KI automatisch in Ihre Sprache übersetzt. Code, Befehle, Pfade und Fachbegriffe bleiben im Original, maßgeblich ist das Dokument des Autors.
Skills entdecken
Daten und Forschung · SKILL.md

gork-analysis

gork-analysis

Gork data API. Uses Grok model to analyze tweet comments, extract valuable intelligence from replies, and fetch latest community sentiment on projects or topics.

Independent GitHub snapshot · Automated classification · Original documentation governs

Skill-Dokumentation

GitHub

name: gork-analysis description: | Gork data API. Uses Grok model to analyze tweet comments, extract valuable intelligence from replies, and fetch latest community sentiment on projects or topics. metadata: author: NotevenDe version: 1.2.0

Gork Analysis — Tweet Comment Intelligence

Base URL: https://crab-skill.opsat.io

API Endpoint

POST /api/gork/analyze (requires Crab signature headers)

FieldRequiredDescription
promptYesAnalysis prompt with context (tweet URL, project name, question)
messagesNoOpenAI-style message list; takes precedence over prompt if given

Response: plain-text analysis generated by the Grok model.

Use Cases & Prompt Patterns

1. Analyze comments on a specific tweet

Extract valuable information from replies — insider knowledge, community warnings, technical critiques, sentiment signals.

{
  "prompt": "Analyze the comments and replies on this tweet: https://x.com/{username}/status/{id}\n\nFocus on:\n- High-value comments (technical insights, insider info, warnings)\n- Overall sentiment (bullish/bearish/neutral ratio)\n- Notable accounts that replied and their stance\n- Any claims or information worth verifying"
}

2. Get latest community sentiment on a project

Fetch what people are saying about a project right now.

{
  "prompt": "What are the latest comments and discussions about {project_name} (${ticker}) on Twitter/X?\n\nFocus on:\n- Recent criticisms or concerns\n- Notable endorsements or callouts\n- Any news, events, or incidents being discussed\n- Red flags mentioned by the community"
}

3. Deep dive on a topic or controversy

When Step 4 (deep dig) surfaces a lead worth investigating via social data.

{
  "prompt": "Search for discussions about {specific topic} related to {project_name}.\n\nFor example: '{project_name} + scam', '{team_member} + rug', '{project_name} + hack'\n\nSummarize what the community is saying and whether concerns are substantiated."
}

Key Rules

  • Max 2 calls per research — pick the top tweet (highest engagement) and the latest tweet (most recent). Do not make additional calls for project-level sentiment.
  • Always include tweet URL or project context in the prompt — Gork needs specific context to return useful data, not generic questions
  • Use targeted prompts — ask for specific information (comments, sentiment, controversy) rather than broad "analyze this project"
  • Chain with Twitter data — use tweet URLs discovered from /api/twitter/tweets as input for Gork comment analysis
  • Deep dig exception — Step 4 may make additional Gork calls only when a high-value lead requires verification, but still keep total calls minimal

Timeout & Fallback

Gork calls the Grok model for analysis, so response times are significantly longer than standard APIs. Allow up to 120 seconds before considering a request timed out.

ScenarioBehavior
Gork API key not setSkip Gork data
Response slow (< 120s)Keep waiting — this is normal for LLM analysis
Gork request timeout (≥ 120s)Retry once, then skip and record a warning
Gespeicherte Skills