leamsigc/shortsgenerator/twitter-research-report
Claude Code and agent skill by leamsigc/shortsgenerator
- community
Checking that the SKILL.md file is still in the repository.
Report state — generates the final HTML report (REPORT.html) from raw-posts.json, audience-scores.json, content-drafts.json, and engagement-responses.json. Includes audience scoring matrix, top post analysis, content drafts, and pre-defined engagement responses for every topic post. In Video Ideas Mode it also renders the top-10 videos by views (with outlines) and the 5 video ideas with 3 scripts each (viral/storytelling/inspiration) plus YouTube metadata (title, description, tags, keywords) vi…
Install
npx vskill@latest install leamsigc/shortsgenerator/twitter-research-reportSKILL.md
Twitter/X Research — Report State (v4)
Generates the final HTML report with audience scoring, post links, and engagement responses.
Video Ideas Mode report
When the session contains video-ideas.json (from the analyze state / the video-idea-research playbook), render the dedicated ideas report:
Writes ideas-report.md + REPORT.html next to the input with the two mandatory sections: 1) the top 10 videos (rank, title, views, window, velocity, link, outline) and 2) the 5 video ideas (titles, viral + storytelling + inspiration scripts, audiences, view estimate, media links, YouTube metadata). If the main REPORT.html also exists, append a link to it so both are reachable from one index.
Preconditions
- Config exists:
.twitter-research/<timestamp>/config.json - Raw posts exist:
.twitter-research/<timestamp>/raw-posts.json(10+ topic posts) - Analysis exists:
.twitter-research/<timestamp>/audience-scores.json - Content drafts exist:
.twitter-research/<timestamp>/content-drafts.json
Steps
1. Generate engagement responses (per topic post)
For EVERY post in raw-posts.json posts[], craft 3 response types the user can post as replies to build presence on the topic:
| Type | Strategy | Limit | Tone | |
|---|---|---|---|---|
| Value add | Build on the tweet's point with an expert insight | 1-3 sentences | Helpful, authoritative | |
| Discussion starter | Ask a thoughtful question that sparks replies | 1-2 sentences | Curious | |
| Agree + amplify | Agree strongly and add a personal take | 1-2 sentences | Enthusiastic |
Rules: never pitch the product, stay on-topic, reference specifics, end with a hook, keep it short.
Save to .twitter-research/<timestamp>/engagement-responses.json (schema: responses[] with targetPostUrl, targetHandle, postPreview, targetSegment, responses[{type, text, whyThisWorks}], tracking).
2. Generate REPORT.html
The script renders a self-contained dark-themed report from all JSON files:
- Audience scoring matrix
- Top posts with direct X links + engagement stats
- Content drafts (social posts + video scripts)
- Engagement responses (copyable, with Reply-on-X links)
Report Completion
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/twitter-research-report/SKILL.md
Popularity
- Repository stars
- 348
- Repository forks
- 75
- 7-day trend score
- 29
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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