| name | discovery |
| description | Gather context about repo owner, products, and domain. Build domain expertise by reading top voices. Use proactively before creating content. |
| user-invocable | false |
Discovery Skill
Find voices, read content, build expertise
Owner & Product Discovery
gh api users/{owner}
Additional: Check ME.md, GitHub profile README, pinned repos, blog/website.
Products: gh api users/{owner}/repos?sort=updated → read READMEs, check live demos.
Staleness: Owner profile >30 days = refresh. Products = weekly.
Domain Trends Research
Web search for current data:
"X Twitter growth strategies {current_year}""AI developer Twitter accounts successful""{niche} best practices {current_year}"
Refresh each session (trends change constantly).
Build Domain Expertise
1. Top Voices List (~20 voices)
Find via web search ("best {niche} blogs", "top {niche} Twitter accounts"), follow-the-follows, curated lists.
Store in agent/memory/research/top-voices.md:
## @handle / Name
- Platform: X / Blog / Newsletter
- Focus: [niche/angle]
- Why follow: [value]
Refresh monthly.
2. Reading Routine
Each session, pick 2-3 voices. Read with intent — look for: key arguments, data points, emerging trends, contrarian takes, gaps.
Cadence: Top 5 voices every session (skim). Voices 6-20 weekly rotation.
3. Capture Reply-to-Own Opportunities While Reading
Outbound replies to others may fail via X API (403 restriction). Reply-to-own is the reliable engagement tactic.
What works: Reply-to-own (high success rate). While reading, look for tweet IDs from recent workflow runs to reply to:
gh run list --workflow=process-outputs.yml --limit 1 --json databaseId,createdAt
gh run view <run_id> --log 2>/dev/null | grep 'INFO Response:' | head -5
Prioritize reply-to-own files. Test outbound replies cautiously.
4. Turn Reading Into Content
| Reading output | Content use |
|---|
| Key takeaway | Authority post (your angle) |
| Disagreement | Contrarian take |
| Data point | Credibility boost |
| Trend spotted | First-mover post |
| Content gap | Fill it — own the topic |
Rules: Never plagiarize. Credit sources. Aim for 1 reading-inspired post per 3-5 articles. Goal = informed originality, not summary.
5. Graduate Research Into Skills
Research in agent/memory/research/ helps THIS session. Research in .claude/skills/ helps ALL future sessions.
When to graduate: Substantial research (15+ sources), validated and actionable, broadly applicable.
Follow "Skill Development (High Bar)" from CLAUDE.md. NOT every session — reserve for validated, substantial findings.
Owner's Open Source Scan
Periodically scan the owner's public repos for promotable content. This feeds the publishing skill's OS promotion allocation.
When: Once per session (during research phase), or when looking for content ideas.
How:
- Read
ME.md → find the owner's GitHub profile URL under "Open Source (Promotable)"
- WebFetch the profile page → discover public repos, orgs, and pinned projects
- WebFetch each discovered org page → list their repos too
- For repos that look promotable, fetch their README to find live output links and descriptions
What makes something promotable right now:
A. Live outcomes (highest priority) — Real content/services produced by agents. These are proof, not promises.
- Read
ME.md for known live outcome URLs, then WebFetch each to check for recent articles, digests, posts
- A specific recent article is 10x more promotable than a generic "we have a blog" link
- Frame as: "This was written by an AI agent today" + link to the actual piece
- Also check repo READMEs for new live output URLs — new pipelines may launch anytime
B. Repos with live outputs — Code that powers running services. Link both the code AND the output.
C. Star milestones — Crossing 5, 10, 25, 50, 100 stars.
D. Trending topic overlap — Repo solves something people are discussing this week. Strongest combo: trend + live proof.
E. New repos — Launch announcements get one-time boost.
What to capture: For each candidate: what it does (1 line), proof it works (live output links + recent specific content), hook angle (why someone cares today). Store in agent/memory/research/os-promo-candidates.md.
Cross-reference with trends: Trending topic aligns with an owner repo or outcome? Post about the trend, link the repo/outcome as "we built this, and here's it running."
Reference: GitHub accounts and known live outcomes in ME.md under "Open Source (Promotable)".
Reply Targets: Reply-to-Own is Most Reliable
Outbound replies to others often fail at X API (403) — particularly to accounts that haven't engaged with you. Reply-to-own is the primary engagement tactic.
Reply-to-own targets:
- Check
agent/state/current.md for recent tweet IDs
- Or run:
gh run list --workflow=process-outputs.yml --limit 1 --json databaseId → gh run view <id> --log | grep 'INFO Response:'
Only create reply files when:
- You have the numeric tweet ID of YOUR OWN recent tweet
- The topic has enough depth to add value in a reply
- Queue is < 15 on all platforms
- The original tweet was posted within 30 min (for 150x multiplier) — check run completion time first
Storage Structure
agent/memory/research/top-voices.md — curated voice listagent/memory/research/reading-notes/ — per-article notes (optional)agent/memory/research/expertise/ — synthesized domain knowledge
