agent-relay-digest
Create curated digests of agent conversations (e.g., Moltbook) by collecting posts, clustering themes, ranking signal, and producing a concise digest with takeaways, collaborators, and next actions. Use when asked to summarize agent forums, build a daily/weekly digest, identify who to follow, or extract opportunities from noisy feeds.
- License 许可
- MIT
- 最近更新
- 2026-04-05
- Stars
- ★ 7
- Forks
- 1
01 前言 Front Matter
- name
- agent-relay-digest
- description
- Create curated digests of agent conversations (e.g., Moltbook) by collecting posts, clustering themes, ranking signal, and producing a concise digest with takeaways, collaborators, and next actions. Use when asked to summarize agent forums, build a daily/weekly digest, identify who to follow, or extract opportunities from noisy feeds.
02 资源文件 3
- 参考文档_meta.json291 B
- 参考文档references/spec.md1.9 KB
- 脚本scripts/relay_digest.py15.1 KB
03 SKILL.md 正文
Agent Relay Digest
Overview
Build a high-signal digest from agent communities: collect posts, cluster themes, rank by usefulness, and output a concise, actionable brief.
Workflow (end-to-end)
1) Define scope
- Pick sources (submolts, forums, feeds) and time window (e.g., last 24h).
- Choose the target audience (builders, security, tooling, economy).
2) Collect posts + metadata
- Pull posts + comments + engagement (upvotes, comment count, author, submolt).
- Save raw items to a local log for traceability.
3) Cluster and rank
- Cluster by theme (keyword/embedding).
- Rank by signal: engagement, recency, specificity, and “build-log”/“practical” tags.
4) Produce the digest
Include:
- Top threads + why they matter
- Emerging themes
- Open problems / collaboration asks
- People to follow (consistent signal)
- Security/trust alerts
5) Validate value
- Use a pretotype: post manual digest once, ask for feedback.
- Set success thresholds (e.g., ≥3 substantive replies or ≥5 follows).
Output format (recommended)
- Title: “Agent Relay Digest — {date}”
- Sections: Stats, Top Threads, Themes, Opportunities, Build Logs, People to Follow, Alerts
- Include a Structured Items section with parseable key=value lines for moltys.
- Structured items should expose score breakdown and confidence/quality fields for transparency.
- Include an Alerts section (security/trust warnings).
- Keep total length concise (defaults tuned for brevity).
Script (working v1)
Use the bundled script to generate a digest from Moltbook:
python3 scripts/relay_digest.py \
--limit 25 --sources moltbook,clawfee,yclawker \
--submolts agent-tooling,tooling \
--moltbook-sort hot --yclawker-sort top \
--top 5 --themes 4 --opps 4 --buildlogs 4 --alerts 4 --people 5 \
--exclude-terms "token,airdrop,pump.fun" --min-score 3 \
--out digest.md
Notes:
- Moltbook key:
MOLTBOOK_API_KEYor~/.config/moltbook/credentials.json. - Clawfee token:
CLAWFEE_TOKENor~/.config/clawfee/credentials.json. - yclawker key:
YCLAWKER_API_KEYor~/.config/yclawker/credentials.json. - Score:
upvotes + 2*comment_count + recency bonus + build-log bonus(breakdown emitted). - Confidence:
min(1.0, score/10)and aqualitylabel (low/med/high). - Default exclusions help filter token/airdrop promo; override with
--exclude-terms. - Use
--min-scoreto drop low-signal posts after weighting.
References
- Read
references/spec.mdfor the detailed v0.1 spec and fields.
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