cosmicstack-labs

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daily-briefing

Automated daily tech briefing — multi-source collection → knowledge-base deduplication → AI summarization → TTS speech synthesis, generating MP3 audio briefings

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Prix non confirmé★ 471 Stars GitHubRegistre mis à jour · 3 sept. 2026agent-skill

Vue d’ensemble

Automated daily tech briefing — multi-source collection → knowledge-base deduplication → AI summarization → TTS speech synthesis, generating MP3 audio briefings

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Daily AI Audio Briefing

Automatically collect, deduplicate, summarize, and synthesize a daily tech briefing as a warm-voiced MP3 every morning.

Workspace

  • Collection script + summarization/TTS script
  • Output: briefing/YYYY-MM-DD.mp3 + .txt
  • Knowledge base: brain/news/YYYY-MM-DD/
  • Schedule: cron (recommended 8:30 AM)

Workflow

  1. Collect — Scrape GitHub trending/rising, HN top/show/new, arXiv latest AI papers, weather
  2. Deduplicate — Compare against brain/news/ existing entries
    • New project → mark is_new
    • Growth >30% → mark is_update
    • Otherwise → discard
  3. Ingest — Write new entries to brain/news/YYYY-MM-DD/
  4. Summarize — AI composes briefing script from filtered JSON
  5. Synthesize — TTS API → MP3 file
  6. Cleanup — Delete briefings older than 7 days

Rules

  • Don't use shell-level file deletion (find -delete) — may trigger security scanners; use Python Path.unlink()
  • Don't assume cron environment has API keys loaded — export them before running scripts
  • Don't use inline python3 -c or heredocs in agent/cron mode — write to .py files first
  • Don't trust agent-reported "MP3 generated" — verify mtime with stat after TTS step
  • Don't let each source exceed 8 items — keeps briefing concise

Validation

  • Collection script runs successfully, all sources return data
  • After dedup, filtered items ≥ 3
  • Generated briefing text contains correct date (no placeholders)
  • MP3 mtime matches current time (TTS actually ran)

Pitfalls

Date placeholders not replaced (Fixed: 2026-05-12)
  • Symptom: Briefing shows "Year X Month X" instead of actual date
  • Root cause: Prompt didn't inject real date, AI made it up
  • Fix: Inject datetime.date.today() into summarization prompt
Wrong weather source (Fixed: 2026-05-12)
  • Symptom: Always reports wrong city/temperature format
  • Root cause: Source only provided real-time temp, no high/low
  • Fix: Switch to structured weather API with high/low temp
Cron security scanner false positives
  • Symptom: Prompt blocked by exfil_curl pattern
  • Fix: Mark trusted cron job with skip_injection_scan: true
Cron environment missing .env
  • Symptom: TTS fails with "Missing credentials"
  • Fix: Export API keys before script execution
Model reasoning field empty content
  • Symptom: Reasoning model puts output in reasoning field, content is empty
  • Fix: Set generous max_tokens + retry with assistant message on empty content
TTS text length limit
  • Symptom: Long text causes unstable TTS output
  • Fix: Auto-truncate at safe threshold (~3000 chars)

References

  • references/weather-api.md — Weather data source and format
  • references/dedup-rules.md — Deduplication strategy and thresholds
  • references/tts-config.md — TTS model and parameters
  • references/cron-prompt-template.md — Cron job prompt template
Métadonnées du fichier
name: daily-briefing
description: 'Automated daily tech briefing — multi-source collection → knowledge-base deduplication → AI summarization → TTS speech synthesis, generating MP3 audio briefings'
metadata:
  author: myuxin007
  version: 1.0.0
  category: automation
  tags:
    - briefing
    - tts
    - news-aggregation
    - cron-automation
    - knowledge-base
    - speech-synthesis
Voir le texte original
---
name: daily-briefing
description: 'Automated daily tech briefing — multi-source collection → knowledge-base deduplication → AI summarization → TTS speech synthesis, generating MP3 audio briefings'
metadata:
  author: myuxin007
  version: 1.0.0
  category: automation
  tags:
    - briefing
    - tts
    - news-aggregation
    - cron-automation
    - knowledge-base
    - speech-synthesis
---

# Daily AI Audio Briefing

> Automatically collect, deduplicate, summarize, and synthesize a daily tech briefing as a warm-voiced MP3 every morning.

## Workspace

- Collection script + summarization/TTS script
- Output: `briefing/YYYY-MM-DD.mp3` + `.txt`
- Knowledge base: `brain/news/YYYY-MM-DD/`
- Schedule: cron (recommended 8:30 AM)

## Workflow

1. **Collect** — Scrape GitHub trending/rising, HN top/show/new, arXiv latest AI papers, weather
2. **Deduplicate** — Compare against `brain/news/` existing entries
   - New project → mark `is_new`
   - Growth >30% → mark `is_update`
   - Otherwise → discard
3. **Ingest** — Write new entries to `brain/news/YYYY-MM-DD/`
4. **Summarize** — AI composes briefing script from filtered JSON
5. **Synthesize** — TTS API → MP3 file
6. **Cleanup** — Delete briefings older than 7 days

## Rules

- Don't use shell-level file deletion (`find -delete`) — may trigger security scanners; use Python `Path.unlink()`
- Don't assume cron environment has API keys loaded — export them before running scripts
- Don't use inline `python3 -c` or heredocs in agent/cron mode — write to `.py` files first
- Don't trust agent-reported "MP3 generated" — verify mtime with `stat` after TTS step
- Don't let each source exceed 8 items — keeps briefing concise

## Validation

- [ ] Collection script runs successfully, all sources return data
- [ ] After dedup, filtered items ≥ 3
- [ ] Generated briefing text contains correct date (no placeholders)
- [ ] MP3 mtime matches current time (TTS actually ran)

## Pitfalls

### Date placeholders not replaced (Fixed: 2026-05-12)
- Symptom: Briefing shows "Year X Month X" instead of actual date
- Root cause: Prompt didn't inject real date, AI made it up
- Fix: Inject `datetime.date.today()` into summarization prompt

### Wrong weather source (Fixed: 2026-05-12)
- Symptom: Always reports wrong city/temperature format
- Root cause: Source only provided real-time temp, no high/low
- Fix: Switch to structured weather API with high/low temp

### Cron security scanner false positives
- Symptom: Prompt blocked by exfil_curl pattern
- Fix: Mark trusted cron job with `skip_injection_scan: true`

### Cron environment missing .env
- Symptom: TTS fails with "Missing credentials"
- Fix: Export API keys before script execution

### Model reasoning field empty content
- Symptom: Reasoning model puts output in `reasoning` field, `content` is empty
- Fix: Set generous `max_tokens` + retry with assistant message on empty content

### TTS text length limit
- Symptom: Long text causes unstable TTS output
- Fix: Auto-truncate at safe threshold (~3000 chars)

## References

- `references/weather-api.md` — Weather data source and format
- `references/dedup-rules.md` — Deduplication strategy and thresholds
- `references/tts-config.md` — TTS model and parameters
- `references/cron-prompt-template.md` — Cron job prompt template

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Licence: MIT

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
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Dépôt source
cosmicstack-labs/mercury-agent-skills
Licence
MIT
Version
1.0.0
Dernier push GitHub
25 août 2026
Registre mis à jour
3 sept. 2026

Version déclarée dans le registre ; vérifiez les versions de la source.

Qualité

70/100

Solide

Confiance

63/100

Sandbox uniquement

Audit

76/100

Revue nécessaire

  • Dependency or permission surface needs review
  • Permission surface may require sandboxing
  • Quality score needs review
  • Permission surface needs review: secrets or environment access, shell or command execution
  • Dependency/runtime risk: command execution surface, credential or environment access
  • Permission surface: secrets or environment access, shell or command execution
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Plus de détails
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Indiquez si ce skill semble utile à votre workflow Agent. Les retours agrégés améliorent le classement au fil du temps.