forest-synthesis

Solid

Weekly cross-corpus synthesis across accumulated daily-forest digests. Cross-day pattern extraction invisible to single-day reading. Use weekly not daily.

AI & Automation 2 stars 0 forks Updated 3 days ago MIT

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Skill Content

# Forest Synthesis Skill ## When to Use When asked for a "forest of forests" synthesis, cross-month pattern extraction, or strategic read across accumulated daily-forest digests. Ideally weekly (not daily. too noisy). ## Prerequisites - Daily-forest digests at `outputs/daily-forest/YYYY-MM-DD-daily-forest.md` (30+ files) - Skills system: `skills/daily-forest/SKILL.md` must exist and be LIVE ## Procedure ### Step 1. Identify the corpus ```bash ls outputs/daily-forest/*.md | wc -l # count available files ls outputs/daily-forest/*.md | head -5 # oldest ls outputs/daily-forest/*.md | tail -8 # most recent ``` ### Step 2. Strategic read via subagent Spawn a subagent with: - Read the 8 most recent digests IN FULL - Read 5-7 selected digests from mid-corpus (pick around sentiment shifts or dates around key events) - Section-header skim on remaining files - Goal: identify cross-day patterns invisible to single-day reading Subagent brief (paste verbatim, replacing N): ``` Read the daily-forest digests at outputs/daily-forest/. Corpus has ~N files. Strategy: read last 8 in full, skim 5-7 from mid-corpus, section-header skim the rest. Extract cross-day patterns in 8 categories: 1. Persistent Movers (appeared 3+ times, same direction) 2. Wave Movers (spiked then faded) 3. Multi-Week Silences (present then absent) 4. Tone Arcs (sentiment shift over time) 5. Long Cross-Stitches (two unrelated themes converging) 6. Late Bloomers (absent early, strong later) 7. Focus-Market-Speci...

Details

Author
0xUrsanomics
Repository
0xUrsanomics/utopia-os
Created
4 days ago
Last Updated
3 days ago
Language
Python
License
MIT

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