算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
serenity-radar【设计与创意】Use @aleabitoreddit ("Serenity")'s full mention archive (built by the follow-aleabito skill) to anticipate where her attention is moving and generate candidate ideas in her style. Two modes — (1) RADAR reads the live mention data for attention momentum (which tickers she is heating up on, new entrants, conviction core, theme rotation) via scripts/rad…
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A data-driven companion to serenity-method. Where serenity-method teaches how she analyzes, this skill uses her actual 11-month archive (2025-07-02 → present, ~6,120 posts / 750 tickers) to estimate where her attention is going and to generate candidates the way she would.
What this is NOT. Not a predictor, not a buy/sell signal, not "she will pump X next." It is a candidate generator + checklist. A single account is fragile; virality ≠ correctness; her archive has survivorship bias (winners get re-cited, losers fade). Read the Caveats section before using output. Always end with: 仅作信息跟踪,不构成投资建议。
follow-aleabito skill produces it). Default path: $FOLLOW_ALEABITO_REPORTS_DIR/aleabito-mentions-events.csv (else the workspace reports/).follow-aleabito's incremental fetch (analyze-mentions.js --incremental --resume) before running radar, so signals reflect the latest days.serenity-method skill.Run the signal extractor:
FOLLOW_ALEABITO_REPORTS_DIR="<reports dir>" node skills/serenity-radar/scripts/radar.js --window 14 --top 20
# add --json for machine-readable output; --asof YYYY-MM-DD to evaluate a past date; --window 7 for a tighter read
It prints four signal blocks (see references/signals.md for the exact math):
How to read it: a name that is both a New entrant and Heating, in a theme that is rotating up, is the strongest "emerging focus" signal. A Conviction-watch name that is cooling (falling out of Heating) may be maturing toward exit/realization. Cross-check a heating name's recent posts (via follow-aleabito) to confirm it is a genuine thesis, not a one-off reply.
When the user wants ideas she hasn't surfaced yet, apply her empirical patterns (full detail in references/patterns.md). Her behavior is remarkably consistent; the three levers that predict her next focus:
Generate 3-5 candidates by running these levers off the current Heating/Conviction themes, then gate each.
A radar signal or generated idea is only a lead. Before presenting it as a thesis, run it through serenity-method (Steps 1-5: chokepoint test → first principles → Buffett quality gate (default unverified) → narrative-vs-fundamentals hygiene → classify as 研究地图 vs 可投资结论). Output should show the candidate and its gate result. Never promote a signal to a recommendation.
Language / 语言: respond in the user's language — 中文 by default, English on request. Bilingual labels below.
For each surfaced candidate, give:
serenity-method verdict (almost always 研究地图 / research-map, with the specific things to verify).| Need | Read |
|---|---|
| Her empirical patterns: theme-rotation logic, selection signature, catalyst playbook, conviction tells, track record | references/patterns.md |
| Exact radar math + how to read each signal + data caveats | references/signals.md |
| The analytical gate every candidate must pass | the serenity-method skill |
| Keeping the archive current / pulling raw posts | the follow-aleabito skill |
仅作信息跟踪,不构成投资建议。 / For information tracking only; not investment advice.