replace-skill-name

> **${var}** — Optional. Pass alternative keywords (comma-separated) to override the default. If empty, monitors `[REPLACE: KEYWORDS]`. Today is ${today}. Monitor social mentions of **[REPLACE: KEYWORDS]** and produce a summary. ## Steps 1. **Resolve keywords** — `KEYWORDS="${var:-[REPLACE: KEYWORDS]}"`. Split on commas, trim each, lower-case. Each token becomes its own search query. 2. **Search X** — for each keyword, use the X / xAI search path (project's standard pattern): ```bash # Uses XAI_API_KEY in-run via ./secretcurl (the key is injected via requires:). # Mirror the fetch-tweets skill: POST https://api.x.ai/v1/responses with # ./secretcurl -H "Authorization: Bearer {XAI_API_KEY}" -d @/tmp/payload.json # WebFetch (or a Nitter mirror) is the last-resort fallback. ``` Restrict to language `[REPLACE: LANGUAGE]` (e.g. `en`, `fr`, `any`). Drop posts with fewer than `[REPLACE: MIN_LIKES]` likes — that filter is what protects the channel from low-signal noise. 3. **Search Reddit** — for each keyword: ```bash # Reddit's keyless JSON endpoint. WebFetch fallback if curl fails (sandbox). curl -sf "https://www.reddit.com/search.json?q=$KEYWORD&t=day&restrict_sr=0" \ -H "User-Agent: aeon/1.0" > .reddit-cache.json || \ echo "use WebFetch on https://www.reddit.com/search.json?q=$KEYWORD&t=day" ``` 4. **Score and pick top 5 per platform** — score on engagement (likes, comments, score) × recency (last 24h gets full marks). Drop reposts and obvious bot accounts (handles like `*_bot`, account age < 7 days with > 100 posts). 5. **Tag sentiment** — for the top 10 posts overall, label each `positive` / `neutral` / `negative` based on tone of the post text. Keep this lightweight — one-token classification, no nested reasoning. 6. **Write `output/articles/[REPLACE: SKILL_NAME]-${today}.md`**: ```markdown # [REPLACE: KEYWORDS] — ${today} ## Volume - X: N posts (vs 7d avg M) - Reddit: N posts (vs 7d avg M) ## Sentiment positive: X · neutral: Y · negative: Z ## Top posts 1. [Author · platform · timestamp] "Excerpt or paraphrase." → URL 2. ... ``` 7. **Notify** via `./notify` with a 2-3 line summary: `*[REPLACE: KEYWORDS] — ${today}* · N posts · sentiment skews positive/negative · top: <one-line title>. Full digest: <url>`. Silent on quiet days (volume < 25% of 7d average AND no negative-sentiment spike). 8. **Log** to `memory/logs/${today}.md`: ``` ## [REPLACE: SKILL_NAME] - **Volume**: x_posts=N, reddit_posts=N, vs_7d_avg=Δ% - **Sentiment**: pos=X, neu=Y, neg=Z - **Status**: SOCIAL_OK | SOCIAL_QUIET | SOCIAL_SPIKE (vol > 2x avg) | SOCIAL_DEGRADED ``` ## Network note X / xAI requires `XAI_API_KEY`; a bare `$XAI_API_KEY` on a `curl` line is refused by the Bash analyzer, so call `./secretcurl` with the `{XAI_API_KEY}` placeholder (the key is injected via `requires:`). Reddit's JSON endpoint is keyless but rate-limited per IP — `WebFetch` is the fallback when `curl` returns 429. ## Constraints - **Bot filter** is critical. New accounts with high posting velocity dominate any keyword and are almost always inauthentic. Strict drop. - **Volume is more honest than sentiment**. A `SPIKE` (volume > 2x 7d avg) is a real signal; sentiment shifts within normal volume often aren't. - **Engagement filters scale**. `MIN_LIKES = [REPLACE: MIN_LIKES]` is a starting threshold — raise it as the topic gains attention so noise stays out.