Narrative Tracker

Read memory/MEMORY.md for context on prior narrative observations. Read the last 3 days of memory/logs/ — specifically any prior ### narrative-tracker entries — to (a) avoid re-reporting the same narratives without new info, and (b) detect phase transitions vs the last run.

Goal

Produce a decision-grade narrative map: every narrative gets a mindshare score, a velocity arrow, a sentiment tag, named drivers, and an explicit position call. Classification without a position call is noise.

Steps

1. Ingest signals

a. XAI pre-fetched cache (primary source). The workflow pre-fetches Grok x_search results to .xai-cache/narratives.json. Read it. If the file exists and contains usable results, use that as the primary signal.

b. If cache is missing or empty, log a NARRATIVE_CACHE_MISS line to memory/logs/${today}.md (so skill-health can spot the pattern — never silently fall through), then attempt the direct API call:

FROM_DATE=$(date -u -d "3 days ago" +%Y-%m-%d 2>/dev/null || date -u -v-3d +%Y-%m-%d)
TO_DATE=$(date -u +%Y-%m-%d)
curl -s --max-time 60 -X POST "https://api.x.ai/v1/responses" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $XAI_API_KEY" \
  -d '{
    "model": "grok-4-1-fast",
    "input": [{"role": "user", "content": "Search X for the dominant crypto and tech narratives from '"$FROM_DATE"' to '"$TO_DATE"'. Return 12-15 distinct narrative threads. For each: 1) short label, 2) 3-5 representative @handles driving it, 3) 2-3 tweet permalinks, 4) rough mention-volume descriptor (niche / growing / saturating / cooling), 5) the strongest one-line bear case against it."}],
    "tools": [{"type": "x_search", "from_date": "'"$FROM_DATE"'", "to_date": "'"$TO_DATE"'"}]
  }'

c. WebSearch supplements (always run, even if XAI worked). Run 3 focused queries to triangulate:

• crypto narrative ${TO_DATE} — broad crypto sentiment
• AI agent crypto trend this week — AI/crypto intersection
• DefiLlama narrative tracker OR Kaito mindshare leaderboard — quantitative reference points Pull 1-2 concrete signals (project name, metric, link) from each query. Do not paraphrase — extract facts.

d. Memory diff. Extract narrative labels mentioned in the last 3 days of ### narrative-tracker log entries. You'll compare against them in step 4.

2. Score each narrative

For each distinct narrative (merge near-duplicates aggressively — "AI agents" and "agentic crypto" are the same), assign:

Drop any narrative that ends up IGNORE unless it's structurally important — noise reduction is the goal.

3. Detect transitions

Compare today's narratives to the last 3 days of logs:

• NEW — narrative wasn't in prior logs at all
• PROMOTED — phase moved up (e.g. Emerging → Rising)
• DEMOTED — phase moved down
• DEAD — was in prior logs, now absent from all signals

Transitions are the highest-value output — the point of a daily tracker is to catch inflection points, not re-report the zeitgeist.

4. Flag reflexivity

For each narrative, flag if the story itself is moving outcomes:

• Token prices moving on narrative alone (no fundamentals shift)
• Projects rebranding/pivoting to ride the narrative
• VCs publicly endorsing to manufacture legitimacy
• Prediction markets or on-chain flows reflecting narrative belief

Only flag explicit cases with a concrete example. "Reflexivity" without evidence is hand-waving.

5. Format the notification

Keep under 4000 chars. Lead with transitions and reflexivity — those are the decisions. Classification goes below.

*Narrative Tracker — ${today}*

TRANSITIONS
• NEW: <label> — <why it matters> — <link>
• PROMOTED: <label> Rising → Peak — <what flipped>
• DEMOTED: <label> Peak → Fading — <what cooled>
• DEAD: <label> — gone

REFLEXIVITY ALERT
• <narrative> — <concrete evidence the story is moving outcomes>

POSITIONS
• FRONT-RUN: <label> (mindshare 2 ↑↑, Bull) — <driver> — <bear case> — <link>
• RIDE: <label> (3 ↑, Bull) — <driver> — <bear case>
• FADE: <label> (5 → Cope) — <driver> — <reflexivity note>

MAP
Emerging: <labels>
Rising: <labels>
Peak: <labels>
Fading: <labels>

If absolutely nothing new or notable (no transitions, no reflexivity, no FRONT-RUN/FADE calls): send a one-line update instead of the full template — *Narrative Tracker — ${today}*: no phase transitions, map unchanged from <last_date>.

6. Send via ./notify

7. Log to memory/logs/${today}.md

Append a ### narrative-tracker section with the full structured output (not just the notification — include all narratives considered, even IGNOREd ones, so future diffs work). If a full run produced nothing actionable, log NARRATIVE_TRACKER_OK with the narrative labels seen (so tomorrow's diff still has a baseline).

Guidelines

• Quantitative over vibes. Every narrative gets mindshare 1-5 and a velocity arrow — no exceptions. If you can't score it, drop it.
• Transitions > classification. A daily tracker's value is catching moves, not listing the weather.
• Named drivers only. "Crypto Twitter is excited about X" is not a driver. "@handle + @handle + @fund" is.
• Position calls are mandatory for Emerging/Rising/Peak narratives. If signals are genuinely ambiguous or contradictory, WATCH is an acceptable call — but never omit a position entirely and never invent conviction you don't have.
• Ruthless dedup. Same narrative under two labels = one narrative. Merge, don't split.
• Call out cope. Manufactured narratives, coordinated shilling, and dead-cat bounces get tagged explicitly.
• Prioritize topics tracked in MEMORY.md over generic market chatter.

Sandbox note

The sandbox blocks outbound curl in many cases. Always read .xai-cache/narratives.json first (pre-fetched by the workflow with full network access). If the cache is missing, try direct curl — if that fails, use WebFetch on individual URLs. WebSearch always works for supplementary triangulation.

Environment Variables Required

• XAI_API_KEY — used by the pre-fetch step outside the sandbox; the skill reads the cached JSON. Optional — falls back to WebSearch.
• Notification channels configured via repo secrets (see CLAUDE.md).