narrative-tracker

<!-- autoresearch: variation B — sharper output (quantitative mindshare + velocity + explicit positioning calls, with multi-angle inputs from A, dedup/empty-state handling from C, and transition detection from D) -->

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. X/Twitter narratives — X.AI API (primary).** The primary signal is a direct `curl` to the X.AI Responses API with Grok's `x_search` tool — see **## Fetching** below for the full contract. `XAI_API_KEY` is injected into this skill's environment via `requires:`; it is present and valid, so this path is required whenever the key check prints `KEY_PRESENT`. Set the Bash tool `timeout` to ≥180000 when running the curl (x_search takes 30-120s) and capture the HTTP status:
```bash
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)
# Presence check uses the ${VAR:+x} modified expansion, NOT a bare $XAI_API_KEY — the bare
# form trips the Bash secret-expansion analyzer; the :+ form does not (it never puts the value on the line).
[ -n "${XAI_API_KEY:+x}" ] && echo KEY_PRESENT || echo KEY_UNSET
# Build the JSON payload to a file with jq (do NOT hand-assemble it), then POST the file.
# TWO SEPARATE commands on purpose: the jq (which interpolates $PROMPT/$FROM_DATE/$TO_DATE)
# is kept OUT of the ./secretcurl command — never pipe jq into secretcurl, and never put a
# $VAR in the secretcurl line, or the Bash permission analyzer blocks the network call.
# The `>` redirect to /tmp is fine in read-only mode (it is not a repo path; nothing reverts it).
PROMPT="Search X for the dominant crypto and tech narratives from ${FROM_DATE} to ${TO_DATE}. Return 12-15 distinct narrative threads. For each: 1) short label, 2) 3-5 representative @handles driving it, 3) 2-3 tweet permalinks, 4) rough mention-volume descriptor (niche / growing / saturating / cooling), 5) the strongest one-line bear case against it."
jq -n --arg p "$PROMPT" --arg fd "$FROM_DATE" --arg td "$TO_DATE" \
  '{model:"grok-4.6", input:[{role:"user",content:$p}], tools:[{type:"x_search",from_date:$fd,to_date:$td}]}' \
  > /tmp/xai-nt-payload.json
HTTP=$(./secretcurl -s -o /tmp/xai-nt.json -w '%{http_code}' --max-time 150 -X POST "https://api.x.ai/v1/responses" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer {XAI_API_KEY}" \
  -d @/tmp/xai-nt-payload.json)
echo "xai http=$HTTP bytes=$(wc -c </tmp/xai-nt.json)"
```
Run that block **verbatim** (do not hand-reassemble the JSON — the `jq -n` builder exists precisely so quoting/expansion can't break; keep the jq and the `./secretcurl` as two separate commands). The `echo "xai http=$HTTP ..."` line **must appear in your output** — it is your proof the call ran. On `HTTP=200` with a non-empty body, parse `/tmp/xai-nt.json` with `jq -r '.output[] | select(.type == "message") | .content[] | select(.type == "output_text") | .text'` and use that as the primary narrative signal (`SOURCE=api`).

**b. WebSearch / WebFetch fallback (last-resort only).** You may reach for this **only after** you have shown an `xai http=<code>` line proving Path A actually ran and returned a non-2xx code (or an empty body, or timed out). If you have no `xai http=` line, you did not run the call — go back and run it. Reach for the fallback **only** when Path A genuinely fails — `KEY_UNSET`, a non-2xx HTTP code, an empty parse, or a timeout. It is lower quality (WebSearch favours old high-engagement posts) and is **never co-equal** with Path A. Log the fetch failure to `memory/logs/${today}.md` recording the **true reason** — `key-unset` | `http-<code>` | `empty` | `timeout` — never "XAI_API_KEY unavailable" when the key was set (a slow curl is a `timeout`, not a missing key). Then compile narratives via WebSearch (`crypto narrative ${TO_DATE}`, `AI agent crypto trend this week`) and WebFetch on individual tweet URLs; discard anything older than the 3-day window.

**c. Quantitative reference points (supplement).** Independently of the fetch path, cross-check mindshare against external quantitative benchmarks with one WebSearch: `DefiLlama narrative tracker` OR `Kaito mindshare leaderboard`. Pull 1-2 concrete numbers (project name, metric, link) to calibrate the mindshare scores in step 2. This is a calibration cross-check, **not** a narrative source. 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:

| Field | Scale | How to decide |
|---|---|---|
| **Mindshare** | 1-5 | 1 = fringe, 3 = known in the sector, 5 = dominating timelines. Base on count of distinct drivers + whether you had to dig or it surfaced unprompted. |
| **Velocity** | ↑↑ / ↑ / → / ↓ / ↓↓ | Compared to the 3-day window or prior log entries. ↑↑ = tripled in attention, ↓↓ = was loud 3 days ago, now absent. |
| **Phase** | Emerging / Rising / Peak / Fading | Use the velocity + mindshare combo. Emerging = low mindshare, high velocity. Peak = high mindshare, flat/down velocity. Fading = high mindshare last week, now ↓. |
| **Sentiment** | Bull / Mixed / Bear / Cope | Cope = bag-holder energy, bear narratives dressed as bull takes. |
| **Drivers** | 2-3 named | Accounts, projects, or funds amplifying it. Include @handles. |
| **Bear case** | 1 line | The sha