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narrative-tracker

Track rising, peaking, and fading crypto/tech narratives with quantitative mindshare + velocity signals and explicit positioning calls

skills/narrative-tracker/SKILL.md

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<!-- 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