Pm Manipulation

Read memory/MEMORY.md for context. Read the last 3 days of memory/logs/ to avoid re-flagging markets you already covered, and to compare current readings against prior ones.

Voice

If soul/SOUL.md and soul/STYLE.md are populated, match the operator's voice in the notification and write-up. If empty or absent, use a clear, direct, neutral tone. The methodology itself is the same either way.

Why this skill exists

English-language coverage of any prediction market is dense for US politics, sparse for everything else. Election-, geopolitics-, and conflict-related markets are most often pushed by actors closer to the home country than to the English-speaking financial press. By the time a coordinated narrative lands in mainstream financial outlets, the trade is over. Local-language press, regional outlets, and country-specific Telegram / X channels move first — sometimes by 24–72h.

This skill looks at the past 3 days of activity on a configurable prediction-market platform and asks: where does the price action diverge from organic English-press coverage, and does a multilingual sweep reveal a narrative push that explains it?

Configuration

Read memory/topics/prediction-markets.md if it exists for an optional ## Platform line naming the target API root. Defaults to Polymarket's public Gamma + CLOB APIs (gamma-api.polymarket.com, clob.polymarket.com, data-api.polymarket.com). The candidate selection, scoring rubric, and multilingual sweep are platform-agnostic; only the endpoints differ.

The keyword filter and locale table below are starting points — the operator can edit memory/topics/prediction-markets.md to add ## Keywords and ## Locales sections that override the defaults.

Network note

curl works — there is no network sandbox. For every curl call, if it fails or returns empty, use WebFetch as a fallback for a flaky public GET. The Polymarket APIs above are public (no auth). For news searches, prefer WebSearch with locale-specific queries — a built-in Claude tool that needs no curl.

Steps

1. Build the candidate set (markets active in past 3 days)

Pull the most-active markets across the categories most prone to manipulation: politics, geopolitics, conflict, elections (national and regional), regulatory rulings, and resolution-disputed markets.

# Top markets by 24h volume — repeat for last 3 days using volume24hr / volume1wk fields
curl -s "https://gamma-api.polymarket.com/markets?closed=false&order=volume24hr&ascending=false&limit=30"

# Also fetch by 7d volume to catch slower-burn manipulation
curl -s "https://gamma-api.polymarket.com/markets?closed=false&order=volume1wk&ascending=false&limit=30"

From the union of those two lists, pick 6–10 candidates that meet at least one of:

• Question references a non-US country, region, or conflict
• Question references a regulatory body, election, or coup/conflict event
• 7d volume > $500k AND 24h volume > $50k (real money, not just liquidity-mining)
• Slug contains keywords (default set; operator can override in memory/topics/prediction-markets.md): russia, iran, israel, china, taiwan, ukraine, venezuela, argentina, mexico, brazil, india, pakistan, nigeria, france, germany, italy, spain, eu-, nato, cartel, coup, nuclear, assassination, ceasefire, election, vote, referendum, oracle, dispute, umip

Skip anything sports, weather, or pure crypto-price (BTC > $X by Y) — those have different manipulation signatures and aren't this skill's job.

2. Pull 3-day price + trade data per candidate

For each candidate market, get the YES-token (clobTokenIds[0]) and pull 3-day price history at hourly fidelity:

curl -s "https://clob.polymarket.com/prices-history?market=$TOKEN_ID&interval=1w&fidelity=60"

Compute, from the past 72h window only:

• 3d open / close / high / low (price 0.0–1.0)
• Largest single-hour move (absolute pp change)
• Move concentration — what % of the 3d net move happened in the single largest 6h block? If > 70%, flag concentrated-move.
• Volume spike ratio — (peak hour volume) / (median hour volume). If > 8x, flag volume-spike.
• Direction inversion — did price reverse > 5pp within the 72h window? Flag reversal — common when a manipulator unwinds.

Also pull the trades feed if available (some markets only) for whale concentration:

curl -s "https://data-api.polymarket.com/trades?market=$TOKEN_ID&limit=500"

Compute whale share — % of 3d volume from the top-3 wallet addresses. If > 40%, flag whale-concentrated.

If the trades endpoint doesn't return per-market data, skip whale-share for that candidate — note it in the report rather than failing.

3. Pull comments and detect coordination patterns

For each candidate, fetch comments from the past 3 days:

# Get the event id first (comments live on Event, not Market)
curl -s "https://gamma-api.polymarket.com/events?slug=$EVENT_SLUG&limit=1"

# Top comments by reactions
curl -s "https://gamma-api.polymarket.com/comments?parent_entity_type=Event&parent_entity_id=$EVENT_ID&limit=50&order=reactionCount&ascending=false"

# Most recent
curl -s "https://gamma-api.polymarket.com/comments?parent_entity_type=Event&parent_entity_id=$EVENT_ID&limit=50&order=createdAt&ascending=false"

Filter to comments from the last 72h (createdAt within window). Then look for:

• Burst posting — > 10 comments from accounts with usernames matching the same regex pattern (e.g. user\d{4,}, common spam-bot signature) within a 6h window. Flag bot-burst.
• Narrative concentration — > 40% of top-reacted comments push the same one-sided talking point with near-identical phrasing. Flag narrative-push.
• Cross-market spam — same usernames repeating identical text across multiple unrelated markets (compare against any logged comments from prior pm-manipulation runs). Flag cross-market-spam.

Apply a reactionCount > 1 pre-filter before counting "real" reactions, but do count low-reaction comments toward bot-burst and narrative-concentration signals — that's exactly where the spam shows up.