Results for “promoter-prediction”

Promote project-specific memories into strict, small global memory only when they are cross-project, stable, useful, safe, and worth the global context cost. Load when the user says make this global, remember across projects, save this globally, or promote this learning.

Graduate a proven pattern from auto-memory (MEMORY.md) to CLAUDE.md or .claude/rules/ for permanent enforcement.

Use when making a forward-looking claim with a checkable outcome (reply within 24h, error rate will drop, this skill will see more use) — record to state/predictions.jsonl with a review horizon so reflection can grade you later. Closes the in-the-moment double-loop.

Compares prediction market probabilities from Polymarket with options-implied probabilities to identify mispricing signals and potential arbitrage opportunities.

Walk into the negotiation with a plan, not a hope. Sets your walk-away and your target, builds the concession ladder (what you trade and what you get for it), maps their likely asks, and drafts the responses that protect price and terms. Built for B2B sales teams, customizable to your CRM and your deal process. Trigger on "prep me for this negotiation", "the prospect wants a discount", "what should I concede", "build my concession ladder", "hold price on a new deal", or any pre-negotiation planning.

Extract warm prospects from competitor and industry post engagers across LinkedIn, Twitter, and blogs

This skill should be used when building prediction market integrations, implementing betting functionality, or querying Polymarket odds. Covers market search, odds checking, and position management.

Use to define what actually predicts support performance in your organisation and build a hiring profile around validated predictors — structured work samples, not vibes. Trigger for "hiring profile", "what should we look for in support hires", "interview scorecard for agents", "reduce bad hires", "work sample test", screening criteria review, or checking whether your interview process predicts ramp and QA.

Quantifies market top probability using O'Neil Distribution Days, Minervini leading stock deterioration, and Monty defensive sector rotation, producing a 0-100 composite score with risk zone classification for tactical 2-8 week timing signals.

Generates at most one token recommendation and one prediction-market pick per run, each with a falsifiable thesis, entry, sizing, and kill criterion. Returns NO_PICK when no candidate meets the bar.

Price-to-win lens using GSA CALC+, BLS OEWS, and incumbent USASpending award patterns for a pursuit. Use when user asks for realism checks or competitive pricing posture before proposal — draft skill, not production-verified.

Sports betting fundamentals including spreads, moneylines, totals, parlays, teasers, props, and futures. Use when analyzing sports betting markets, converting odds formats, evaluating bet types, or building a sports betting strategy. Also trigger for 'point spread', 'moneyline', 'over under', 'parlay', 'prop bet', 'teaser', 'sports odds', or 'sportsbook'.

Creates a presenter-mode deck with speaker notes, theme switching, and a popup teleprompter.

Prediction markets data - Polymarket, Kalshi markets, prices, positions, and trades. Use when: the user needs market data, stock analysis, watchlists, or portfolio workflows.

The instruction to profile before optimizing survives because intuition about

v4.1.0 reward function redesign to fix overtrading and DSR dominance

Derive selection thresholds from market data instead of hardcoding. Trigger when: (1) reviewing hardcoded parameters, (2) volume/price thresholds seem arbitrary, (3) selection returns too many/few candidates.

Use when tuning RL reward function weights, fixing reward hacking, or addressing P&L gradient issues

COBRA v1.1 — Arena Sprint Predator. Trades the single most dominant SM asset with maximum conviction. Fee-optimized maker orders. Wider DSL lets positions breathe. Designed to win Arena weeks.

Analyze auto-memory for promotion candidates, stale entries, consolidation opportunities, and health metrics. Use when the user runs /si:review or asks what has been learned and what should be promoted or pruned.