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signalpulse

Deliver institutional-grade trading and prediction-market intelligence with multi-engine reads across crypto, FX, macro-events, prediction markets, and sports.

Instructions

SignalPulse: Institutional-grade trading & prediction-market intelligence for agents. Calibrated multi-engine reads across crypto, FX, macro-events, prediction markets (Polymarket/Kalshi/Manifold/PredictIt) and sports — de-vigged sportsbook consensus plus proprietary xG/EPA/Statcast/weather analytics. Agent analysis tier; the curated, sized, tracked calls are the premium service.

Coverage: Global

Endpoints: • sample (FREE): FREE pick-of-the-day — a full-depth sample of the sports engine on one featured matchup. No payment, no key. • game ($1.00): Deep single-match analysis: de-vigged sportsbook consensus + proprietary stats/weather analytics + props; 3 ranked +EV plays with full reasoning. • predmarket ($0.50): Cross-venue prediction-market superforecaster across Polymarket/Kalshi/Manifold/PredictIt; calibrated probabilities, edge and full analysis (props included). • crypto ($0.50): Crypto market scan — multi-layer read of BTC/ETH and the top-25: regime, breadth, on-chain cycle, derivatives positioning, funding extremes, liquidations. • market ($0.50): Cross-asset scan across FX majors, metals and equity indices — the single best opportunity with full multi-layer rationale. • forex ($0.50): FX scan across 28 pairs — ICT structure, carry, COT positioning, real yields and session timing. • event ($0.50): Macro-event scan — directional read around a scheduled print (NFP/CPI/Fed) using market and prediction-market signals.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesWhich endpoint to call. Options: sample | game | predmarket | crypto | market | forex | event
langNoResponse language code (en | es | fr | de | zh | hi | ar | pt | ja | ko | etc.)
sportNomlb | nba | nfl | nhl | wnba | soccer_epl | tennis | mma | esports
eventNomatchup hint, e.g. yankees-red-sox
market_typeNooptional focus: moneyline | spread | total | props
categoryNocrypto | economics | geopolitics | politics | sports | esports
horizonNoshort | mid | long
styleNoscalp | intraday | swing
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool offers a 'premium service' with 'curated, sized, tracked calls' and explicitly mentions pricing for endpoints ($1.00, $0.50). It does not hide any major behavioral traits, though it could note rate limits or authentication requirements.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with an introductory sentence and bullet-point-like endpoints. It front-loads the main purpose. However, it includes pricing details that, while useful, could be considered verbose for a tool description. Minor redundancy exists (e.g., repeating 'Agent analysis tier').

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema or annotations, the description covers most aspects: purpose, endpoints, parameters, and pricing. It lacks details on the output format or expected response structure, which would help an agent process the results. The description is otherwise thorough for a complex tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds significant meaning beyond the parameter names. For example, it explains each action (e.g., 'game ($1.00): Deep single-match analysis...') and provides context for optional parameters like sport and event. This goes well beyond the schema's brief descriptions.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'institutional-grade trading & prediction-market intelligence for agents' with specific coverage of crypto, FX, macro-events, prediction markets, and sports. It lists endpoints (sample, game, predmarket, etc.) and their functions, making it easy to distinguish from sibling tools such as cryptopulse or macropulse.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly guide when to use signalpulse over its many siblings. It lists endpoints but lacks 'when-to-use' or 'when-not-to-use' advice. For example, it does not compare signalpulse against alphapulse or marketpulse, leaving the agent to infer usage from the endpoint list alone.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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