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Prediction Markets Quant

by com.predictionmarketspicks

Base Rate Gap

base_rate_gap
Read-only

Compare a market price against the historical base rate for a class of events and get the gap in percentage points plus a signal and sample-size quality. Pass either a known base-rate id (one of: incumbent_reelected, fed_hold_unemp_below_4, fed_cut_cpi_above_3, recession_called_12mo, sp500_positive_year, bitcoin_above_100k_eoy, gdp_growth_above_2, cpi_above_3, senate_incumbent_wins_primary, vix_below_20_eoy, interest_rate_cut_next_meeting, major_sports_upset) or your own baseRateValue. Use for "how does this price compare to history", "is the market ignoring the base rate", "historical frequency vs market".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseRateIdNoKnown base-rate id to look up (includes sample size + source).
marketPriceYesCurrent market price in cents / implied probability % (0–100). Accepts 55, "55%", "55¢", "$0.55", 0.55 or American odds (+120 / -150) — all read as 55%.
baseRateValueNoYour own base rate in % (0–100), used when no baseRateId is given.

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, so the agent understands this is a safe read operation. The description adds value by describing the output (gap, signal, sample-size quality) and the two input modes (by ID or custom value). No contradiction with annotations.

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

Conciseness5/5

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

Two sentences, front-loaded with purpose, no redundancy or filler. Every word earns its place.

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?

For a read-only tool with no output schema, the description covers the core logic, input modes, and typical use cases. It could briefly mention the return structure (e.g., that output includes numerical gap and signal type) but is largely sufficient.

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

Parameters3/5

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

Schema coverage is 100%—all three parameters are described in the schema. The description adds by listing the enum values in text and explaining the flexible marketPrice format, but these are already in the schema. It provides convenience but not novel semantic depth beyond the schema.

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 verb ('compare'), the resources ('market price against historical base rate'), and the outputs ('gap in percentage points plus a signal and sample-size quality'). It is specific and distinguishes from sibling tools like 'calculate_ev' or 'edge_alerts' which have different purposes.

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

Usage Guidelines4/5

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

The description provides explicit use cases: 'how does this price compare to history', 'is the market ignoring the base rate', 'historical frequency vs market'. It does not explicitly exclude any scenarios or mention alternatives, but the guidance is clear and context-rich.

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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TDQS

A3.9/5.0
Disambiguation4/5

Most tools target distinct workflows with explicit usage hints, such as best_available vs who_do_i_draft vs compare_players. The main risk is the cluster of 'edge' tools—calculate_ev, scan_mispricings, edge_alerts, nfl_edge, nfl_prop_edge—but descriptions narrow them by venue, asset, and scope well enough.

Naming Consistency3/5

All names use lowercase snake_case, but there is no stable verb_noun pattern: some are verbs (calculate_ev, scan_mispricings), many are noun phrases (draft_board, market_pulse, nfl_edge), and one is a full question (who_do_i_draft). The nfl_* prefix adds structure, but overall the convention is mixed though still readable.

Tool Count3/5

24 tools is on the heavy side and the set spans two fairly distinct domains: prediction-market edge tools and fantasy-football draft tools. Most tools serve a distinct function, but several 'edge' tools and the eight fantasy tools could feel redundant if consolidated.

Completeness4/5

The set covers the core prediction-market workflow: base rates, Bayesian updates, EV, Kelly sizing, mispricing scans, arbitrage, and vertical signals, plus a full fantasy-draft surface. Notable gaps are generic market/price lookup and portfolio-level tracking, but agents can work around these.

Resources