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augiemazza

Varrd

by augiemazza
OverviewSchemaRelated ServersScoreDiscussions
Python
Remote

varrd_edges

Read-onlyIdempotent

Access Bonferroni-corrected trading edges with full transparency. Select depth from free market status to complete analytics including setup code and equity curve.

Instructions

Browse VARRD's library of statistically validated trading edges — strategies discovered and tested with institutional-grade methodology, running 24/7 against live market data.

THREE TIERS: depth=0 (FREE): See which markets have edges firing right now, pending bar close, or actively in trades. Markets and status only — no direction, no stats. Get a sense of what's live. depth=1 ($0.50): Unlock direction, occurrence count, EV/trade, stop-loss, take-profit, hold horizon, and current entry prices for ALL active edges in one request. depth=2 ($1 per edge, $5 for all): Full methodology — the actual formula, setup code, how the edge was discovered, edge decay analysis, complete performance analytics (Sharpe, drawdown, equity curve, profit factor). Machine-readable so any AI can audit the statistical rigor. Includes drill-down sections (free after purchase): setup_code, horizons, analytics, occurrences, and view (interactive chart link for your user, 15 min).

Every edge in this library is Bonferroni-corrected, tested against both zero returns and market baseline, with K-tracking to prevent p-hacking. Out-of-sample validated. Full transparency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNo0=free (markets + status), 1=$0.50 (direction, stats, trade levels for ALL active edges), 2=$1/edge or $5/all (full methodology + performance). Cheaper than a coffee.
edge_idNoSpecific edge ID for depth 1 or 2 detail. Omit to see all edges.
marketNoFilter by market symbol (e.g. 'ES', 'GC'). Omit to see all.
statusNoFilter by status: 'firing', 'pending', 'active', or omit for all.
directionNoFilter by direction: 'LONG' or 'SHORT'.
timeframeNoFilter by timeframe: '60min', '120min', '240min', '480min', 'daily', 'weekly'.
asset_classNoFilter by asset class: 'futures', 'equities', 'crypto'.
sectionNoDrill into a specific section of a depth=2 edge (free after purchase). Options: setup_code, horizons, analytics, occurrences, view. Omit to get the overview directory.

Tool Definition Quality

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and no destruction. The description adds extensive behavioral context: tiered pricing, Bonferroni correction, K-tracking, out-of-sample validation, and drill-down sections (free after purchase). 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.

Conciseness4/5

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

The description is well-structured with tiered headings and bullet-like lists, front-loading the purpose. However, it is verbose with excessive marketing language ('Cheaper than a coffee' in schema, but description also has some fluff). Could be trimmed slightly without losing essential info.

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 8 parameters with 100% schema coverage and no output schema, the description thoroughly covers behavior, tiers, filtering, and drill-downs. It lacks explicit mention of response format (list vs object) but the detail on what each tier returns compensates. Nearly complete for the tool's complexity.

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

Parameters4/5

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

With 100% schema coverage, baseline is 3. The description adds significant meaning beyond the schema: explains depth parameter with pricing details, clarifies edge_id usage for depth 1-2, and elaborates on section parameter with 'free after purchase' and examples. This extra context justifies a higher score.

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 browses VARRD's library of statistically validated trading edges, with specific verb 'Browse' and resource 'library of edges'. It distinguishes from sibling tools like varrd_ai (likely interactive) and get_hypothesis (hypothesis generation) by focusing on edge library browsing.

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 explicitly outlines three tiers (depth=0,1,2) with pricing and what each returns, guiding agents on when to use each level. It implies usage for browsing edges but does not explicitly contrast with sibling tools or state when not to use this tool, leaving a small gap.

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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