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Polymarket Edge Tracker

polymarket_edge_tracker
Read-onlyIdempotent

Edge persistence and decay telemetry built from daily polymarket_edges snapshots. Answers "how long has this edge existed and is it shrinking?" — a fresh wide edge and a 3-week-old wide edge are different trades (the latter is wide for a reason nobody is willing to take). Args: days (lookback, default 14, max 30), window (snapshot family, default "1wk"). RESPONSE: tracked[] = every opportunity in the LATEST snapshot with its full edge_pp_net time-series across prior snapshots, first_seen, trend (new | widening | stable | decaying) and decay_pp_per_day (both computed on |edge_pp_net| — the value itself is signed by trade direction, negative = SELL YES); expired[] = opportunities that appeared in earlier snapshots but are GONE from the latest (closed, resolved, or arbed away) with their lifespan_days — the median lifespan is your competition clock; snapshot_dates[] = which days actually have data (snapshots are written when polymarket_edges runs on a cache-miss, so gaps mean nobody scanned that day). LIMITS: history depth is bounded by the 60-day snapshot TTL and starts from when snapshotting was enabled; decay numbers come from daily closes of edge_pp_net (net of default slippage), not intraday.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNoLookback in days (default 14, clamp 2-30).
windowNoWhich polymarket_edges window family to read snapshots for: 24hr | 1wk | 1mo (default 1wk).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.4/5.0
Behavior5/5

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

The description discloses numerous behaviors beyond annotations: snapshot TTL (60 days), decay calculation from daily closes, snapshot generation triggers (cache-miss), and response fields. This provides rich operational context that annotations (readOnlyHint, etc.) do not cover.

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 front-loaded with purpose and key question, then breaks down response structure. It is verbose but every sentence adds information. Could be slightly more concise, but overall well-organized.

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

Completeness5/5

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

Despite lacking an output schema, the description explains all response fields (tracked, expired, snapshot_dates) and their meanings. It also covers limitations (TTL, decay source). No critical missing context for an agent to use the tool correctly.

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%, so the schema already documents both parameters. The description adds marginal value by explaining 'lookback' and 'snapshot family' in context, but mostly restates what the schema says (defaults, options). Baseline 3 is appropriate as the description does not significantly deepen parameter understanding.

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 states the tool provides 'edge persistence and decay telemetry' and answers a specific question about edge freshness. It clearly identifies the resource (edge time-series) and distinguishes from siblings like polymarket_edges and polymarket_arbitrage.

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 implies when to use (to understand edge persistence and decay) and gives a concrete motivation (fresh vs old edge difference). However, it does not explicitly exclude scenarios or name alternative tools for comparison, missing the 'when-not' guidance for a top score.

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

B3.1/5.0
Disambiguation4/5

Most tools have distinct purposes, especially within the Roblox and Pipeworx domains. However, the three variants of ask_pipeworx (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded) are very similar and could cause confusion, as could deep_research vs ask_pipeworx.

Naming Consistency3/5

Naming conventions are mixed: snake_case (user_followers_count), verb_noun with underscores (ask_pipeworx), and camelCase (recall, forget). Roblox tools follow a consistent 'user_' prefix, but Pipeworx tools lack a uniform pattern.

Tool Count2/5

41 tools is excessive for a server named 'Roblox'. The majority of tools are Pipeworx data utilities, which are unrelated to the server's apparent focus. This overloading undermines coherence.

Completeness3/5

Coverage within the Roblox domain is basic (user profiles, friends, games) but misses common features like asset details or group management. Pipeworx appears comprehensive for data lookups, but the overall set lacks unified domain completeness.