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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

A4.6/5.0
Behavior5/5

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

The description adds significant behavioral context beyond the annotations. It explains that the tool reads snapshots, computes decay, and returns tracked, expired opportunities, and snapshot dates. It also clarifies the signed nature of edge_pp_net and the limitations of decay computation. 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 clear sections: core question, arguments, response breakdown, limits. It front-loads the purpose and uses readable formatting. Some minor redundancy, but overall concise enough for the complexity.

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?

Given the absence of an output schema, the description fully compensates by detailing the response structure (tracked, expired, snapshot_dates) and their fields. It also covers edge cases like gaps in snapshots and limitations, making it highly complete.

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?

Schema coverage is 100%, but the description adds value by explaining default and clamp behavior for 'days' (default 14, max 30) and the default for 'window' (1wk). It also clarifies the snapshot family concept, which the schema's description only labels as 'window family'.

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: answering how long an edge has existed and whether it is shrinking. It distinguishes itself from sibling tools like polymarket_edges by focusing on persistence and decay telemetry, not just current edge values.

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 implicitly guides usage by focusing on edge persistence analysis, and mentions limitations such as the 60-day TTL and daily closes. While it doesn't explicitly state when not to use it, the context of siblings and the detailed output structure provide clear usage context.

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

A3.5/5.0
Disambiguation2/5

Several clusters of tools have heavily overlapping purposes: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, discover_tools, and suggest_questions all route/discover questions across the same 5,743 tools, differing mainly in mode or betaness. The polymarket_* family (arbitrage, edges, edge_tracker, fill_risk, kalshi_spread) similarly overlaps in prediction-market edge detection. An agent would frequently struggle to pick the right tool from these near-duplicate groups despite verbose descriptions.

Naming Consistency3/5

Snake_case is used throughout, but patterns are mixed: some tools are verb-first (ask_pipeworx, find_sites, recall, forget, subscribe), some are noun phrases (current_conditions, entity_profile, bet_research), and some use a domain prefix (pipeworx_*, polymarket_*). The version-suffixed ask_pipeworx_beta is also a minor deviation from the otherwise clear descriptive style.

Tool Count2/5

34 tools is excessive for a server named 'Usgs Water' since only 3 tools (current_conditions, daily_values, find_sites) actually relate to USGS water data. Even as a general Pipeworx platform server, the count is heavy, with many tools dedicated to niche prediction-market trading and meta-routing that inflate the surface.

Completeness1/5

Against the stated USGS Water purpose, the surface is severely incomplete: it lacks water-quality samples, groundwater data, site metadata details, historical statistics, rating curves, parameter code lookup, and flood/alert data. The remaining 31 tools cover an entirely different domain (SEC filings, drugs, prediction markets, npm scans, memory), so agents using this server for water data will hit dead ends almost immediately.