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Cdc

by io.github.pipeworx-io

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. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the readOnly and other hints, the description details response fields (tracked, expired, snapshot_dates), their meanings, and computation approach (e.g., decay from daily closes, edge_pp_net signed by direction). This provides substantial behavioral context.

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 fairly concise given the complexity, with clear sections for purpose, response structure, and limits. It could be slightly tighter, but each sentence adds value.

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 no output schema, the description thoroughly documents the response structure (tracked, expired, snapshot_dates) with key field explanations. It also covers data limits and sources, making it self-contained for agent usage.

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?

The description adds value over the schema by explaining the 'window' parameter as 'snapshot family' and providing explicit defaults and bounds (days default 14, max 30; window default '1wk'). Schema coverage was already 100%, but the description enhances clarity.

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: providing edge persistence and decay telemetry from daily polymarket_edges snapshots. It answers a specific question about edge longevity vs. width, distinguishing it from sibling tools like polymarket_edges.

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 when to use (e.g., for historical edge analysis) and notes limits (60-day TTL). However, it does not explicitly contrast with siblings or state when not to use.

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
Disambiguation3/5

Tools like ask_pipeworx, ask_pipeworx_grounded, and deep_research serve similar querying purposes, and there is overlap among prediction market tools (e.g., polymarket_arbitrage, polymarket_edges). However, descriptions help differentiate them, so agents can usually select the correct one.

Naming Consistency3/5

Most tools use snake_case with verbs (ask_, resolve_, validate_), but there are noun-style exceptions (entity_profile, recent_changes, pipeworx_trending) and mixed naming among Polymarket tools. The pattern is readable but not fully consistent.

Tool Count2/5

With 32 tools, the server feels bloated, especially given the name 'Cdc' implies a focus on CDC data, yet many tools cover unrelated domains like prediction markets and company profiles. Several tools could be consolidated or removed to align with a narrower scope.

Completeness3/5

The CDC domain is thinly covered with only search and get for datasets, lacking upload or advanced filtering. Company financials are limited to basic fundamentals from 10-Ks. Prediction markets are well-covered with arbitrage, edges, and fill risk. The server has notable gaps in its core domain.

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