Skip to main content
Glama

Epa Echo

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. Added
  2. Removed
  3. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true and destructiveHint=false. The description adds important behavioral details beyond annotations: limits on history depth (60-day TTL, dependent on snapshotting start), that decay numbers are from daily closes (not intraday), and the meaning of negative edge_pp_net values. 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 fairly long but well-structured: purpose first, then detailed response format (tracked, expired, snapshot_dates), then limitations. Uses inline code for field names. Could be slightly tighter, but every sentence adds value. Good front-loading.

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?

Although there is no output schema, the description thoroughly explains the response structure: three arrays with fields like trend, decay_pp_per_day, first_seen, lifespan_days, etc. It covers what to expect from each part of the output. For a time-series analysis tool, this is appropriately complete.

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% with descriptions for days (lookback, default 14, clamp 2-30) and window (24hr|1wk|1mo, default 1wk). The description mentions these parameters redundantly but adds no new semantic information beyond the schema. Baseline 3 is appropriate.

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 uses specific verbs ('answers', 'track') and resource ('edge persistence and decay telemetry'), distinguishing it from siblings like polymarket_edges (current 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 this tool via the example comparing fresh vs. 3-week-old edges, and suggests that newer edges may be more informative. However, it does not explicitly state when not to use it or directly name alternatives, though sibling tools like polymarket_edges are implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Epa Echo toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.9/5.0
Disambiguation2/5

ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded form a tight cluster, and the beta variant is explicitly identical to ask_pipeworx today. Several meta-tools like discover_tools, suggest_questions, and deep_research also overlap in discovery-oriented usage, so an agent must read carefully to pick the right one.

Naming Consistency3/5

Names are uniformly lowercase with underscores and mostly descriptive, but the conventions are mixed: verb_noun tools like validate_claim and list_subscriptions sit alongside noun_phrase tools like entity_profile and polymarket_arbitrage, plus bare verbs like remember and subscribe. It is readable but not a single predictable pattern.

Tool Count2/5

36 tools is well above the 25+ threshold, and the surface spans unrelated domains: EPA ECHO data, general Pipeworx research, Polymarket betting, memory, npm scanning, and AI visibility checks. For a server named 'Epa Echo', most tools feel out of scope and the collection seems like several separate servers merged together.

Completeness4/5

The EPA ECHO subset provides a solid facility-search, violations, compliance-history, and enforcement-action lifecycle. The broader Pipeworx surface also covers lookups, grounded answers, deep research, entity profiling, subscriptions, and memory, with only minor workaround-level gaps such as no dedicated ECHO permit/emissions detail tool.

Resources