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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

A4.2/5.0
Behavior4/5

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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds concrete behavioral details: snapshot-based, daily closes, 60-day TTL, decay computation method. No contradictions 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 thorough but well-structured, with clear sections for response fields and limitations. A slight overuse of dashes and parentheses could be tightened, but overall it is effectively front-loaded.

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?

No output schema exists, yet the description comprehensively explains the response structure (tracked[], expired[], snapshot_dates[]) and their fields. It also notes data limitations and computation details, making it self-sufficient for an agent.

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?

Input schema already provides full coverage with descriptions for both parameters. The description restates defaults and clamping but adds no new semantic meaning beyond what the schema offers, so baseline score 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 provides 'edge persistence and decay telemetry' and answers a specific question. It distinguishes itself from the sibling 'polymarket_edges' by focusing on historical persistence and decay, not just current 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 explains when to use this tool (to evaluate edge longevity and decay) and contrasts fresh vs. old edges. It implicitly differentiates from 'polymarket_edges' but does not explicitly list alternatives or 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

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct function or data domain, from prediction markets (bet_research, polymarket_*) to company research (entity_profile, compare_entities) to data queries (query, dataset_info). No two tools have overlapping purposes; meta-tools like ask_pipeworx and deep_research are clearly differentiated.

Naming Consistency5/5

All tool names follow a consistent snake_case pattern with descriptive verbs (e.g., search_datasets, validate_claim, remember). No mix of conventions like camelCase or inconsistent verb choices.

Tool Count4/5

At 33 tools, the server covers a broad range of capabilities (data retrieval, AI visibility, prediction markets, company profiles, subscriptions, etc.). While slightly above the ideal range, the count is justified by the breadth of functionality and no tool feels redundant.

Completeness4/5

The tool set provides comprehensive coverage for data discovery, retrieval, and analysis across multiple domains (SEC, FDA, FRED, Paris Open Data, prediction markets, etc.). Minor gaps exist (e.g., no update/delete for Paris Open Data), but the primary focus on reading and analysis is well-served.

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