Skip to main content
Glama

Intact

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).

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds significant behavioral details: it reads from daily snapshots, uses a 60-day TTL, explains that decay numbers come from daily closes not intraday, and that gaps mean no scan. 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 front-loaded with the purpose and structured with explicit sections (RESPONSE, LIMITS). Every sentence adds value, and while it is long, the detail is necessary given no output schema. It is well-organized and concise 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?

With no output schema, the description thoroughly explains the return structure: tracked[], expired[], snapshot_dates[], including fields like trend, decay_pp_per_day, and lifespan_days. It also covers limits like the 60-day TTL. The description is fully complete for effective tool invocation.

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 both parameters having clear descriptions. The tool description adds default values and range for days (clamp 2-30) and options for window, but these are already present in the schema description. Thus, the description does not add meaning beyond the schema, leading to a baseline score of 3.

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: 'edge persistence and decay telemetry built from daily polymarket_edges snapshots.' It answers a specific question ('how long has this edge existed and is it shrinking?') and distinguishes itself from sibling tools by focusing on edge tracking and decay analysis.

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 provides explicit context for when to use the tool: to differentiate fresh edges from old ones. It implies usage by stating 'a fresh wide edge and a 3-week-old wide edge are different trades.' While it doesn't explicitly exclude alternatives, it gives clear guidance on the telemetry aspect.

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

All Intact 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

A4.1/5.0
Disambiguation3/5

Most tools have strong, detailed descriptions with explicit usage guidance, but a few clusters are genuinely ambiguous: ask_pipeworx_beta is currently an exact duplicate of ask_pipeworx, and the Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker) overlap heavily in purpose. The descriptions help differentiate them, but an agent could still easily select the wrong variant.

Naming Consistency4/5

All tool names are snake_case and most follow an imperative verb-first pattern such as resolve_entity, subscribe, or validate_claim. A few noun-style names like entity_profile, bet_research, and interaction_count deviate, but the consistent underscore style and clear prefixes like polymarket_ and pipeworx_ keep the set predictable.

Tool Count2/5

At 33 top-level tools, the surface is heavy, and several tools are near-duplicates or narrow variants of the same core capability. The broad scope explains some of the count, but the agent-facing API would be cleaner with fewer, more consolidated entry points.

Completeness5/5

The set provides strong lifecycle coverage for its main workflows: querying and grounding, deep research, entity resolution, company profiling, comparisons, Polymarket edge analysis with fill-risk checks, memory storage, and subscription management. There are no obvious dead ends that would prevent an agent from completing a typical task.

Resources