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Greynoise

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

A3.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, non-destructive. Description adds behavioral nuances: snapshot TTL (60-day), decay from daily closes (not intraday), gaps meaning no scan that day. 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.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Description is lengthy with technical details but structured clearly with sections (args, RESPONSE, LIMITS). However, it could be more concise; some sentences are dense and require careful parsing.

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?

No output schema, but description thoroughly explains the return fields (tracked[], expired[], snapshot_dates[]) with key attributes and semantics, making the tool's response predictable.

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 covers 100% of parameters with descriptions. Description only reiterates defaults and max days without adding new meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the tool provides 'edge persistence and decay telemetry' and answers a specific question about edge age and shrinkage. It distinguishes itself from sibling polymarket_edges by focusing on temporal analysis rather than 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 Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies usage for judging trade quality based on edge persistence (fresh vs. old wide edge) but lacks explicit when-to-use or when-not-to-use instructions. No direct mention of alternatives like polymarket_edges for current snapshots.

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

A3.7/5.0
Disambiguation2/5

ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, creating a true duplicate entry point, and the prediction-market cluster (bet_research, polymarket_arbitrage, polymarket_edges, polymarket_kalshi_spread) all detect mispricings with heavily overlapping descriptions. The detailed docs help, but an agent choosing among these will frequently misselect.

Naming Consistency3/5

The set mixes verb-first names (ask_pipeworx, compare_entities, discover_tools, subscribe) with noun-first names (polymarket_edges, entity_profile, ip_context, recent_changes) and bare verbs (remember, forget) without a unifying convention. Subfamilies are internally consistent (polymarket_*, ask_pipeworx_*, subscribe/unsubscribe), which keeps it readable, but there is no predictable server-wide pattern.

Tool Count2/5

32 tools is well into the too-many band, and several tools duplicate or wrap others: ask_pipeworx_beta is a redundant copy of ask_pipeworx, scan_competitor_ai_presence wraps ai_visibility_check, and bet_research overlaps polymarket_edges/arbitrage. The broad scope justifies a large set, but it would be tighter and clearer around 20-24 tools.

Completeness4/5

For the domain the descriptions actually define (structured-data research, company intelligence, prediction markets, subscriptions, memory), coverage is strong with few dead ends: subscription and memory lifecycles are complete, and research has routing/grounded/deep modes. However, the server is named Greynoise while only ip_context serves that domain, and side tools like generate_llms_txt and scan_dependency sit outside any core workflow.

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