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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?

Annotations already indicate readOnly, openWorld, idempotent, and non-destructive. The description adds significant behavioral detail: data sources (daily snapshots), history limits (60-day TTL), decay calculation basis (daily closes), and response structure (tracked, expired, snapshot_dates). No contradictions.

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 well-structured with a clear summary first, then detailed response format, and limits. However, it is quite dense and could be more concise without losing meaning.

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?

Given no output schema, the description extensively explains the response fields (tracked, expired, snapshot_dates) and their semantics. It also covers limitations and data source details, making it fully informative for agent use.

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?

Schema coverage is 100%, so the schema already documents the parameters. The description adds context about the 'window' parameter as 'snapshot family' and clarifies defaults/clamping for 'days', which provides marginal added value beyond the schema.

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 about edge age and shrinkage. It distinguishes itself from siblings like polymarket_edges by focusing on historical tracking rather than current snapshots.

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 this tool by contrasting a fresh wide edge with an old one, but it does not explicitly list when not to use it or name alternative tools. The sibling list includes related tools, providing some differentiation.

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

A3.8/5.0
Disambiguation2/5

The ask_pipeworx family (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) has significant boundary overlap, and ask_pipeworx_beta is explicitly identical to ask_pipeworx today. The six polymarket_* tools plus bet_research also cover heavily overlapping prediction-market territory, so an agent could easily route a query to the wrong one despite detailed descriptions.

Naming Consistency4/5

Most tools follow a consistent snake_case verb_noun pattern (ask_pipeworx, compare_entities, generate_llms_txt, list_subscriptions, validate_claim, scan_dependency). Minor deviations exist — entity_profile is noun-noun, brightdata_serp/brightdata_unlock use a vendor prefix, and remember/recall/forget are bare verbs — but the overall style is predictable and readable.

Tool Count2/5

At 33 tools this exceeds the 25+ threshold that signals an over-heavy surface. While the server covers multiple domains (data lookup, prediction markets, memory, subscriptions, AI visibility), many of those domains carry redundant variants that could be consolidated, making the count feel bloated rather than well-scoped.

Completeness4/5

The surface covers the core workflows well: querying (ask_pipeworx variants), deep research, entity resolution, entity profiles, comparisons, change feeds, claim verification, discovery/onboarding, subscriptions (list/subscribe/unsubscribe), memory (remember/recall/forget), and feedback. Minor gaps exist — there is no direct tool to fetch a returned pipeworx:// citation URI, and memory lacks an explicit update operation — but agents can work around these.