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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. Added
  2. Removed
  3. Added

TDQS

A4.4/5.0
Behavior5/5

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

Beyond the readOnlyHint annotations, the description adds significant behavioral details: snapshot TTL of 60 days, cache-miss write behavior causing gaps, decay computed on daily closes net of default slippage, the meaning of negative edge_pp_net (SELL YES), and the full response shape (tracked, expired, snapshot_dates). 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 long but well-structured with 'Args:', 'RESPONSE:', and 'LIMITS:' labels, front-loaded with the core purpose. Every sentence provides unique information such as the trade interpretation, response fields, and limitations. It is not maximally concise, but the density is justified for a tool with no output schema and complex telemetry semantics.

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 the tool's complexity and absence of an output schema, the description is remarkably complete. It fully specifies response fields (tracked, expired, snapshot_dates), explains data freshness limits (TTL, cache-miss gaps), and clarifies computational methodology (daily closes, net of slippage, trend classification). It also provides the competition-clock heuristic, leaving little ambiguity for the 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?

The input schema already covers both parameters with descriptions (days: default 14, clamp 2-30; window: which family with allowed values and default). The description's 'Args:' line is mostly redundant, adding only 'max 30' which is already present in the schema as 'clamp 2-30'. Thus the description adds marginal value beyond the schema, so 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 opens with a specific verb and resource: 'Edge persistence and decay telemetry built from daily polymarket_edges snapshots.' It directly answers 'how long has this edge existed and is it shrinking?' which distinguishes it from siblings like polymarket_edges (current edge) by focusing on time-series and decay. The distinction is further emphasized with the trade example.

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?

It provides strong contextual guidance: 'a fresh wide edge and a 3-week-old wide edge are different trades' explains when the tool is valuable, and the 'LIMITS' section clarifies data availability (TTL, cache-miss gaps). However, it does not explicitly state when to prefer this over sibling tools like polymarket_arbitrage or polymarket_fill_risk, so it is clear but not fully explicit.

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

C2.6/5.0
Disambiguation3/5

Tools like ask_pipeworx, ask_pipeworx_grounded, deep_research, and entity_profile have overlapping purposes, causing potential confusion. However, their descriptions provide some differentiation, so an agent can usually pick the right one with careful reading.

Naming Consistency2/5

Naming is highly inconsistent: mixes verb_noun (ask_pipeworx), noun_verb (reverse_dns), single-word (geoip), and compound phrases (generate_llms_txt). No clear pattern, making it hard for an agent to predict tool names.

Tool Count2/5

44 tools is overwhelmingly high for a single server. The set mixes unrelated domains (network tools, data APIs, memory, prediction markets), suggesting it's a grab bag rather than a focused toolkit.

Completeness2/5

The server lacks a coherent domain, so evaluating completeness is difficult. There are many lookup tools but few for updates or deletes (except memory). The HackerTarget subset is sparse, and the overall surface feels incomplete for any single purpose.