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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

A4.7/5.0
Behavior5/5

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

With annotations declaring read-only and idempotent behavior, the description still adds substantial behavioral transparency: it details the response structure (tracked, expired, snapshot_dates), explains that snapshots are written on cache-miss so gaps mean no scan, and discloses limits like the 60-day TTL and that decay is computed from daily closes, not intraday. This goes far beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The description is front-loaded with the purpose and uses clear sections (Args, RESPONSE, LIMITS) to present detailed information efficiently. Every sentence contributes value, covering purpose, parameters, output structure, and limitations without unnecessary fluff.

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 fully compensates by explaining the response fields (tracked, expired, snapshot_dates) and their meanings, along with behavioral caveats like TTL and cache-miss semantics. This makes the tool's behavior and constraints complete for an agent to use correctly.

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 baseline is 3. The description adds extra semantics by explaining the 'window' as a snapshot family and clarifying the lookback concept. It also notes that history depth is bounded by the 60-day TTL, which informs how the 'days' parameter behaves in practice. No contradictions with 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's function: 'Edge persistence and decay telemetry built from daily polymarket_edges snapshots.' It answers a specific question (how long an edge has existed and whether it's shrinking) and distinguishes itself from sibling tools by focusing on historical tracking vs. current edges. The example of fresh vs. 3-week-old edges adds clarity.

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 context on when to use the tool by framing the question it answers ('how long has this edge existed and is it shrinking?') and contrasting with the qualitative difference between edge ages. It does not explicitly name alternatives or exclusions, but the context is clear enough for an agent to infer its use case relative to sibling tools like polymarket_edges.

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

A4/5.0
Disambiguation3/5

Most tools have clearly distinct purposes, but there are overlapping clusters: the three ask_pipeworx variants and multiple polymarket analysis tools can cause selection ambiguity. Descriptions help, yet boundaries between entity_profile, compare_entities, recent_changes, and ask_pipeworx require careful reading.

Naming Consistency4/5

Tool names almost all follow snake_case with verb-noun or verb-phrase structure (ask_pipeworx, validate_isin, list_subscriptions), and family prefixes like ask_pipeworx_* and polymarket_* are consistent. Minor deviations include one-word verbs (remember, recall, forget) and adjective-noun names (recent_alerts, recent_changes, entity_profile).

Tool Count2/5

With 34 tools, the surface is well above the 25-tool threshold that typically feels heavy, even though the Pipeworx platform is broad in scope. The server named 'Isin' exposes a large toolkit far beyond its apparent identifier-focused purpose, making the count feel excessive.

Completeness4/5

The broader data-access, research, subscription, and utility workflows are well covered, including discovery, grounded queries, entity profiles, comparisons, and claim validation. Minor gaps include the lack of direct pipeworx:// URI reading and ISIN issuer resolution, but agents can work around these.