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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

A4.5/5.0
Behavior5/5

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

Despite strong annotations (readOnly, idempotent, non-destructive), the description adds substantial behavioral detail: 60-day snapshot TTL, cache-miss write behavior, gaps meaning no scan, decay computed from daily closes not intraday, and the signed edge_pp_net convention (negative = SELL YES). This far exceeds annotation coverage and gives the agent critical interpretive nuance.

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 long but tightly structured: purpose, args, response fields, limits. It front-loads the core question, uses caps for field names, and every sentence adds operational or behavioral context without filler. The formatting makes a dense payload skimmable.

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 fully documents the response shape (tracked[], expired[], snapshot_dates[]) and explains edge cases like gaps, TTL bounds, and median lifespan as a 'competition clock'. It is complete for an agent to invoke and interpret results without external docs.

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 clear parameter descriptions, so baseline is 3. The description mostly restates defaults ('days default 14 max 30', 'window default 1wk') and adds the concept of 'snapshot family' but no new syntax or constraints beyond what the schema already provides.

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 'Edge persistence and decay telemetry built from daily polymarket_edges snapshots' and explicitly frames the question it answers ('how long has this edge existed and is it shrinking?'). This clearly names the resource (snapshots) and distinguishes it from sibling tools like polymarket_edges by focusing on temporal persistence rather than current edge values.

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 gives clear context: use when needing edge history vs. current state, and defines when data exists (snapshots written on cache-miss, gaps). However, it doesn't explicitly name alternatives like polymarket_edges or state when not to use it, so it stops short of full when/when-not guidance.

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
Disambiguation3/5

Many tools are crisply separated (memory CRUD, subscription lifecycle, single-entity vs compare vs profile), but several broad entry points overlap: ask_pipeworx, ask_pipeworx_beta, and ask_pipeworx_grounded are very close variants, and discover_tools/suggest_questions/ask_pipeworx all serve discovery/routing. Descriptions help, but an agent can still easily select one of the duplicate or adjacent tools instead of the intended one.

Naming Consistency3/5

All names are readable snake_case and there are coherent families (polymarket_*, ask_pipeworx_*, search_*, get_*), but there is no consistent verb_noun convention: noun-phrase names like recent_alerts and pipeworx_trending coexist with single verbs like remember and forget and domain-prefixed nouns like polymarket_edges. Mixed, but still reasonably navigable.

Tool Count2/5

At 35 tools, the surface is well past the comfortable 3-15 tool scope and even beyond the 16-25 heavy range unless the server has one explicit mega-purpose. The set also sprawls across music lookup, Pipeworx research, prediction markets, npm checks, LLM visibility, memory, and subscriptions, so no single coherent job emerges.

Completeness4/5

For the dominant read-only research workflow, the set is remarkably complete: discover tools, grounded and ungrounded asking, deep research, entity resolution, profiles, recent changes, comparisons, claim verification, search_within, plus full memory and subscription lifecycles. Minor gaps include the shallow music side relative to the rest of the server and the absence of an explicit source catalog.