Skip to main content
Glama

Europeana

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. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Beyond annotations, the description details snapshot mechanics (cache-miss triggers), gaps meaning no scan, limitations (60-day TTL, daily closes), and response structure (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 information-dense but well-organized: purpose, args, response fields, limitations. Slight redundancy could be trimmed, but every part adds value.

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?

For a tool with no output schema, the description fully explains the response fields, edge cases (gaps, TTL), and limitations. No critical information missing.

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 baseline is 3. The description adds default values, clamp ranges, and interprets 'window' as snapshot family, providing meaning 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. It uses a specific verb (answers) and resource (edge snapshots), and distinguishes from sibling tools like polymarket_edges by emphasizing historical context.

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 gives context on when to use (to assess edge history and decay) and implies alternatives indirectly via sibling tool names. Explicit when-not-to-use guidance could be stronger, but the narrative makes it clear this is for historical analysis.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Europeana toolsInspect
Try in Browser
RayrunBuild, deploy, and operate MCP servers without becoming an infrastructure team.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.5/5.0
Disambiguation2/5

Many tools have overlapping purposes, e.g., three versions of ask_pipeworx for similar tasks, and several research/analysis tools (bet_research, deep_research, entity_profile) with unclear boundaries. The mix of Europeana-specific tools with a broad research toolkit creates confusion.

Naming Consistency2/5

Tool names are inconsistent, mixing snake_case (ai_visibility_check, ask_pipeworx), verb_noun patterns (compare_entities, resolve_entity), and short names (search, record, forget). No clear naming convention is followed throughout the set.

Tool Count2/5

33 tools is excessive for a Europeana-focused server, as only 3 tools (search, record, search_within) are directly related to Europeana. The rest are a broad, unrelated toolkit, making the server feel like a kitchen sink rather than a cohesive collection.

Completeness2/5

The Europeana-specific tool surface is severely incomplete, lacking browse collections, advanced filters, or entity linking. The inclusion of many unrelated tools does not compensate for the gaps in the core domain, resulting in a poorly scoped offering.

Resources