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Glama

Entso E

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. 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?

Annotations already mark it read-only and idempotent. The description adds rich details: response structure (tracked, expired, snapshot_dates), time-series behavior, and limits (60-day TTL, non-intraday decay). 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 and front-loaded but somewhat verbose. It includes necessary details without redundancy, earning a slightly above-average score.

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 explains the response fields (tracked, expired, snapshot_dates) and limits. It covers all aspects needed for an agent to use the tool correctly.

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 description coverage is 100%, so baseline is 3. The description repeats the same parameter info (days, window) without adding new meaning.

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 purpose: tracking edge persistence and decay from daily snapshots. It distinguishes from siblings like polymarket_edges by focusing on historical telemetry.

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 implicit usage context by contrasting fresh vs. old edges, aiding when to use. However, it lacks explicit comparison to alternative tools like polymarket_edges or polymarket_arbitrage.

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

B3.1/5.0
Disambiguation2/5

Several tools have overlapping or duplicate roles: ask_pipeworx and ask_pipeworx_beta are explicitly identical right now, and deep_research/ask_pipeworx/discover_tools/suggest_questions all serve query routing. The five ENTSO-E tools are distinct but are lost among the unrelated Pipeworx/prediction-market tooling.

Naming Consistency2/5

Naming mixes single verbs (remember, forget, subscribe), noun phrases (actual_load, entity_profile), verb_noun patterns (compare_entities, discover_tools), and brand-prefixed groups (pipeworx_*, polymarket_*). Snake_case is consistent, but the verb style and naming logic vary widely with no discernible overall pattern.

Tool Count2/5

36 tools is too many for a server supposedly focused on ENTSO-E electricity data, especially since only 5 tools serve that domain. Even as a general data-access server, the set is heavy and includes redundant/beta variants (ask_pipeworx_beta, ask_pipeworx_grounded) that inflate the count.

Completeness1/5

The server name 'Entso E' implies electricity-market data, but only 5 of 36 tools cover generation, load, prices, capacity, and cross-border flow. Missing typical ENTSO-E operations like forecasts, balancing, or real-time grid status, while the remaining 31 tools belong to an unrelated data platform — severely incomplete for the advertised purpose.

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