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countries

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

A4.7/5.0
Behavior5/5

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

The description extensively discloses behavior beyond the readOnlyHint annotations: response structure (tracked/expired/snapshot_dates), trend categories, decay computation on absolute value, signed edge_pp_net, snapshot gaps, TTL limits, and daily-close frequency. This far exceeds annotation baselines.

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 well-structured with Args, RESPONSE, and LIMITS sections. Every sentence carries operational detail; given no output schema, this level of detail is necessary and earns its place.

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?

The tool has no output schema, so the description must compensate by fully documenting return values and edge cases. It does so: tracked[], expired[], snapshot_dates[], trend values, decay semantics, TTL boundaries, and data-gap behavior. The description is complete for an AI agent to select and invoke the tool 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?

Both parameters are already fully documented in the schema (100% coverage). The description adds helpful context by explaining days as lookback and window as snapshot family, with defaults and max, but it omits the lower clamp (present in schema). This adds some meaning beyond the schema, so a 4 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 clearly states the tool's purpose as 'edge persistence and decay telemetry' and frames the question it answers ('how long has this edge existed and is it shrinking?'). It distinguishes itself from the sibling polymarket_edges by being snapshot-based and tracking history rather than current edges.

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 conveys when to use it: when edge age and decay matter, contrasting fresh vs old wide edges. However, it does not explicitly name alternatives or state when not to use it, so it stops short of a 5.

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

B3.4/5.0
Disambiguation2/5

The tool set is a mix of country lookups and many unrelated Pipeworx tools (e.g., prediction markets, memory, subscriptions). While the country-specific tools are distinct, the overall set is a hodgepodge, making it difficult for an agent to determine which tools are relevant to a given task.

Naming Consistency2/5

Naming conventions are mixed: some use verb_noun (search_countries), some noun_verb (countries_by_currency), some single verbs (forget, recall), and some phrases (ai_visibility_check, ask_pipeworx). No consistent pattern is followed.

Tool Count1/5

35 tools is excessive for a server named 'countries'. Only about 6-7 tools are actually related to countries; the rest are unrelated (Pipeworx services, prediction markets, etc.), creating an extreme mismatch between the server name and its content.

Completeness2/5

For the country domain, the tool set includes search and lookups by code/currency/language/region but lacks basic CRUD, comparisons, maps, or sorting. Additionally, the presence of many unrelated tools dilutes completeness for the stated purpose.

Resources