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exchange

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

A4.5/5.0
Behavior5/5

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

Annotations declare read-only, open-world, and idempotent behavior, and the description adds substantial non-trivial context: snapshot TTL limits, cache-miss snapshot writing, signed edge_pp_net (negative = SELL YES), and interpretation of gaps in snapshot_dates. It also clarifies decay uses daily closes, not intraday data, and notes the median lifespan as a 'competition clock'.

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?

Despite its length, the description is efficiently structured with labeled sections (Args, RESPONSE, LIMITS) and front-loads the core purpose. Every sentence contributes meaning—explaining response fields, data caveats, and usage context—making the length appropriate for the tool's complexity.

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 thoroughly documents all return components: tracked[] with time-series, trend, decay; expired[] with lifespan; and snapshot_dates[] with gap interpretation. It also touches on data depth, freshness, and the computation basis, making it self-contained for an agent to understand full behavior.

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?

The input schema already specifies both parameters fully, including defaults and clamp ranges. The description's 'Args' section reiterates this without adding new semantic detail (e.g., examples or parameter interplay). With 100% schema coverage, the description adds marginal value, hence the baseline of 3.

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 explicitly states the tool's purpose as 'edge persistence and decay telemetry' and answers the question 'how long has this edge existed and is it shrinking?', clearly distinguishing it from the sibling polymarket_edges tool which provides current edge snapshots. The mention of time-series vs. single-snapshot analysis adds specificity.

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 implies usage context—this tool is for analyzing edge persistence/decay over time, as opposed to the direct polymarket_edges snapshot. It doesn't explicitly name alternatives or exclusions, but the 'built from daily polymarket_edges snapshots' phrasing and response semantics provide enough guidance for when to choose it.

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
Disambiguation4/5

Most tools have clearly distinct purposes with detailed descriptions. Potential confusion exists between similar tools like ask_pipeworx and ask_pipeworx_grounded, but the descriptions differentiate them well. The high number of tools across multiple domains could still cause some ambiguity, but overall an agent can distinguish them.

Naming Consistency3/5

Naming patterns are mixed. Some subgroups follow consistent patterns (polymarket_*, pipeworx_*, get_*), but overall the set includes verb_noun (list_subscriptions, get_rate, remember) and noun_verb (entity_profile, deep_research) without a unified convention. The mixture of imperative and descriptive names reduces predictability.

Tool Count2/5

34 tools is excessive for a single server, bundling unrelated domains (currency, memory, data query, prediction markets, dependency scanning). This scope could be split into multiple servers for better coherence. The high count may overwhelm agents and increases the risk of misselection.

Completeness3/5

Each sub-domain (e.g., currency, memory, Polymarket) has reasonable coverage with common operations present. However, the server name 'exchange' is misleading—it suggests a narrower focus. Some gaps exist (e.g., no batch currency conversion, no direct Polymarket market detail tool). Overall, the set covers many tasks but lacks a unified purpose.

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