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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).

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already indicate read-only, open-world, idempotent. Description adds details like snapshot TTL (60-day), data gaps, decay computation from daily closes. 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?

Well-structured with clear heading, bulletized response fields, and limits section. Slightly verbose but each part adds value. Front-loaded with the key question.

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, description fully explains return types (tracked, expired, snapshot_dates) and their fields. Covers limits and assumptions. Complete for a tool with optional params.

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 describes both parameters with default and constraints. Description reinforces defaults (days=14, window=1wk) and adds max lookback (30). Schema coverage is 100%, so description adds marginal value.

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?

Clearly states it measures edge persistence and decay, distinguishing from sibling tools like polymarket_edges by focusing on time-series analysis. Answers specific question about edge age and shrinkage.

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?

Provides context on when to use: for evaluating edge longevity vs freshness, especially comparing a 3-week-old wide edge to a fresh one. Does not explicitly list alternatives or when not to use, but the context is clear.

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

A4.1/5.0
Disambiguation4/5

Most tools have clearly distinct purposes, but there is some overlap: ask_pipeworx and ask_pipeworx_grounded are very similar, and the multiple Polymarket tools could be confused. The memory tools (remember, recall, forget) are distinct.

Naming Consistency3/5

Tool names consistently use snake_case, but the pattern is not strictly verb_noun. Some names are descriptive phrases (e.g., scan_competitor_ai_presence), while others are straightforward (e.g., keyword_overview). Overall readable but not highly consistent.

Tool Count3/5

32 tools is on the high side for a single server, but the scope is broad (SEO, finance, FDA, betting, memory). The tool count feels slightly excessive, yet each tool appears justified by its specific use case.

Completeness4/5

The tool set covers a wide range of business research needs: SEO, SEC filings, FDA data, betting analytics, and memory. Minor gaps exist (e.g., no direct social media or HR data), but the coverage is impressive for a general-purpose data server.

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