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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

A4.6/5.0
Behavior5/5

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

Annotations already indicate readOnly, idempotent, non-destructive. The description adds rich behavioral details: response structure with tracked (time-series, trend, decay), expired (lifespan), and snapshot dates; explains sign interpretation and decay computation. No contradictions 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 front-loaded with the key question and structured into response fields and limits. It is slightly verbose but every sentence adds value. No wasted words, but could be trimmed without losing clarity.

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?

Despite no output schema, the description fully explains the response structure. Parameter schema is complete, annotations provide safety info, and limits are noted. The description covers all necessary context for understanding edge decay telemetry.

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 provides 100% coverage with descriptions for days (number, default 14, clamp 2-30) and window (string, options listed). The description adds context like default '1wk' and snapshot family concept, going slightly beyond the schema. Baseline 3 raised to 4 for added 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?

The description clearly states the tool's purpose: providing edge persistence and decay telemetry from daily snapshots. It answers a specific question about edge longevity and shrinking, and distinguishes itself from sibling tools like polymarket_edges (raw edges) by focusing on temporal dynamics.

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 when to use the tool (when needing historical edge data) and mentions limits like 60-day TTL. It indirectly contrasts with raw edges, but could be more explicit about when not to use it or alternatives. Nonetheless, the context is clear for an AI agent.

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
Disambiguation2/5

Several tools intentionally overlap: ask_pipeworx_beta is explicitly identical to ask_pipeworx, and ask_pipeworx/ask_pipeworx_grounded/deep_research plus discover_tools/suggest_questions sit close together. The long descriptions clarify differences, but an agent still has to choose between near-equivalent entry points.

Naming Consistency3/5

All names are readable snake_case, but there is no single consistent convention: verb-led names like list_tags and resolve_entity sit alongside noun-led names like random_cat, entity_profile, and polymarket_arbitrage. Domain prefixes like polymarket_ and pipeworx_ help, but the mixed grammar makes the surface less predictable.

Tool Count2/5

34 tools is far beyond what a cat-image server needs; only 3 tools relate to Cataas, while the rest form a sprawling Pipeworx data, prediction-market, memory, and subscription suite. The count is in the 'too many' range and most tools are outside the server's apparent stated domain.

Completeness3/5

The cat-image core covers random cats, tag-filtered cats, and tag listing, but omits other Cataas-style operations like fetching by cat ID or creating cat images with text/effects. The embedded Pipeworx side is broad, but it does not fill the gaps in the server's named cat API purpose.

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