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The Guardian

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

A4.7/5.0
Behavior5/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds crucial details: snapshot source, 60-day TTL, decay computation from daily closes (not intraday), and output structure. No contradiction 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and usage context. It is moderately long but every sentence adds necessary detail about behavior, output format, and limitations. No wasted words.

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 comprehensively covers the return structure (tracked, expired, snapshot_dates), field meanings (edge_pp_net signed, trend classification, decay rate), limits, and data source. All essential information is present.

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 coverage is 100% with clear parameter descriptions. The description adds additional explanation for 'days' (default, max) and 'window' (snapshot family examples). While schema already covers basics, the extra context about window options ('24hr | 1wk | 1mo') adds 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 provides 'edge persistence and decay telemetry' and answers a specific question about edge duration. It distinguishes itself from siblings like polymarket_edges by focusing on historical time series.

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 gives strong context for when to use (e.g., distinguishing a new edge from an old one) but does not explicitly list when not to use or directly compare with sibling tools. The sibling list provides context but no exclusions.

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

Many tools have overlapping purposes and similar names, especially the Pipeworx query tools (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research) and the Polymarket tools (polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, etc.). The Guardian-specific tools are distinct but are outnumbered by these confusing clusters, making it hard for an agent to reliably select the right tool.

Naming Consistency1/5

Tool names follow no consistent pattern: some are snake_case (ai_visibility_check, ask_pipeworx), some are verbs without objects (item, tags, forget, recall), and some are inconsistent in style (compare_entities vs. bet_research). There is no unifying naming convention across the set.

Tool Count2/5

With 36 tools, the server is bloated for its implied purpose ('The Guardian' suggests a focused news outlet). Many tools belong to unrelated domains (Pipeworx data platform, Polymarket prediction markets), making the count feel excessive and unfocused. A news-specific server should have far fewer tools.

Completeness1/5

The tool set lacks a coherent domain. The Guardian news tools are complete (search, item, sections, etc.), but the massive inclusion of Pipeworx and Polymarket tools creates dead ends and gaps (e.g., no direct tool to list all prediction markets or search patents). The surface feels like a random collection rather than a designed whole.

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