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spacenews

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 mark the tool readOnly/openWorld/idempotent, and the description goes far beyond by detailing exact data sources, time-series semantics, computed fields (trend, decay_pp_per_day), handling of expired opportunities, and the meaning of snapshot gaps. It also discloses limitations (60-day TTL, daily closes not intraday) that are not present in 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 longer than average but densely packed with high-value information, front-loaded with the core question it answers, then structured into Args, RESPONSE, and LIMITS. Every sentence contributes meaningful detail, though the sheer length keeps it from being maximally concise.

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 fully enumerates the response shape (tracked[], expired[], snapshot_dates[]) and explains each field's meaning, including derived metrics and edge cases (gaps, TTL, expiry). It also covers data provenance and limitations, making it self-contained for an agent to invoke and interpret results 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?

Schema coverage is 100% for both parameters, so baseline is 3. The description adds meaning by explaining 'days' as lookback with bounds and 'window' as a 'snapshot family' influencing which data source to read, which clarifies the conceptual role of each parameter beyond the raw schema.

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 defines the tool as 'edge persistence and decay telemetry built from daily polymarket_edges snapshots,' with a specific verb implied ('answers how long has this edge existed and is it shrinking?'). It distinguishes itself from the sibling tool polymarket_edges by focusing on longitudinal edge decay and time-series tracking rather than current edge values.

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 provides clear context on when this tool is relevant ('a fresh wide edge and a 3-week-old wide edge are different trades'), implying use for evaluating edge longevity and decay. It does not explicitly name alternative tools or state when NOT to use it, but the context is strong and the LIMITS section adds practical usage boundaries (e.g., snapshot TTL, cache-miss gaps).

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

A3.6/5.0
Disambiguation3/5

Several tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research. While each has distinct nuances, they could be confused by an agent.

Naming Consistency3/5

Most tools use snake_case, but the naming pattern is inconsistent (e.g., bet_research vs. polymarket_arbitrage vs. ai_visibility_check). There is no strong verb_noun pattern across the set.

Tool Count2/5

34 tools is high given the server's stated purpose ('spacenews'). Only a few tools directly relate to space news; the bulk are general-purpose Pipeworx utilities, making the scope too broad.

Completeness2/5

For a space news server, the tool surface is incomplete: only get_articles, get_blogs, and search_articles are relevant. Missing tools for article details, source filtering, or categories. The extensive general tools don't make up for this gap.

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