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Gdelt

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?

The description details response structure (tracked, expired, snapshot_dates) and explains derived fields like trend and decay_pp_per_day. It also notes limitations (60-day TTL, daily closes, not intraday), adding significant value beyond readOnlyHint and idempotentHint 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 lengthy but well-structured, explaining each response field in separate paragraphs. It front-loads the core question. Though verbose, every sentence adds value for a complex tool.

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 thoroughly covers return values and their meanings. It also addresses limitations like data gaps and snapshot TTL. All essential aspects for using the tool are 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%, but the description adds default values and range for 'days', and explicitly lists allowed values for 'window' (24hr, 1wk, 1mo), which are not enums in the schema. This extra context improves parameter understanding.

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, answering 'how long has this edge existed and is it shrinking?'. It distinguishes from siblings like polymarket_edges by focusing on time-series analysis.

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 (to differentiate old vs. new edges) but does not explicitly contrast with alternatives or state when not to use. It provides context through examples but lacks explicit usage boundaries.

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 are near-duplicates: ask_pipeworx_beta is explicitly identical to ask_pipeworx, and discover_tools/suggest_questions plus entity_profile/recent_changes/compare_entities/validate_claim overlap in purpose. An agent selecting among the five ask/deep-research variants or six Polymarket tools will frequently need to read lengthy descriptions to avoid picking the wrong one.

Naming Consistency3/5

Most names are readable snake_case and clear verb_noun phrases like search_articles, resolve_entity, and validate_claim, with helpful families like polymarket_* and timeline_*. However, several tools are bare noun phrases (entity_profile, recent_alerts, pipeworx_trending, tone_distribution), and the memory trio (remember/recall/forget) breaks the domain-prefix pattern.

Tool Count2/5

35 tools is past the 25+ threshold and feels bloated for a server nominally about GDELT; much of the surface is meta/utility tooling (diagnostics, memory, discovery, subscriptions) rather than core news retrieval. Several tools could be consolidated, such as ask_pipeworx_beta and the multiple Polymarket edge/arb/research variants.

Completeness4/5

For its broad data/news/prediction-market scope, the surface is quite complete: GDELT search, volume, tone, and distribution are covered, along with entity resolution, company profiles, comparisons, claim verification, and trade-side analytics. Minor gaps exist, such as no full-text article fetch or direct GDELT raw-event export, but agents can mostly work around them.

Resources