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Producthunt

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
Behavior5/5

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

Annotations indicate read-only, open-world, idempotent, non-destructive behavior. Description adds critical behavioral contexts: data sourced from daily snapshots with 60-day TTL, decay computed from daily closes not intraday, and response includes tracked, expired, and snapshot dates. 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?

Description is thorough but somewhat lengthy. It is front-loaded with the core question and response structure is clearly explained. Every sentence contributes to understanding, but could be slightly more concise without losing information.

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, description comprehensively explains the response format (tracked, expired, snapshot_dates) with field semantics. It also covers data provenance, limitations (60-day TTL), and decay computation details. No gaps for effective use.

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 covers both parameters with descriptions, but description adds meaningful context: default values for days and window, explanation of window as 'snapshot family', and implicit constraints (max 30 days). This adds value beyond the schema definitions.

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?

Description clearly specifies the tool's purpose: providing edge persistence and decay telemetry from daily snapshots. It explicitly contrasts with raw edge data by focusing on temporal analysis ('how long has this edge existed and is it shrinking?'). This distinguishes it from sibling tools like polymarket_edges.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage context is implied but not explicitly stated. The description indicates it is for assessing edge persistence, and the response structure suggests analysis of opportunities over time. However, it does not provide explicit guidance on when to use this tool versus alternatives like polymarket_edges or direct scenario comparisons.

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 functionally near-identical: ask_pipeworx_beta is explicitly a duplicate of ask_pipeworx (descriptions say they 'currently match exactly'), and ask_pipeworx_grounded differs only in answer-extraction mode. The six Polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_edge_tracker, polymarket_fill_risk, polymarket_kalshi_spread) heavily overlap on edge-finding and fill-risk, and ai_visibility_check duplicates scan_competitor_ai_presence's per-entity probing. Agents will frequently misselect among these.

Naming Consistency4/5

Naming is consistently snake_case with a mostly verb_noun pattern (get_post, top_launches, subscribe, forget, validate_claim, resolve_entity). Minor deviations exist where nouns lead (entity_profile, recent_changes, recent_alerts, bet_research), and polymarket_* names use a domain-prefix style rather than pure verb_noun, but the overall pattern is predictable and readable.

Tool Count2/5

33 tools is at the heavy end, and the count is badly mismatched to the server's stated identity: it is named 'Producthunt' yet only 2 of 33 tools (get_post, top_launches) are Product Hunt related — the rest are Pipeworx data lookup, prediction-market, memory, and subscription tools. The redundancy (duplicate ask_pipeworx_beta, overlapping polymarket tools) inflates the count without adding surface.

Completeness2/5

Judged against the Product Hunt domain implied by the server name, the surface is severely incomplete: coverage is limited to list-top-launches and get-one-post, with no search, users, comments, votes, collections, or categories — and no way to act on Product Hunt data at all. As a general Pipeworx data platform the coverage is broader, but for the named purpose there are large gaps that will force agent failures.

Resources