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Comicvine

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

A4.2/5.0
Behavior5/5

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

The description provides extensive behavioral traits beyond annotations: snapshot TTL (60-day), gaps in data, decay computation from daily closes (not intraday), and detailed response fields. This adds significant value beyond the 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 well-structured: summary, args, response with subsections, and limits. It is front-loaded with the core idea. While slightly verbose, every sentence adds value, making it efficient for an AI agent.

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 the tool's complexity, the description covers purpose, response format, edge cases (gaps, TTL), and limitations. No output schema exists, but the description details the return structure thoroughly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema covers both parameters with descriptions. The description paraphrases them and adds default values, but no additional semantics beyond the schema. Baseline 3 is appropriate due to high schema coverage.

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 starts with a clear summary ('Edge persistence and decay telemetry') and uses specific verbs and resources. It does not simply restate the name but explains the core question it answers. While it doesn't explicitly differentiate from siblings, the purpose is highly specific and unambiguous.

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?

The description implies usage for analyzing edge persistence and decay, but it does not explicitly state when to use this tool versus alternatives like polymarket_edges. No direct 'use when' or 'do not use when' guidance is provided.

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

B3.3/5.0
Disambiguation2/5

Many tools have overlapping purposes, especially the Pipeworx utilities (ask_pipeworx, ask_pipeworx_grounded, deep_research, etc.). The comic tools are distinct but the large number of similar generally-purpose tools creates confusion across the set.

Naming Consistency3/5

Comic tools follow a consistent noun pattern (character, characters, issue, issues) but Pipeworx tools mix verb_phrase (ask_pipeworx), noun_phrase (entity_profile), and composite names (scan_competitor_ai_presence). No single convention dominates.

Tool Count1/5

The server name 'Comicvine' suggests a focused comic book reference, yet 30 of 40 tools are unrelated Pipeworx services (company financials, prediction markets, subscriptions, etc.). This is a severe scope mismatch.

Completeness2/5

The comic-related tools cover characters, issues, volumes, publishers, and creators reasonably well, but the server's overall purpose is diluted by including many non-comic tools that don't form a coherent surface. The comic subset is complete, but the full set is not.

Resources