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superhero

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?

The description goes well beyond the annotations by disclosing the 60-day snapshot TTL, data gaps, decay computed from daily closes (not intraday), and net of default slippage. It also details the response format, including expired opportunities and snapshot dates, fully transparent about behavior.

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 long but well-structured with clear sections (purpose, args, response, limits). Every sentence adds value, though it could be slightly tighter. The front-loaded purpose sentence and logical organization earn a high score.

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 and the absence of an output schema, the description is exceptionally complete. It explains the response fields (tracked[], expired[], snapshot_dates[]), the meaning of decay_pp_per_day, and the limits, leaving no critical context unaddressed.

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?

Schema coverage is 100% and the description repeats parameter defaults and meanings without adding significant new semantics. It provides a little context around 'days' and 'window' but not beyond what the schema already explains, so the baseline of 3 is appropriate.

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 uses a specific verb-resource structure: 'Edge persistence and decay telemetry' and answers 'how long has this edge existed and is it shrinking?', clearly distinguishing it from siblings like polymarket_edges by focusing on historical decay rather than current edges.

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 for when to use the tool (to distinguish fresh vs. old edges) and explains the rationale ('a fresh wide edge and a 3-week-old wide edge are different trades'). However, it does not explicitly name alternatives or state when not to use it, though the reference to 'polymarket_edges snapshots' implies the sibling.

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
Disambiguation1/5

The tool set is dominated by a huge number of unrelated tools for data lookup (Pipeworx, Polymarket, etc.), with only 4 superhero-specific tools. Many tools serve overlapping purposes (e.g., ask_pipeworx, deep_research, suggest_questions all handle general queries), making it very difficult for an agent to distinguish the right tool.

Naming Consistency2/5

Naming conventions are highly inconsistent: some tools use CamelCase (ask_pipeworx, discover_tools), others use snake_case (get_hero, list_all, compare_entities), and some use long descriptive phrases (polymarket_arbitrage, scan_competitor_ai_presence). This mixture makes it hard to predict tool names.

Tool Count1/5

With 34 tools, the count is far too large for a server named 'superhero'. Most tools are unrelated to superheroes, making the set seem bloated and misaligned with the server's stated purpose. A focused superhero server would need at most 10 tools.

Completeness1/5

For the superhero domain, the tool set is severely incomplete: only basic retrieval of heroes and powerstats, with no search, filtering, creation, comparison, or battle mechanisms. For the broader data access domain it is more complete, but that is not the server's name.

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