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The Undesirables TCG Oracle

by io.github.sailorpepe

sports_board

Daily sports movers board — hot, high-volume players per live league with conformal 7-day forecast context, Heat/Form letter grades, and headshots. FREE. Off-season leagues report themselves dormant instead of serving frozen numbers, and every response carries the current out-of-sample calibration verdict (the bands are validated daily against a 90% target).

Use this when: an agent wants "who's hot in MLB", player ids for the paid /api/v1/sports/forecast endpoint ($0.05 — full per-stat calibrated bands), or fantasy-adjacent market context. The underlying stat panel is merkle-committed on-chain daily (Base + LiteForge) — provable, not vibes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
leagueNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden, and it does so thoroughly. It reveals that the tool is FREE, updates daily, reports dormant status in the off-season, includes a calibration verdict validated against a 90% target, and uses an on-chain merkle-committed stat panel for verifiability.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and efficient: it front-loads the core value, then adds behavioral details, and closes with explicit usage guidance. Every sentence adds meaningful information, and the 'provable, not vibes' phrase reinforces trust without bloating the definition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and no annotations, the description covers a lot: output contents, update cadence, cost, off-season behavior, calibration context, and related use cases. The main gap is the lack of explicit guidance on the limit parameter and league value conventions, but the board's purpose and behavior are clear enough for an agent to invoke it.

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 description coverage is 0%, so the description must compensate. It gives useful context for the 'league' parameter via 'per live league' and an MLB example, but it does not explain the 'limit' parameter, valid league values, or expected formats.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: a daily sports movers board of hot, high-volume players per live league, with forecast context, grades, and headshots. It is specific about the resource and content, though it does not explicitly differentiate from sibling tools like market_snapshot or fantasy_league.

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 includes an explicit 'Use this when' section listing concrete use cases: 'who's hot in MLB', player ids for the paid forecast endpoint, and fantasy-adjacent market context. It does not state when not to use it or name alternative sibling tools, but the guidance is actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All The Undesirables TCG Oracle toolsInspect
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TDQS

A3.6/5.0
Disambiguation2/5

Multiple tools have unclear boundaries: card_forecast and simulate_price both return conformal-calibrated forecasts with Safe-Hold/Momentum grades; grade_card and grade_or_not both include ROI verdicts; check_accuracy and oracle_scorecard are both accuracy dashboards; market_snapshot and trending_cards both surface market movers. The descriptions carry some differentiators, but an agent would frequently misselect among these pairs.

Naming Consistency3/5

All names are snake_case, which is consistent, but the verb/noun pattern is mixed: some are verb_noun (check_accuracy, grade_card, optimize_portfolio, search_tcg_products, simulate_price), while many are noun_noun or noun phrases (card_forecast, market_snapshot, oracle_scorecard, sports_board, souls_in_wallet). The result is readable but not predictable.

Tool Count3/5

23 tools sits in the heavy 16–25 band, and the server spans several domains: TCG pricing/forecasting/grading, souls and fantasy, the Syndicate game, and technocore. It is not extreme, but the count feels bigger than a single focused oracle needs.

Completeness4/5

The core card-market workflow is well covered: search, price forecast, simulation, trending, market snapshot, grading, ROI, loan preview, and accuracy verification are all present. Minor gaps include the paid loan quote for off-board cards not being exposed as an MCP tool and some redundancy between card_forecast and simulate_price, but no CRUD lidecycle is required for a read-only oracle.

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