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The Undesirables TCG Oracle

by io.github.sailorpepe

grade_or_not

Answers: "Should I grade this card? Will I make money?"

Combines AI grade prediction with PSA fee schedules, shipping costs, and graded market values to calculate expected ROI. Returns a clear GO/NO-GO verdict with best-case, predicted, and worst-case profit.

PAID: $0.10 USDC per call.

Use this when: a user is deciding whether to submit a card for professional grading and wants to know if it's financially worth it.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
card_nameYes
raw_priceNo
service_tierNoregular
predicted_gradeNo

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior4/5

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

With no annotations provided, the description carries the burden of explaining behavior. It discloses that the call is paid ($0.10 USDC), combines several data sources, and returns a verdict with profit ranges. It does not mention side effects or assumptions, but this appears to be a read-only analytical tool and the main behavioral traits are covered.

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 concise, well-structured, and front-loaded with the core question. Every section—answer, method, pricing, and usage guidance—adds value without redundancy.

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

Completeness3/5

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

The description explains the return concept (GO/NO-GO and profit scenarios), which matters because there is no output schema. However, missing parameter semantics and a lack of clarifying details about service tiers or currency/units leave meaningful gaps for an agent trying to call the tool correctly.

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

Parameters2/5

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 by explaining the four parameters. It indirectly references card, grading, price, and costs, but it never names raw_price, service_tier, or predicted_grade, nor clarifies their meaning, defaults, or how they affect the ROI calculation.

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 states a specific verb and resource: it answers whether to grade a card and calculates expected ROI. It also names the concrete output (GO/NO-GO verdict with best-case, predicted, and worst-case profit) and is clearly distinguishable from siblings like grade_card or market_snapshot.

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?

Explicit usage guidance is provided: 'Use this when: a user is deciding whether to submit a card for professional grading and wants to know if it's financially worth it.' It lacks explicit when-not-to-use or alternatives, so it does not fully earn a 5.

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.

Resources