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Glama

The Undesirables TCG Oracle

loan_terms_preview

FREE worked derivation of safe lending terms for a trading card on today's published free board (250 cards): value -> calibrated 99% tail -> liquidation buffer -> liquidity cap -> max LTV, all six steps shown with the price source and merkle proof links. term_days: 7, 14 or 30.

Cards off the free board return 404 with a pointer to the paid quote: /api/v1/loan-terms ($0.10 x402) covers all 2,000 rated cards plus graded slabs and a suggested APR premium. The rated universe is public at /api/v1/loan-terms/universe. Informational only — not financial advice.

Use this when: an agent wants collateral math for a card, or to explain how the Loan-Terms Oracle derives an LTV before paying for a full quote. Human page: https://oracle.the-undesirables.com/lending

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
term_daysNo
product_idYes

Schema Changelog

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

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

There are no annotations, so the description carries the burden. It discloses the free nature, the 404 behavior for out-of-scope cards, the pointer to the paid quote, the 'Informational only — not financial advice' caveat, and the transparency artifacts like merkle proof links. It does not explicitly declare read-only/no side effects or mention auth/rate limits, but the read-only intent is strongly implied.

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 dense but well organized: coverage and derivation steps first, then failure behavior and paid alternative, then usage trigger and related URLs. A few phrases repeat the free/board concept, but every sentence adds relevant decision-making or invocation context.

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?

There is no output schema, so the description must convey return content, and it does: six derivation steps, price source, merkle proof links, and 404 behavior. It also provides the rated universe endpoint and a human page, giving an agent enough context to call the tool and recover when a card is outside the free board.

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 explicitly enumerates term_days as 7, 14 or 30, which is valuable. However, product_id is only implied to be the trading-card identifier on the free board; its format, source, or lookup is not directly explained, leaving a partial semantic gap.

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, concrete behavior: a free worked derivation of safe lending terms for a trading card on the free board, including the exact derivation pipeline. It also clearly distinguishes itself from the paid /api/v1/loan-terms quote, so an agent knows this is the preview, not the full paid quote.

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

Usage Guidelines5/5

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

The description explicitly says 'Use this when: an agent wants collateral math for a card, or to explain how the Loan-Terms Oracle derives an LTV before paying for a full quote.' It also states the exclusion boundary clearly: cards off the free board return 404 and point to the paid quote endpoint.

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

A3.6/5.0
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.