View TCG Oracle's public prediction accuracy dashboard. Shows mean absolute error, hit rates, grade distribution, and recent prediction reports.
FREE — no payment required.
Use this when: a user asks "how accurate is the grading AI?" or wants to verify the model's track record.
| Name | Required | Description | Default |
|---|---|---|---|
| game | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It does disclose that the dashboard is public and free ('FREE — no payment required'), and 'View' implies a read-only operation. However, it does not explicitly state whether there are side effects, authentication requirements, or any limitations on usage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loads the core action before listing the dashboard contents. The 'Use this when' section is a helpful structural cue, though 'FREE — no payment required' is slightly redundant since 'FREE' already communicates the same idea.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only dashboard tool, the description covers purpose, content, and usage triggers reasonably well. However, it is incomplete because the 'game' parameter is entirely unexplained, and there is no explicit statement about output format or whether the parameter is a filter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description never mentions the 'game' parameter. The only parameter is an optional string with a default value, leaving agents with no guidance on what valid values look like, whether it filters the dashboard, or how it affects results. The description completely fails to compensate for the lack of schema-level documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'View TCG Oracle's public prediction accuracy dashboard' and lists the specific content it shows, including mean absolute error, hit rates, grade distribution, and recent prediction reports. This goes beyond a vague verb and resource, though it does not explicitly differentiate itself from sibling tools like oracle_scorecard.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit trigger scenarios: use when a user asks 'how accurate is the grading AI?' or wants to verify the model's track record. This is clear when-to-use guidance, but it does not mention when not to use the tool or suggest alternative tools, so it misses the full explicitness required for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.