Cardpeer MCP by Nova (CIVAI)

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

No annotations are provided, so the description carries the full behavioral burden. It adds useful context about sources and currency units, but it does not disclose return shape, time-series granularity, permissions, or other behavioral details needed to invoke confidently.

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 two short sentences with the key concept front-loaded. Every sentence contributes: the first identifies the data and sources, and the second clarifies the unit.

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?

With no output schema and no annotations, the description is too sparse for a historical pricing tool. It clarifies sources and units but does not explain what a pricing snapshot contains, how days/condition affect results, or what the response looks like.

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 high at 80%, so the schema already documents most parameters including days, source, product_id, and notification_message. The description adds source and unit context but does not add parameter-level meaning beyond the schema, 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.

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

The description states a clear resource (historical pricing snapshots) and sources (Cardpeer and market), so the tool is distinguishable from product/catalog/search siblings. It does not explicitly contrast itself with search_listings or get_product, but the pricing focus is clear.

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 no explicit when-to-use guidance, no prerequisites, and no indication of when an agent should call get_pricing instead of get_product or search_listings. Historical pricing is implied by the purpose, but there is no actionable routing guidance.

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

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

No annotations exist, so the description carries the full burden; it discloses the returned payload categories, which is the most valuable behavioral detail for a read tool. It is silent on what happens when the product_id is unknown, auth requirements, and how the unusual notification_message parameter behaves at runtime.

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?

A single sentence, front-loaded with the verb and resource, with the return-content list appended as useful detail. No filler or repetition.

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?

With no output schema and no annotations, the description's enumeration of returned data carries the return-value burden reasonably well. It still leaves gaps around not-found behavior and the notification_message follow-up semantics, so it is adequate rather than complete.

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 100%, so both product_id and notification_message are already documented in the schema, establishing the baseline of 3. The description adds nothing about parameters beyond implying that one ID selects a single product, and does not explain the role of notification_message.

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?

States a specific verb ('Get') and resource ('single product') and enumerates what the payload contains (card info, set, series, pricing snapshots, language variants). This clearly distinguishes a single-product fetch from the sibling list/search tools, though it does not explicitly acknowledge get_pricing as a narrower alternative.

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?

Phrasing 'a single product' implies the tool is for lookup-by-ID rather than browsing, which is enough for an agent to infer use versus list_series or search_cards. However, no explicit when-to-use, when-not, or named alternative (e.g. get_pricing for pricing-only queries) is given.

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

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

With no annotations provided, the description carries the full burden. It implies a read-only listing but does not say whether results are exhaustive, ordered, cached, or filtered to a default game, and the presence of a notification_message parameter (unexplained) leaves the side-effect profile ambiguous.

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?

Two compact sentences with the core purpose front-loaded and the downstream usage hint second; nothing is wasted, though the brevity contributes to the behavioral gaps.

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 3-param, no-annotation, no-output-schema read tool, the description is close to adequate but omits what a returned series looks like (name, slug, game) and how it relates to list_sets, both of which an agent needs to chain calls correctly.

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 coverage is 67%: search and notification_message have their own descriptions, and game is an enum. The tool description adds no meaning to any parameter, so it neither compensates for the gap nor adds value over the schema, making the 3 baseline appropriate.

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?

States a specific verb+resource ('List available card series') with a concrete example and notes that the slug feeds search_cards. However, it never distinguishes 'series' from the sibling tool list_sets, which an agent will inevitably confuse.

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 line about the slug being usable in search_cards implies a workflow (discover series, then search cards), but there is no explicit guidance on when to use list_series versus list_sets or when to pass the game filter.

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

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

No annotations are supplied, so the description carries the full burden. "List" implies a safe read, and the mention of slugs adds real downstream context, but nothing is said about pagination, result volume, ordering, or what happens with the unusual notification_message parameter.

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?

Two short sentences, front-loaded with the resource being listed, with zero filler. The downstream pointer is compact and useful.

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 6-parameter paginated listing tool with no output schema and no annotations, the description is thin: nothing about what a set object contains, how paging works, or why a notification_message parameter exists. An agent could call it but has little basis for choosing filters or interpreting results.

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 only 33% — only search and notification_message are documented in the schema. The description adds no parameter meaning at all, leaving game, page, size, and language semantics and the strange notification_message contract entirely unaddressed.

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 gives a clear verb and resource ("List available card sets/expansions") and adds a hint about the returned identifier, so an agent knows this is a read-only enumeration tool. It does not differentiate from the sibling list_series, which sounds adjacent enough that an agent could confuse sets with series.

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?

Usage is implied by the name and the note that the slug feeds search_cards, which usefully links the two tools in a workflow. However, there is no guidance on when to pick this over list_series or search_cards, and no mention of filters like game or language as selection criteria.

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

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

With no annotations, the description carries the full burden. It does valuable work by disclosing the aggregation model (one row per product, cheapest active listing plus last known market price) and the unit convention (euro cents), but it says nothing about pagination behavior, result caps, empty-result handling, or any auth/rate constraints on a 16-parameter search.

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?

Three tight sentences with the core purpose front-loaded and the currency convention stated immediately after the return semantics. Nothing is padded or redundant.

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 16-parameter, annotation-free search tool with no output schema, the description covers purpose and the shape of the returned price data but omits pagination limits, how the 16 filters combine, and what fields each result carries. Adequate but with clear gaps.

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 81%, so the schema already documents nearly every parameter, including the sort semantics and price units. The description's euro-cents clarification largely duplicates what max_price/min_price already state, so baseline 3 is appropriate.

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?

States a specific verb and resource ('Search for trading cards and sealed products on Cardpeer') and even describes the result shape (one result per product with cheapest active listing price and last known price). It does not distinguish itself from the sibling search_listings, which likely overlaps heavily, so an agent must guess which search to use.

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?

No when-to-use, when-not-to-use, or alternative routing is given. The description never says how this differs from search_listings or why an agent would pick it over get_product for a single item, leaving selection to inference.

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

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

No annotations are provided, so the description carries full behavioral burden. It does disclose the return grouping ('seller × condition × price'), which is genuine added context, but never confirms this is a read-only operation, says nothing about pagination behavior despite page/size parameters, and gives no hint about result volume or ordering.

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?

Two sentences, zero waste; the capability statement is front-loaded and the prerequisite follows. Nothing repeats the schema or restates the tool name.

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 an 8-parameter tool with no annotations and no output schema, the description covers purpose and the product_id prerequisite but leaves the agent guessing about pagination, result size, and the unexpected notification_message parameter on what appears to be a search operation. Adequate to invoke, incomplete to invoke well.

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 coverage is 63%, so several parameters (page, size, ships_from, notification_message, min/max price) rely on the schema alone. The description does implicitly signal the seller/condition/price filter dimensions, but adds no unit, format, or default guidance beyond what the schema already says.

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?

States a specific verb and resource ('Find individual seller listings for a specific product') plus the result shape ('grouped by seller × condition × price'), which separates it from get_pricing's aggregate view. It also positions the tool relative to search_cards, so an agent can place it in the workflow without opening another schema.

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 prerequisite is explicit and actionable: 'Use search_cards first to get a product_id', which matches the single required parameter. It stops short of stating when-not to use it (e.g. when aggregate pricing is enough, use get_pricing), so it is clear context without exclusions.

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