cdk-mcp

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

No annotations are provided, so the description carries full burden. It correctly implies a read-only operation (browse) but does not mention rate limits, side effects, or output format. Adequate but not comprehensive.

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 concise sentences: first states the action, second gives guidance. No redundant words, and every sentence earns its place.

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?

Given no output schema, the description could mention return structure, but for a simple listing tool the current info is largely sufficient. The context signals indicate low complexity, so a score of 4 is reasonable.

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?

The tool has no parameters, so schema coverage is trivially 100%. The description adds no parameter details because none exist. Baseline of 4 is appropriate for zero-parameter tools.

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 explicitly states the tool lists all available platforms, devices, regions, and languages for filtering, using specific nouns. It distinguishes from siblings like 'search_games' or 'get_game_details' by focusing on valid filter values.

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?

It clearly advises calling this first to know valid filter values, providing explicit usage context. However, it does not mention when not to use it or offer alternatives, which is minor given its simple nature.

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?

Discloses automatic polling for pending orders, a notable behavioral trait. No annotations exist; description covers key behavior but omits side effects or idempotency details.

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 concise sentences with front-loaded purpose and no filler; each word adds value.

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 tool with no output schema, description covers purpose, key parameter nuance, and polling behavior. Could mention return type but sufficient.

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 covers both params fully; description adds context that wallet_address is needed specifically for key retrieval, enhancing schema info.

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?

Clearly states 'Check the status of a purchase order' and specifies retrieving product key with wallet_address. Distinct from sibling tools like confirm_purchase or get_price_quote.

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?

Explains when to use (check status) and condition for retrieving product key. Does not explicitly state when not to use or list alternatives, but provides adequate guidance for typical use.

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 provided, so description carries full burden. States core action (verify payment and receive product key) but lacks details on side effects, error handling, or restrictions. Adequate but not comprehensive.

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, no wasted words, front-loaded with key action. Efficient and to the point.

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 4-parameter tool with no output schema, the description covers the core flow but omits details like error cases and full response format. Still fairly complete given complexity.

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?

Input schema covers all parameters with descriptions (100% coverage). Description adds value by explaining the sequence (call after get_price_quote) and the purpose of quote_id for price guarantee, enriching beyond the bare schema.

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 it verifies USDC payment and delivers the product key. It uses specific verb 'verify' and resource 'payment', and differentiates from siblings like get_price_quote which provides the price quote.

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?

Explicitly instructs to call after sending USDC to the address from get_price_quote and requires transaction hash. Does not mention when not to use, but the context is clear.

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 must fully disclose behavioral traits. It only lists return content but does not mention that the operation is read-only, whether authentication is needed, error scenarios (e.g., invalid game_id), or rate limits.

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 consists of two short, front-loaded sentences that efficiently convey purpose and prerequisite. Every word is necessary, no fluff.

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?

Given the tool's simplicity (single parameter, no output schema), the description adequately covers what the tool returns and the source of the required parameter. It could mention response format or error handling, but overall is sufficient for a straightforward retrieval tool.

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?

The input schema covers 100% parameter documentation with the description for game_id (UUID from search results). The description adds no new semantic information beyond what the schema already provides, so baseline score of 3 applies.

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 retrieves detailed information about a specific product, listing specific fields (price, activation instructions, delivery time). It also ties to the sibling search_games tool by instructing to use the game_id from its results, distinguishing it from other tools like get_price_quote.

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 explicitly says to use the game_id from search_games results, providing clear context for when to use this tool. However, it does not mention when not to use it or point to alternatives like get_price_quote for a subset of info.

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?

The description discloses that the quote_id is valid for 5 minutes, implying a time constraint. It also indicates price locking. No annotations are present, so the description carries the full burden. It does not mention potential side effects or permissions, but the behavioral constraint is well communicated.

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 concise sentences, front-loaded with the core action, no redundant words. Every sentence adds value.

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?

The description covers the key aspects: purpose, time limit, and next step. It mentions returns a quote_id but does not detail the payment instructions structure, which might be expected given no output schema. However, it is sufficient for a tool with only 2 parameters.

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 100%, with descriptions for both parameters (chain with enum and game_id). The description adds no additional meaning beyond the schema, so a 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 clearly states the action: 'Lock the current price for a product and get USDC payment instructions.' It distinguishes from siblings by mentioning the follow-up step 'confirm_purchase' and specifies the output (quote_id).

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 provides a clear usage context: initiating a purchase and then using confirm_purchase after payment. However, it does not explicitly state when not to use this tool or mention alternatives among siblings like check_order or request_refund.

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 full burden. It discloses time constraints and processing differences per reason, but lacks details on outcomes (e.g., confirmation, side effects) or permission requirements.

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 sentences efficiently deliver purpose, constraint, and behavioral nuance. No wasted words; front-loaded with key information.

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?

Covers purpose, constraints, and reason-dependent handling. Missing: expected return value (e.g., refund ID) or outcome of submission. With no output schema, an implied result would improve completeness.

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?

Input schema has 100% coverage with concise descriptions; the tool-level description adds no additional meaning to parameters, meeting the baseline.

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 action ('Submit a refund claim') and the resource ('purchased product key'), distinguishing it from siblings like check_order and confirm_purchase.

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?

Provides explicit conditions (30-day limit, auto-approval for not_delivered, 24h verification for key issues), offering context for when to use. However, no direct comparison to alternatives or when not to use.

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 of behavioral disclosure. It states that the tool returns a 'best match with alternatives (smart matching),' which transparently indicates the nature of results. It does not mention any destructive effects or required permissions, but as a read-only search tool, this is acceptable. No contradictions.

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 three sentences, front-loading the purpose and return behavior, then providing a usage tip. Every sentence adds value: what the tool does, what it returns, and how to get valid filter values. No unnecessary words.

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?

Given the tool's complexity (5 parameters, no output schema, no annotations), the description covers purpose, return type, and a prerequisite (use browse_filters). It does not detail pagination, result limits, or error scenarios, but for a search tool the information is sufficient for an agent to use it correctly. The absence of an output schema is mitigated by describing the return (best match with alternatives).

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 100% (all 5 parameters have descriptions in the schema). The description lists the search criteria (title, platform, device, region, language) but adds minimal new meaning beyond the schema's own field descriptions. The baseline score of 3 is appropriate as the schema already does the heavy lifting, and the description does not significantly enhance parameter understanding.

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: searching for digital products (game keys, gift cards, DLC) by title, platform, device, region, or language. It specifies the return type ('best match with alternatives') and distinguishes itself from the sibling tool 'browse_filters' by advising to use that first. This is a specific verb+resource combination.

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 provides explicit guidance to 'use browse_filters first to see valid filter values,' which helps the agent understand the proper workflow. However, it does not explicitly state when not to use this tool or describe other alternatives among siblings, though the guidance is sufficient for common use cases.

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 full burden. It notes 'One review per order' (a behavioral constraint) and required fields, but does not disclose mutation details, reversibility, or success/failure responses.

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 sentences, each with essential information; no fluff. Front-loaded with purpose, then constraints, then requirements.

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 rating tool with no output schema, the description covers key aspects: purpose, constraints, and required fields. It could mention what happens after submission (e.g., confirmation), but current completeness is sufficient.

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 100%, but the description adds critical context: wallet_address must match the order, and comment is optional. This goes beyond the schema's property descriptions, adding meaningful constraints.

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 uses a specific verb 'Rate' and clearly identifies the resource 'completed purchase'. It differentiates from siblings like request_refund or confirm_purchase by focusing on star rating for improving service.

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 explicitly states conditions: 'One review per order' and 'Requires order_id and wallet_address used for payment', guiding when to use. It lacks explicit when-not-to-use or alternatives, but context from siblings and constraints make it clear.

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