ChangeGamer

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

With no annotations, the description carries full burden. It discloses the return format (valid:true/false and details when valid) and explicitly states what it never returns (key, email, Stripe session), providing good behavioral context beyond the basic function.

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 extremely concise, with two sentences that front-load the main purpose and provide necessary details in a structured manner with no wasted 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 simplicity (1 parameter, no output schema), the description is complete. It explains return values, what is included when valid, and explicitly states omissions. No additional context is needed.

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 already describes the single parameter (api_key) with 100% coverage. The tool description adds no additional parameter semantics but mentions output constraints ('Never returns the key'). Baseline 3 is appropriate as schema does the heavy lifting.

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 action ('Verify an access key') and its result ('report what it unlocks'). It uses a specific verb and resource, distinguishing it from siblings like get_access_info which might serve a different purpose.

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 when to use the tool: 'Use this to confirm a freshly-purchased key works before relying on it.' It provides a clear use case but does not explicitly state when not to use or mention alternatives among siblings.

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 the full burden. It states 'Return' implying read-only, but does not disclose authentication requirements, caching, side-effects, or whether the info is for the current context or global.

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 a single, clear sentence with no wasted words. It is appropriately sized for a simple retrieval tool.

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 zero parameters and no output schema, the description is adequate for a basic info retrieval. However, it does not clarify the relationship to siblings like 'get_pricing' and 'check_access', leaving ambiguity about overlap.

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?

There are zero parameters and schema coverage is 100%, so no parameter info is needed. However, the description could add context about what the output contains (e.g., keys like 'accessLevel' or 'price') but does not.

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 verb 'Return' and the resource 'current access and pricing information for ChangeGamer resources,' distinguishing it from siblings like 'get_pricing' (likely just pricing) and 'check_access' (likely just access). However, it could be more specific about whether it returns info for the current user or all resources.

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 guidance is provided on when to use this tool versus alternatives. Sibling tools like 'get_pricing' and 'check_access' exist, but the description does not explain when to prefer 'get_access_info' over them.

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 burden. It discloses the response size is large, that premium content is only a stub, and that it mirrors '/llms-full.txt'. This provides adequate behavioral context for a read-only operation without needing to mention rate limits or authentication.

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 with essential information: first sentence defines the tool's output in detail, second provides usage guidance. No redundant or filler words. Information is front-loaded and well-structured.

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 zero parameters and no output schema, the description fully covers what the agent needs to know: what the return contains (free vs premium), its size, and its similarity to a known URL. It is self-contained and adequate for invoking this tool 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?

There are no parameters (0 params, schema coverage 100%). The baseline for zero parameters is 4. The description adds no parameter-specific info, which is acceptable since there are none to elaborate on.

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 returns the entire free corpus as one document, detailing exactly what free resources include (title, description, canonical URL, full Markdown body) and how premium resources appear (stub with purchase link). It distinguishes itself by explaining the scope (free vs premium) and references '/llms-full.txt' for clarity.

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 'Use this to ingest everything in a single call; the response is large,' which guides when to use it for bulk ingestion. It implies alternatives for accessing individual resources or premium content, but does not explicitly name sibling tools like 'get_resource' or 'get_full_corpus'.

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 that an unauthorized key returns a payment-required/upgrade object, and that it returns entire corpus in one document. No annotations to contradict; fully self-contained.

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 carrying distinct information: purpose, licensing requirement, and alternative. No redundancy.

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 only one parameter and no output schema, the description sufficiently covers what the tool returns, when to use, and error behavior. No 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 already describes api_key; description adds the specific format and license requirement, going beyond schema alone.

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 verb 'Return' and resource 'corpus' with scope 'ENTIRE including premium resource bodies'. Distinguishes from sibling 'get_corpus'.

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 states required license level (Corpus/Enterprise), what Starter key does vs not, and the alternative 'get_corpus' for free version.

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. It discloses the data content (payment methods, retry loop, free items, recommended path) and refers to the API endpoint, but does not explicitly declare it as read-only.

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, front-loaded with action and content list. No wasted 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?

Covers key aspects of what is returned, including various payment methods and paths. Lacks explicit format specification, but the reference to /api/payment.json compensates somewhat.

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?

No parameters in schema, so baseline is 4. Description adds no param info, but none needed.

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 'Return the agent payment manifest' and enumerates specific payment methods and details, distinguishing it from sibling tools like check_access or get_pricing.

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 clear context for when to use this tool (to get payment info), but does not explicitly state when not to use or mention alternatives. However, sibling tool names imply differentiation.

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 disclose behavioral traits. It states the return data and references an API endpoint, indicating a read-only operation. However, it lacks details on authentication requirements, rate limits, or whether the data is cached.

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 with no wasted words. Front-loads the core purpose and includes a reference for verification. Highly efficient.

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 input schema and no output schema, the description fully covers the tool's purpose and return value. It provides enough detail for an agent to decide when to use it.

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 zero parameters, so the baseline is 4. The description does not need to explain parameters, and it correctly omits any parameter discussion.

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?

Description clearly states it returns the full paid-offer catalog with specific fields (tier, price, currency, interval, checkout URL, etc.) and mentions the free layer and premium slug list. It distinguishes from sibling tools by specifying its unique data scope.

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 implies when to use this tool: to get the complete pricing catalog. However, it does not explicitly state when not to use it or suggest alternative tools. Given no input parameters, the usage context is straightforward, but a mention of alternatives like get_payment_info could improve it.

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?

Without annotations, the description must disclose behavior. It does so by explaining that free resources return full metadata and Markdown body, while premium resources require an api_key or return a payment-required object. This covers key behavioral traits.

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 at two sentences, front-loading the main purpose. While clear, it could be slightly more structured (e.g., separating free and premium cases) but remains effective.

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 adequately explains return types for free and premium scenarios. It could mention error cases (e.g., invalid slug), but the provided information is sufficient for basic usage.

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?

Both parameters (slug and api_key) are described in the schema with 100% coverage. The description adds semantic value by explaining the role of slug (resource identifier) and api_key (for premium access) in the context of free vs premium resources.

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 fetches a ChangeGamer resource by slug, and distinguishes between free and premium resources. This differentiates it from sibling tools like get_corpus or get_stats.

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 specifies when to use the tool (by slug) and provides context about free vs premium resources. However, it lacks explicit guidance on when not to use it or how to choose among siblings like get_full_corpus.

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 accurately describes the output and implies a read-only, lightweight operation. However, it omits details like authentication needs, rate limits, or behavior under error conditions, which would be helpful for full transparency.

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: first lists all data returned, second adds usage context and API equivalence. Every word is informative, no fluff. Front-loaded with the most critical 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?

Given no output schema, the description fully documents return values (counts, dates, top resources, feed URLs) and their purpose. No parameters to define, and the usage suggestion completes the picture. Entirely adequate for a simple stat 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?

There are zero parameters and schema coverage is 100%. The baseline for 0 params is 4. The description adds no parameter info (unnecessary) but succinctly explains the tool's purpose.

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 specific verbs ('Return corpus stats') and enumerates exact data items like counts, dates, and feed URLs. It also distinguishes itself from siblings by positioning the tool as a lightweight freshness check before re-ingestion, and references an API endpoint for clarity.

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 states when to use: 'poll before deciding whether to re-ingest.' This provides clear context. While it doesn't explicitly say when not to use, the sibling list and lightweight signal imply it's for quick checks, not detailed data retrieval.

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 that the tool returns metadata and URLs but no body content. This is transparent for a read-only listing tool. However, it does not mention potential pagination, ordering, or rate limits, but for a simple list without parameters, the description is adequate.

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 sentences. The first sentence states the purpose and what is returned. The second sentence lists the return fields and explicitly states what is not included. Every sentence adds value, and the information is front-loaded.

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 has no parameters and no output schema, the description provides sufficient information: it lists all resources, specifies the returned fields, and clarifies that no body content is returned. It is complete for the tool's 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?

The input schema has no parameters, so the baseline is 4. The description adds context about what the tool does but has no need to describe parameters. No additional parameter information is required.

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 lists all ChangeGamer resources with metadata and absolute URLs. It specifies the exact fields returned and distinguishes itself from similar tools by explicitly stating it returns no body content and is a list of all resources.

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 implies this tool is for retrieving the full catalog of resources without filtering. While it does not explicitly mention when not to use or name alternatives, the sibling tools (e.g., get_resource, search_resources) provide contrast, and the simplicity of the tool makes its use case 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?

With no annotations, the description discloses behavioral traits: it ranks by relevance across multiple fields, returns metadata and URLs, and explicitly states 'no body content.' It does not mention auth needs or rate limits, but for a read-only search tool, these are less critical.

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, each earning its place: first defines purpose and behavior, second gives usage advice. No wasted 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?

The description is adequate but lacks detail on the return format. Without an output schema, the agent would benefit from knowing the structure of results (e.g., fields like id, title, score, URLs). The mention of 'metadata plus HTML/Markdown/JSON URLs' is vague.

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 descriptions cover both parameters (query and limit). The description adds value by specifying which fields are searched (title, description, tags, category, body) and that results are ranked by relevance, which is not in the 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 searches the ChangeGamer corpus by keyword, ranks by relevance across title, description, tags, category, and body, and returns metadata plus URLs but no body. This distinguishes it from siblings like get_resource which fetches full resources.

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 'Use this to find resources before fetching them with get_resource,' providing clear context for when to use this tool. However, it does not mention alternatives like list_resources or cases where this tool should not be used.

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