ChangeGamer

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

The description discloses what the tool returns (valid:true/false, tier, creation time, premium slugs, and granted deliverables) and explicitly states what it never returns (key, email, Stripe session). This provides comprehensive behavioral insight beyond basic annotations.

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 with no wasted words. It front-loads the main purpose, then provides return details and usage guidance in a clear, structured manner.

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 (one parameter, no output schema, no annotations), the description provides a fairly complete picture: purpose, return values, excluded data, and usage context. It could mention potential side effects or rate limits, but these are not critical.

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 schema has 100% coverage for the single parameter (api_key with description). The description does not add additional meaning beyond the schema, meeting the baseline for adequate parameter semantics.

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: 'Verify an access key and report what it unlocks.' It uses a specific verb ('verify') and resource ('access key'), and the functionality is distinct from siblings like get_access_info or 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?

The description provides explicit context: 'Use this to confirm a freshly-purchased key works before relying on it.' It implies a specific use case, though it does not explicitly state when not to use it or mention alternatives.

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, and the description does not disclose behavioral traits beyond the lexical meaning of 'Return'. It does not specify if the operation is read-only, destructive, requires authentication, or has rate limits. The description carries the full burden but provides minimal 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?

The description is a single sentence of 11 words, front-loaded with the key verb 'Return' and specific resource. No wasted words; every part 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 and no parameters, the description is adequate but minimal. It does not describe the format or structure of the returned information, which would be helpful for an agent to interpret results. More detail on what access and pricing info entails 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?

The input schema is empty (0 parameters) and schema coverage is 100%. The description adds value by specifying what the tool returns (access and pricing info), which is meaningful beyond the empty schema. Baseline for 0 params is 4.

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 'access and pricing information' for 'ChangeGamer resources' with a specific verb ('Return') and resource. It distinguishes from siblings like 'get_resource' (likely general resource details) and 'list_resources' (listing all resources) by focusing on access and 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?

The description implies usage by stating its purpose but lacks explicit guidance on when to use vs alternatives or prerequisites. It does not mention exclusions or context like 'use this instead of get_resource for pricing 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?

Discloses behavior of premium resources as stubs with purchase links, mentions equality to /llms-full.txt, and warns about large response size, compensating for missing annotations.

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 focused sentences front-load purpose and key details with no extraneous 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?

Fully describes return content and behavior for a no-parameter tool without an output schema, leaving 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?

No parameters exist, so baseline is 4; description adds value by explaining output content, which is sufficient.

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 with details, distinguishing it from siblings that operate on individual resources or search.

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 advises use for ingesting everything in a single call and notes the response is large, implying it's not for partial fetches, but does not explicitly exclude alternatives.

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 key authorization behavior and the upgrade response for unauthorized keys. Without annotations, it covers safety aspects well, though could mention response size or pagination if applicable.

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: purpose, requirement+consequence, alternative. Every sentence adds value, 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 one parameter, no output schema, and no annotations, the description covers purpose, prerequisite, error/upgrade case, and alternative tool. Adequate for its 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?

Schema already describes the api_key parameter with tier hint. Description reinforces the need for a Corpus/Enterprise key, adding clarity beyond the schema's text.

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 returns the entire corpus with premium resource bodies, using specific verbs and resource name. It distinguishes from the sibling tool get_corpus, which is the free stubbed version.

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 specifies the required key tier (Corpus/Enterprise) and the consequence of using an unentitled key. Also names the alternative free version get_corpus for when the full corpus is not needed.

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 details the content returned (payment methods, retry loop, free items) and notes it matches /api/payment.json. It does not mention auth requirements or side effects, but as a read-only tool, this is acceptable.

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, front-loaded with the core purpose, followed by a concise list of included data. Every word is informative with 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?

Given zero parameters and no output schema, the description sufficiently covers what the tool returns by listing key data categories and referencing an external endpoint for context. It is complete for an agent to understand its use.

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 exist, so baseline is 4. The description does not need to explain parameters since schema coverage is 100% and no params are 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 returns the agent payment manifest, listing specific components like payment methods, retry loop, free items, and recommendations. It is distinct from sibling tools which cover access, pricing, and 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 implicitly defines usage for retrieving payment manifest information, but does not explicitly compare with sibling tools or state when not to use it. It is clear enough for most contexts.

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 full burden for behavioral disclosure. It implies a read-only operation by describing a data retrieval, but does not explicitly state side effects, auth needs, or rate limits. The description is accurate but lacks 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, front-loaded with the main purpose, and every word adds value. Efficient and clear without 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?

Given no output schema, the description comprehensively lists the return data elements. However, it could be more complete by mentioning the response format (JSON) or any potential constraints like rate limits, which are not covered.

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 the description adds rich meaning by detailing exactly what the response contains, including price, currency, deliverables, license grant, etc. Since the schema is empty, the description fully compensates and adds significant value.

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 returns the full paid-offer catalog, listing all components (price, currency, interval, etc.) and even mentions the free layer and premium slug list. This distinguishes it from sibling tools like get_access_info or 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?

The description provides context by mentioning it returns same data as an API endpoint, but does not explicitly state when to use this tool versus alternatives or when not to use it. No exclusions or prerequisites are given, so usage guidance is minimal.

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 discloses that free resources return full metadata and Markdown body, while premium resources require a valid api_key and otherwise return a payment-required object. This provides insight into the tool's behavior beyond the input schema. It could be improved by noting non-existent slugs or error responses, but the free/premium distinction is well handled.

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 long, front-loads the primary action, and covers the key differentiator (free vs premium) without any fluff. Every word contributes meaning, making it 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 the absence of an output schema, the description should detail return values more thoroughly. It covers two return scenarios (free full resource, premium without api_key payment-required) but omits details like error handling for invalid slugs or the structure of the full resource object. The tool has two parameters and a conditional return, so more completeness would be helpful for an agent to parse responses.

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 (slug and api_key). The description adds no new meaning to slug beyond 'by slug', and for api_key it reinforces the context of premium access. Since the schema already provides adequate definitions, the description does not significantly enhance parameter semantics, aligning with the baseline of 3.

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 ('Fetch a ChangeGamer resource by slug') and distinguishes between free and premium resources. This differentiates it from siblings like 'list_resources' (which lists all resources) and 'get_access_info' (which presumably deals with access). The verb-resource pair is specific and unambiguous.

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 clear context on when to use the tool (fetching a resource by slug) and offers guidance on api_key usage for premium resources. However, it does not explicitly mention when not to use it (e.g., for listing all resources) or direct users to alternative tools like 'list_resources' for non-specific fetches. The guidance is good but not exhaustive.

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 behavioral burden. It describes the return contents and notes it is the same data as /api/stats.json. It implies read-only behavior, but does not explicitly state side effects, permissions, or rate limits. Still sufficiently transparent for a simple stats endpoint.

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: the first lists all return elements, the second gives a usage hint. No filler or redundant information. Front-loaded with the most important 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 or annotations, the description is fairly complete. It explains what is returned and why to use it. It could mention output format or limits, but for a zero-parameter stats tool, this is sufficient. A 4 acknowledges it is good but not exhaustive.

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 schema coverage is 100%. Per guidelines, 0 parameters yields a baseline of 4. The description does not need to add parameter info, and it does not. Baseline 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 what the tool returns (total/free/premium counts, per-category counts, tag count, newest/oldest dates, 10 most recent resources, feed URLs) and its purpose as a freshness/size signal. It distinguishes from sibling tools like get_corpus and get_full_corpus by focusing on aggregate stats rather than full resource data.

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 usage context: 'A small freshness/size signal to poll before deciding whether to re-ingest.' This tells the agent when to use it. However, it does not explicitly state when not to use it or provide alternatives to siblings, so it is not a perfect 5.

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 present, so description bears full burden. It discloses that no body content is returned and lists the metadata fields, giving a clear picture of behavior.

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?

Single, efficient sentence listing fields upfront; 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 no output schema, the description fully explains return fields and notes lack of body content, making it complete for a simple list 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?

No parameters exist, so schema coverage is 100%. Description adds no parameter semantics, but baseline for zero parameters is 4.

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 it lists all ChangeGamer resources with metadata, differentiating from sibling tools get_access_info and get_resource (which likely target single resources or access details).

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?

States what the tool does but does not explicitly guide when to use it over alternatives or mention exclusions.

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 correctly discloses that the tool returns metadata and URLs but not body content. However, it does not mention potential traits like pagination, ordering details, or rate limits, which would be beneficial but not critical for a search tool.

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 are used effectively: the first explains the functionality, and the second provides usage guidance. Every sentence is necessary and concise.

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 explains what is returned (metadata and URLs, no body) and contextualizes its use with get_resource. While it could mention result format or ranking, it is sufficient for an agent to understand the tool's scope.

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. The description adds value by providing example search queries and clarifying the default limit, going beyond the schema definition.

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 searches the corpus by keyword, ranks by relevance, and returns metadata and URLs without body content. Distinguishes from sibling tools by mentioning that resources should be found with this before fetching with get_resource.

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 the tool: 'Use this to find resources before fetching them with get_resource.' This provides a clear workflow and contrasts with an alternative tool.

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