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

With no annotations, the description discloses default daysBack and handling of missing data. However, it does not mention idempotency, read-only nature, or any side effects. 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?

Three concise sentences with no wasted words. Front-loaded with purpose, then usage, then behavior. Perfectly sized.

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?

Describes output format partially but omits details like whether data is cumulative or per-day, how conversionRate is calculated, or pagination. Adequate for simple tool but could be more complete given no output schema.

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?

Only daysBack is explained (default 7 days). minTrials is not described at all despite 0% schema description coverage. The description partially compensates for one parameter but fully misses the other.

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 aggregates SUBSCRIPTION_EVENT data by country and SKU, listing the returned fields. It distinguishes from sibling tools that likely return raw events (e.g., asc_get_subscription_events).

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 to use this for comparing geo/pricing performance across paid campaigns. Does not include explicit exclusions, but the purpose and context with siblings imply when not to use (raw events).

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 timezone (America/Los_Angeles), Apple's data lag, and truncation via maxLines. It does not explicitly state the tool is read-only, but the context implies it. 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 concise with bullet points, front-loaded with purpose, and each sentence adds value. 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?

For a tool with 6 parameters and no output schema, the description covers purpose, date formats, report types, lag, and timezone. It lacks details on maxLines truncation behavior beyond header preservation, but is otherwise comprehensive.

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 50%. The description adds value for reportDate format and reportType meanings, but does not explain version, maxLines, frequency, or reportSubType. Baseline of 3 is appropriate as the description partially compensates.

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 'Download a sales/subscription report as TSV' and lists report types and date formats. It does not explicitly differentiate from sibling tools like asc_get_subscription_events, but the purpose is specific and actionable.

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 explains when to use each reportType (SALES for downloads+revenue, SUBSCRIPTION for active subscriptions, etc.) and mentions Apple's 1-day lag. It does not provide explicit when-not-to-use or alternatives, but the guidance 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?

Discloses the default date behavior (yesterday in Apple's timezone) and output contents, but lacks information on read-only nature, authorization requirements, or rate limits. No annotations are provided to supplement.

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 with no filler: purpose, output contents, and default behavior. Every sentence adds necessary 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?

For a simple single-parameter tool without an output schema, the description adequately explains the return format (per SKU and country) and default behavior, making it effectively complete for 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?

Schema provides full description of the single parameter, but the tool description adds explicit timezone name (America/Los_Angeles) and clarifies default behavior, offering marginal added value beyond 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?

Clearly states it fetches the SUBSCRIPTION_EVENT report for one day, specifying what data it shows (trial starts, conversions, cancels, etc.) and distinguishing from sibling asc_get_subscription_events_range by limiting scope to a single day.

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?

Describes the tool as a convenience wrapper for a single day, implying use for daily reports, but does not explicitly state when not to use it or mention the alternative range tool. The sibling name provides implicit 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?

With no annotations, the description discloses key behaviors (default JSON with reportDate column, tsv for raw, max 60 days). However, it omits error handling, authentication needs, or what happens if date range is invalid. More transparency would be beneficial.

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—two sentences that front-load the purpose and then detail usage. Every sentence earns its place without any 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 the moderate complexity (4 params, no output schema, no annotations), the description covers the essential information: purpose, parameter alternatives, constraints, and output format. It is largely complete for an agent to use 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 75%, and the description adds value by explaining the effect of format (JSON for aggregation, tsv for raw) and clarifying the relationship between daysBack and startDate/endDate. This compensates for schema gaps.

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 and concatenates SUBSCRIPTION_EVENT reports for a range of days. This distinct purpose is differentiated from the sibling asc_get_subscription_events, which likely handles single events or days.

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 on using daysBack versus startDate/endDate, a maximum of 60 days, and the format parameter's impact. However, it does not explicitly say when to avoid this tool or name 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 provided, so description carries full burden. Discloses that reports are vendor-scoped and merged, and that default date is yesterday in Apple's timezone. Provides adequate behavioral context.

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, no fluff. Each sentence provides distinct value: definition, functionality, and usage tip. Well-structured and 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?

Despite no output schema and no annotations, description explains what data is fetched and what fields are returned. Sufficient for an agent to understand tool's purpose and output. Could be more explicit about response structure.

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?

Only one parameter (reportDate) with schema description covering its format and default. Description adds 'skip reportDate to use yesterday' which aligns with schema. At 100% schema coverage, baseline 3 applies; no additional semantics beyond 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?

Clearly describes a cross-app snapshot that fetches sales and subscription events and merges with app list. Distinguishes from siblings like asc_list_apps, asc_get_sales_report, asc_get_subscription_events by combining multiple data sources.

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 to skip reportDate for default yesterday's data, implying use case. Does not explicitly mention when not to use or alternative tools, but context makes it clear for combined data.

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 bears full burden. It discloses returned fields but does not mention rate limits, pagination, or authentication requirements. Acceptable for a simple listing tool, but could be improved.

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 superfluous words. Front-loaded with action and returns. 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?

Given no parameters and no output schema, description covers purpose, return fields, and usage hint. Lacks mention of pagination or result set limits, but generally complete for a simple list.

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?

Tool has no parameters, and schema coverage is trivially 100%. Description adds no parameter info, but none is needed. Baseline score 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?

Description clearly states it lists apps from App Store Connect account, specifies returned fields (id, name, bundleId, sku, primaryLocale), and indicates its primary use case of discovering appIds for other tools, which distinguishes it from siblings.

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 says 'Use this first to discover appIds for other tools', providing clear usage context. However, it does not mention when not to use it or discuss alternatives like asc_list_all_apps_snapshot or rc_list_apps.

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 convey behavioral traits. It states the sorting order and optional developer response inclusion, but omits details on pagination, rate limits, error handling, or authentication requirements. The description is 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?

The description is concise (two sentences) and front-loaded with the primary action. Each sentence adds distinct information, with no unnecessary words. Excellent structure.

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, the description should give more detail about returned data. It mentions reviews and developer responses but not fields like rating or text. The limit and territory parameters are not explained thoroughly, leaving gaps for an agent to understand full behavior.

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 50%; the description adds meaning for includeDeveloperResponse and implies appId usage, but does not explain the limit or territory parameters. It provides some value beyond the schema but does not fully compensate for the missing schema descriptions.

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 retrieves customer reviews for a specific app, sorted newest-first, and distinguishes itself from siblings like asc_reply_to_review (which modifies) and asc_list_apps (which lists apps). The verb 'get' and resource 'customer reviews' are 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 implies usage when seeking recent reviews for an app, but does not explicitly provide when-not-to-use or mention alternatives. However, the context (sibling tools) and clear purpose make it obvious; no guidance is needed beyond what is stated.

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 carries burden. Discloses creation-only nature and role requirements, but could add more detail (e.g., behavior on duplicate submissions, rate limits). Adequate for a simple action.

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 no filler. Critical info is front-loaded: purpose, constraint, permission requirement.

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 creation tool with no output schema, description covers core aspects. Could mention possible error conditions or response, but not essential.

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 clear descriptions. Description adds context for reviewId (source in asc_list_customer_reviews) and confirms body max chars. Adds value beyond 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 the verb (Post) and resource (developer response to a customer review), distinguishing it from sibling tools like asc_list_customer_reviews. It 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?

Explicitly notes that the endpoint creates a new response and cannot overwrite, and requires Admin or Customer Support role. Does not explicitly contrast with alternatives, but the constraint is valuable.

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, placing the burden on the description. The description only states the tool fetches details but does not disclose behavior like read-only nature, error handling (e.g., missing customer), response size, or anything about side effects. This is insufficient for an agent to predict 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?

The description is a single sentence of 10 words, front-loading the core purpose. Every word is necessary; there is no redundancy or 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?

Given there is no output schema, the description should compensate by indicating what 'details' includes (e.g., customer info, entitlements, transactions). It fails to do so, leaving the agent without understanding the return value structure or any limitations. The tool's complexity is low (2 params), but behavioral context is missing.

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% (both parameters are described). The description adds value by clarifying that 'project_id' can be omitted to use a default from environment, and that 'customer_id' can be either app_user_id or RevenueCat customer ID. This goes beyond the schema's generic descriptions.

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 ('Get details') and the resource ('single customer'), and specifies the identifier ('by app_user_id'). This effectively distinguishes it from siblings like 'rc_list_customers' (list vs single) and 'rc_get_customer_purchases' (details vs purchases).

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 when needing details for one customer, but provides no explicit guidance on when to use this tool versus alternatives (e.g., why not use 'rc_get_customer_purchases' or 'rc_get_customer_subscriptions'). No when-not-to-use or fallback instructions are 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?

No annotations exist, and the description only states 'get all purchases' without disclosing behavioral traits such as pagination, rate limits, or whether the tool is read-only. Minimal disclosure for a data retrieval 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?

One short sentence is concise and front-loaded with verb and resource, but could include essential details without becoming verbose.

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?

Adequate for a simple two-parameter tool, but lacks details on output format, parameter defaults (project_id uses env var), and any constraints. Meets minimum 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?

Schema description coverage is 50% (project_id documented, customer_id not). The tool description adds no extra meaning to parameters; missing customer_id format or validation details.

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 all purchases/transactions for a specific customer, distinguishing it from sibling tools like rc_get_customer_subscriptions (subscriptions only) and rc_get_customer (general info).

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 on when to use this tool vs alternatives (e.g., rc_get_customer_subscriptions), no prerequisites or when-not-to-use information provided.

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 carry the full burden. It mentions 'active and expired' subscriptions, which is useful, but omits side effects, authentication needs, rate limits, or error handling. For a read operation, it fails to explicitly confirm it is safe and non-destructive.

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, front-loaded, and contains no extraneous information. It effectively communicates the core purpose in minimal space.

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 should ideally mention response format or any pagination. It misses details on what the returned subscriptions contain. However, the tool is simple with two parameters, so the gap is moderate.

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 describes project_id with default behavior, but customer_id has no description. The tool description adds no extra info about parameters beyond the schema, and with 50% coverage, it does not compensate for the gap.

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 'Get', the resource 'subscriptions', and the scope 'for a customer' including both active and expired. It distinguishes from sibling tools like rc_get_customer_purchases which fetches a different 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?

The description provides no guidance on when to use this tool versus alternatives, no prerequisites or exclusions. It simply states what it does without context for selection.

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 describes the contents of the snapshot (apps, products, entitlements, customer sample) but does not disclose any potential side effects, authentication needs, or rate limits. Adequate for a read-only overview, but lacks extra behavioral context.

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 extraneous words. Front-loaded with the core purpose and a clear benefit statement.

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?

Completeness is high for a low-complexity tool with one optional parameter and no output schema. Explains the tool's composite nature and when to use it. Could mention the output structure or size limit of the customer sample, but 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?

Only one parameter (project_id) with full schema coverage. Description adds that if omitted, RC_DEFAULT_PROJECT_ID from env is used, which is valuable context beyond 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?

Clearly states the tool provides a one-shot overview of a RevenueCat project including apps, products, entitlements, and a small customer sample. Distinguishes from sibling tools like rc_list_apps, rc_list_products, etc., which are granular list tools.

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 says it cuts 4+ tool calls down to 1 when you want the big picture, implying use when needing a high-level overview. Does not explicitly state when not to use, but context is clear from the contrast with sibling tools.

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 bear the burden of behavioral disclosure. It only states 'list all apps,' but does not disclose potential pagination, sorting, or authentication requirements. However, for a simple list operation, this is minimally 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 a single, clear sentence with no unnecessary words. It efficiently conveys the tool's purpose and parameter context.

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 only one optional parameter and no output schema, the description covers all necessary aspects: what the tool does, what it lists, and the parameter's default behavior. It is complete for its simplicity.

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 already describes the project_id parameter, but the description adds context by mentioning it is a RevenueCat project ID and that it defaults from the RC_DEFAULT_PROJECT_ID environment variable. This goes beyond the schema description.

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 apps under a RevenueCat project, mentioning supported platforms (iOS, Android, web). This distinguishes it from sibling tools like rc_list_projects (which lists projects) and rc_list_products (which lists products).

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 does not provide explicit guidance on when to use this tool versus alternatives. It implies usage when needing to list apps within a project, but does not mention cases like checking all projects first or alternative tools for different resource types.

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 carry the burden. It discloses pagination behavior and implies that project_id can be omitted via environment variable (from schema). However, it does not mention rate limits, authentication needs, or safety (e.g., read-only hint), leaving gaps.

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 with no extraneous information. Every word serves a purpose, 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?

The tool has 3 parameters and no output schema or annotations. The description covers purpose and pagination but lacks details on response format, error handling, or what constitutes a 'customer.' This is adequate but may leave some agent users uncertain about the data returned.

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 project_id described). The description adds value for starting_after by explaining its function in pagination. For limit, no additional info is provided. This partially compensates for the low schema coverage.

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 'List customers in a RevenueCat project,' which specifies the verb (list) and resource (customers). This distinguishes it from sibling tools like rc_list_projects or rc_list_apps.

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 pagination guidance ('Paginate with starting_after (id of last item)'), which helps in using the tool effectively. However, it does not explicitly state when to prefer this tool over alternatives, though siblings target different entities, so 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 provided; description only states 'list entitlements' without disclosing any behavioral traits such as side effects, authentication needs, or response format.

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 sentence is efficient and front-loaded, but lacks any structural elements like bullet points or additional context.

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?

Adequate for a simple list tool with one optional parameter, but missing details about the response structure (e.g., fields returned) since no output schema is present.

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 one parameter described; description adds no extra meaning beyond the schema, matching the baseline for high coverage.

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 the verb 'list' and resource 'entitlements in a RevenueCat project', distinguishing it from sibling tools like rc_list_products and rc_list_customers.

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 explicit guidance on when to use this tool versus alternatives; lacks context on prerequisites or 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?

Without annotations, the description must disclose behavioral traits. It mentions pagination but omits read-only nature, authentication needs, rate limits, or side effects. The agent lacks key safety information.

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 succinct sentences covering purpose and pagination hint. No redundant text; 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 basic purpose and pagination, but lacks details on response format, ordering, or error handling. Given no output schema, more context on return values 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?

Schema coverage is low (33%). The description adds meaning for 'starting_after' by explaining its role in pagination, but does not elaborate on 'limit' constraints or 'project_id' details beyond schema. Partial compensation.

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 products (SKUs) configured in a RevenueCat project, with a specific verb and resource. It distinguishes from siblings that list other entities like apps or projects.

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 explicit guidance on when to use this tool versus alternatives like rc_list_projects or rc_list_apps. The name implies purpose, but no exclusions or context are provided.

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. The description does not disclose any behavioral traits such as pagination, rate limits, return format, or side effects. It only states the basic function, which is insufficient for a tool with no 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 a single sentence that is front-loaded with the purpose. No unnecessary words or repetition. It 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 the tool's simplicity (no parameters, no output schema), the description is mostly complete for listing projects. However, it does not mention pagination, response structure, or potential limitations, which would be helpful for an agent.

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 description does not need to add parameter info. The schema coverage is 100% (empty schema). The description does not add any parameter-specific meaning but is not required to.

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 'List' and the resource 'RevenueCat projects', and specifies the scope 'your secret key has access to'. It distinguishes itself from siblings like rc_list_apps which list apps, not projects.

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 explicit guidance on when to use or when to avoid, nor alternatives. However, the context implies it is a prerequisite for other RevenueCat operations. The description lacks explicit usage context.

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