Stripe_connect

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

With no annotations provided, the description fully discloses that Pipeworx picks the right tool, fills arguments, and returns results, making the autonomous behavior clear.

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?

Description is concise (4 sentences) and front-loaded with purpose, immediately followed by how it works and examples.

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 single parameter and no output schema, the description adequately explains the tool's autonomous behavior and provides examples, making it complete 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?

Schema coverage is 100% for the single 'question' parameter, and the description adds examples but no further semantics beyond what the schema already provides.

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 takes a plain English question and returns an answer from the best available data source, distinguishing it from sibling tools that are specific to memory or Stripe operations.

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 'No need to browse tools or learn schemas' and provides examples, indicating this tool should be used for general queries instead of selecting specific 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?

With no annotations, the description bears full responsibility. It discloses that data is from SEC EDGAR (for companies) and what fields are returned for each type. It does not mention auth, rate limits, or side effects, but since the operation is read-only, the lack of destructive warnings 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 extremely concise—four sentences that cover purpose, type breakdown, output summary, and efficiency benefit. No redundant 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?

The output schema is absent, and the description only vaguely mentions 'paired data + pipeworx:// resource URIs'. The structure of the returned data is not detailed, which could confuse an agent. Given the tool's comparative nature, more clarity on output format 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?

Input schema has 100% description coverage. The description adds value by providing concrete examples (e.g., ["AAPL","MSFT"]) and mapping 'type' to specific data fields, enriching the schema's meaning.

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 that the tool compares 2–5 entities side by side, specifies two types (company and drug) with distinct data fields, and mentions the data source (SEC EDGAR for companies). It distinguishes itself from sibling tools, which are unrelated (e.g., Stripe, memory).

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 notes that one call replaces 8–15 sequential agent calls, indicating efficiency. It does not explicitly state when not to use it or name alternatives, but the context (siblings like resolve_entity) implies single-entity use cases. Some guidance on preconditions (e.g., valid tickers/drug names) is implicit.

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?

Annotations are absent, so description must cover behavior. It states it returns 'most relevant tools' but doesn't specify search algorithm, sorting, or whether it uses embeddings/keywords. However, it adds value by mentioning the tool count context (500+ tools) and search method ('natural language').

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 serving a purpose: what it does, what it returns, when to call it. Could combine last two sentences for tighter structure, but no waste.

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, description explains what is returned (tool names and descriptions). For a search tool with simple parameters, this is sufficient. Could mention return limit behavior but schema covers that.

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%, so baseline is 3. Description adds context by explaining the query parameter format with examples ('analyze housing market trends') and default/max for limit. This goes beyond the schema's terse 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?

Clearly states verb ('search'), resource ('Pipeworx tool catalog'), and how it works ('natural language query'). Distinguishes from siblings like 'ask_pipeworx' by specifying it returns tool names and descriptions, not general answers.

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 'Call this FIRST when you have 500+ tools available', giving clear when-to-use guidance. No alternatives needed as this is the primary discovery tool.

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 discloses that the tool returns citation URIs and replaces 10–15 sequential calls, and notes that person/place support is coming soon. However, it does not explicitly state that this is a read-only operation, nor does it mention authentication or rate limits. The description is fairly transparent but could be slightly more explicit about the safe nature of the call.

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 moderately long but every sentence adds value: it states the purpose, lists data sources, mentions return format, explains bundling efficiency, and gives exclusion guidance. It front-loads the main action and is well-structured for an agent to parse quickly.

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 of the tool (2 parameters, no output schema), the description covers the key aspects: what it does, what data it aggregates, when to use an alternative, and a hint about future types. It could mention the output structure more explicitly, but the mention of pipeworx:// URIs provides a useful expectation. The description is largely complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% (both parameters described). The description adds significant value beyond the schema by explaining that only 'company' type is supported ('person/place coming soon') and that value accepts ticker or CIK, not names, with a usage hint to use resolve_entity. This enriches the agent's understanding of valid inputs.

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 that the tool returns a full profile of an entity across multiple Pipeworx packs, listing specific data sources (SEC filings, XBRL, patents, news, LEI) and the return format (pipeworx:// URIs). It distinguishes from siblings by explicitly mentioning when to use an alternative (usa_recipient_profile for federal contracts).

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 when to use this tool vs alternatives: for federal contracts, call usa_recipient_profile directly. It also advises that names are not supported and to use resolve_entity first if only a name is available, which helps the agent choose the correct tool.

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 must carry full burden. It states deletion behavior but lacks details on reversibility, confirmation, or side effects. Adequate but could be more transparent.

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 with no wasted words. Front-loaded with verb and resource. Every word 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?

For a simple delete operation with one required parameter and no output schema, the description is complete enough. It explains the action and the required key.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and description adds no extra param info. Baseline is 3, but given the single required param with clear schema description, the tool is straightforward. Description is consistent and 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?

Description clearly states it deletes a stored memory by key, specifying verb (delete) and resource (stored memory). It distinguishes from sibling tools like remember (create) and recall (retrieve).

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?

Description implies when to use (when needing to delete a memory), but does not explicitly exclude alternatives or provide when-not scenarios. However, sibling names suggest complementary functions, making usage 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 carries the full burden. It discloses rate-limiting (5 per identifier per day) and the requirement to describe issues in terms of Pipeworx tools/data. It could mention whether feedback is anonymous or if a confirmation is returned, but the provided details are sufficient for an agent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three short sentences, each adding vital information without redundancy. It is front-loaded with the main verb 'Send feedback' and immediately follows with allowed categories and usage hints.

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 simplicity of the tool (feedback submission with no output schema), the description covers purpose, usage constraints, and rate limiting. It could mention whether a response is expected, but for a feedback tool this is acceptable 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 100% and each parameter already has clear descriptions (e.g., type enum with explanations, context optional with fields). The description adds minimal value beyond reinforcing specificity; it does not introduce new meaning not already 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 the tool's purpose: sending feedback to the Pipeworx team. It enumerates specific use cases (bug reports, feature requests, missing data, praise) which distinguishes it from sibling tools like ask_pipeworx or stripe 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?

The description tells when to use the tool and provides explicit guidance on what to avoid (do not include end-user's prompt verbatim) and rate limits. However, it does not mention alternatives or when not to use it, but the tool's unique purpose makes that less critical.

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

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

No annotations exist, so description carries full burden. It states the tool retrieves memories across sessions and lists all when key is omitted. However, it doesn't disclose potential size limits, persistence guarantees, or performance implications of listing all memories.

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 that front-load the main purpose. No wasted words. Could arguably merge the second sentence into the first, but it's clear.

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 only 1 parameter, no required params, and no output schema, the description is sufficiently complete. It explains both use cases (single key retrieval and listing all) and their context (across sessions).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. The description adds context about the optional key parameter behavior ('omit to list all keys') but doesn't add beyond what schema's description already implies.

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 ('Retrieve', 'list') and a clear resource ('previously stored memory by key'), and distinguishes between two modes of operation. It contrasts with siblings like 'remember' and 'forget' by focusing on retrieval.

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 this tool ('to retrieve context you saved earlier') and when to omit the key to list all memories. However, it does not provide when-not-to-use or alternatives among siblings (e.g., preferring 'discover_tools' for other context).

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 the tool fans out to SEC EDGAR, GDELT, and USPTO in parallel, and describes the input format for 'since' parameter (ISO date or relative). It also mentions the return includes structured changes, total_changes count, and URIs. While it doesn't detail error handling or rate limits, it covers the core behavioral traits sufficiently.

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 and well-structured: it starts with the purpose, then details behavior, parameter usage, return value, and use cases. Every sentence adds value 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 the complexity (parallel queries across multiple sources) and the absence of an output schema, the description adequately describes what is returned (structured changes, count, URIs). However, it could be more complete by elaborating on the structure of 'structured changes' or mentioning potential delays from parallel sources.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds value by explaining the 'type' is only 'company', the 'since' parameter accepts relative formats like '7d', '30d', etc., and the 'value' can be a ticker or zero-padded CIK. This goes beyond the schema's basic descriptions, providing practical guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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

The description states the tool's purpose clearly: 'What's new about an entity since a given point in time.' It gives concrete behavior for type 'company' with fan-out to multiple sources, and distinguishes from siblings by focusing on temporal change monitoring, as indicated by the use case 'brief me on what happened with X'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use the tool: 'Use for 'brief me on what happened with X' or change-monitoring workflows.' It also mentions that only 'company' type is supported, implying it should not be used for other entity types. However, it does not provide explicit alternatives or when-not-to-use scenarios, which would elevate it to a 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 provided, but description covers persistence differences between authenticated vs anonymous sessions (persistent vs 24-hour TTL). This is valuable behavioral context beyond schema.

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 key info front-loaded: purpose, use cases, and persistence behavior. 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 simple schema (2 string params) and no output schema needed, description is complete. Covers purpose, use cases, behavioral nuance (auth vs anonymous), and parameter semantics sufficiently.

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 has 100% coverage with clear descriptions for key and value. Description adds usage examples (e.g., 'subject_property') and clarifies value can be any text. Provides good context without redundancy.

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 the tool stores a key-value pair in session memory, with specific examples of what to store. Differentiates from sibling tools like 'forget' and 'recall' by its focus on storage.

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 when to use (save intermediate findings, user preferences, context across calls). No explicit when-not-to-use or alternatives, but sibling context makes it clear.

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

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

No annotations are provided, so the description must disclose behavior. It explains the return values but does not mention whether the operation is read-only, idempotent, or requires authentication. The description is adequate for a lookup tool but lacks explicit safety guarantees.

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. First sentence states the overall purpose; second provides version, accepted inputs, and return value. Every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description covers the return fields (ticker, CIK, company name, URIs). It does not address error handling or edge cases, but for a simple lookup tool, it is fairly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds value by explaining that 'type' is limited to 'company' and 'value' accepts ticker, CIK, or name with concrete examples, enriching the 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 the verb 'resolve' and the object 'entity to canonical IDs', specifying it consolidates multiple lookups (replaces 2–3 calls). The purpose is unambiguous and distinguishes it from broader tools like ask_pipeworx.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states the supported entity type ('v1: type="company"') and provides example inputs (ticker, CIK, name). It implies when to use (instead of multiple lookup calls) but lacks explicit 'when not to use' or comparison to 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?

Annotations are empty, so the description must carry the burden. The description mentions the action (get balance) but does not disclose behavioral traits like whether it's read-only, if it requires specific permissions beyond the API key, or what the response format looks like. However, the verb 'Get' strongly implies a read operation, and the tool is simple, so a 3 is appropriate.

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, concise sentence that front-loads the purpose. Every word earns its place with no wasted content.

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 is simple with one parameter and no output schema. The description is complete enough for its purpose, but it could mention that the balance is returned in various currencies or that it's the current balance. Still, for a straightforward tool, a 3 is reasonable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the one parameter (_apiKey), which is already well-described in the schema as a 'Stripe secret or restricted API key'. The description adds no additional meaning beyond the schema. Baseline 3 is appropriate since schema covers it fully.

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 the current Stripe account balance, using the specific verb 'Get' and the resource 'current Stripe account balance'. It distinguishes itself from sibling tools that deal with customers, charges, invoices, or subscriptions, as those are all about other 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 the tool is for checking the overall balance but does not explicitly state when to use it versus alternatives. It does not mention when not to use it, such as for historical balances or other financial details, nor does it reference sibling tools for comparison.

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

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

The description indicates a read operation (get). No annotations are present, so the description must carry the burden. It doesn't mention idempotency, error conditions, or rate limits. Adequate but lacks depth.

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: one sentence of 6 words. No wasted words. Front-loaded with the verb 'Get' and resource.

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 simplicity (2 params, no output schema), the description is minimally adequate. It explains what it does but could mention return structure or that it's a read operation. Still, it's sufficient for a straightforward retrieval tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, and the description adds no additional meaning beyond the schema. The schema already explains id and _apiKey. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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

The description clearly states the tool retrieves a Stripe customer using an ID. The verb 'Get' is specific, and the resource is a customer. It distinguishes from siblings like stripe_list_customers which lists multiple 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?

The description implies usage when you have a customer ID and need to retrieve details. However, it does not provide guidance on when not to use it or mention alternatives for listing customers.

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?

Annotations are empty, so the description bears full burden. It only says 'recent' which is vague. No disclosure of pagination, rate limits, data freshness, or what 'recent' means (e.g., last 7 days?). No mention that this is a read-only operation.

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 short phrase, which is concise but lacks structure. It fits in one sentence but could be more informative without adding much length.

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 is a list operation with 3 parameters and no output schema, the description is insufficient. It doesn't explain the default ordering, pagination, or that results are limited by the 'limit' parameter. Lacks completeness for a data-fetching 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?

Schema coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning beyond the schema, but the schema itself is clear. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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

The description 'List recent charges' clearly states the verb (list) and resource (charges), with an implicit time scope (recent). It distinguishes from siblings like stripe_list_customers and stripe_list_invoices by specifying charges.

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 versus alternatives. For example, it doesn't mention that to list charges for a specific customer, the customer parameter should be used, or contrast with other list tools. The description provides no when/when-not or 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; description only mentions pagination but does not disclose read-only nature, rate limits, or auth requirements beyond schema. Schema already documents _apiKey as required.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two short sentences, no wasted words, but could be slightly more informative 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?

Given no output schema and moderate complexity (3 params, pagination), the description is too brief. Does not explain return format, sorting, or filtering options.

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% and already describes all three parameters adequately. Description adds no additional meaning beyond 'supports pagination'.

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 lists Stripe customers and supports pagination, which distinguishes it from siblings like stripe_get_customer (singular) and stripe_list_charges/invoices/subscriptions (different 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 on when to use this vs. other list tools or stripe_get_customer. Does not mention typical use cases or limitations.

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?

Annotations are empty, so description carries full burden. It lacks details on behavior: e.g., does it return all invoices or paginate? Is it read-only? The description only says 'List invoices' without disclosing the default limit or that it lists across all customers.

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 short (two words), which could be seen as concise, but it omits essential context. It is not front-loaded with key information; it lacks the word 'Stripe' and any scope indication.

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 explain return format, but it does not. The tool lists invoices, but the description is incomplete: it does not mention pagination, filtering capabilities, or that it requires an API key (though required in 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?

Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema, but it is not required to since the schema is comprehensive. However, no extra context is provided, so score is slightly above baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

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

The description 'List invoices' is too vague. It doesn't specify the resource (Stripe) or any scope. Sibling tools like 'stripe_list_charges' and 'stripe_list_customers' provide similar patterns, but the description does not distinguish 'stripe_list_invoices' from them.

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. No mention of filters or when to use other listing tools. The description does not indicate that it lists all invoices by default or that it can be filtered by customer or status.

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 doesn't disclose behavioral traits like whether it's a read operation (safe), or any authentication requirements beyond the parameter. The word 'active' suggests default filtering, but this is not explicit.

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?

Very concise single sentence with no wasted words. Could be slightly improved by front-loading the default behavior, but it's 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 output schema, the description could mention that it returns a list of subscription objects. The parameter coverage is complete, but behavioral details missing. It's adequate for a simple list tool but not thorough.

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%, so baseline is 3. The description adds no additional meaning beyond what the schema provides for parameters. It does not mention that the default status is active, which would be useful.

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 lists active subscriptions, with a specific verb 'List' and resource 'subscriptions'. However, it doesn't distinguish from sibling tools like 'stripe_list_customers' or 'stripe_list_invoices', but the resource is unique enough.

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. The description doesn't mention filtering options or that it returns active subscriptions by default, but provides no context for when to use other list 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 present, so the description carries the full burden. It discloses key behaviors: uses SEC EDGAR + XBRL, supports only financial claims, returns specific output with citations and delta. However, it omits details on rate limits, authentication, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loaded with purpose, and each sentence adds value: purpose, scope, output, and benefit. 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 complexity and no output schema, the description adequately explains return values (verdict types, citation, delta) and data sources. It could mention error handling or unsupported claim types, but is sufficiently complete for a single-parameter 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?

Schema description coverage is 100% with examples in the schema. The tool description does not add significant parameter-level detail beyond what the schema already provides, matching the baseline score 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 tool fact-checks natural-language claims against authoritative sources, specifies the domain (company-financial claims for public US companies), and lists return values (verdict, structured form, actual value, citation, delta). It distinguishes itself from unrelated siblings with a clear verb and 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 clear context on when to use: for company-financial claims, replacing multiple sequential calls. It does not explicitly state when not to use or mention alternatives, but implies scope with 'v1 supports company-financial claims', which is a limitation.

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