ActionGate

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds context by specifying that both balance and usage count are returned, which goes beyond the tool name but does not disclose additional behavioral traits such as rate limits or error conditions.

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, straightforward sentence that is efficiently front-loaded. Every word contributes to specifying the tool's purpose without unnecessary detail.

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 tool with one parameter and no output schema, the description sufficiently explains what the tool returns. It lacks explicit response formatting but given the simplicity and rich annotations, it is adequately complete for an AI agent to select and invoke 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?

The input schema fully describes the only parameter (api_key) with a pattern and description, so schema coverage is 100%. The description does not add further meaning about the parameter, so the baseline of 3 applies.

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

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

The description clearly states the action ('Return') and the resource ('current prepaid credit balance and usage count for an ActionGate API key'). It is specific and distinguishes the tool from siblings such as top_up, which adds credits rather than reading balance.

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

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

No guidance is provided on when to use this tool versus alternatives. For example, it does not mention checking balance before topping up or that top_up is used for adding credits. The functionality implies usage, but no explicit context or exclusions 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?

Annotations already declare read-only, idempotent, and non-destructive hints. The description adds valuable behavioral context beyond annotations by disclosing the payment mechanism ('Paid via x402 or API key credits') and rate limits ('Free tier: 10 policy gate calls/day per client'). This helps the agent anticipate costs and usage constraints.

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

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

The description consists of two concise, front-loaded sentences. The first sentence states the core function and return values; the second adds pricing and rate limit context. No wasted words or repetition of schema details.

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 correctly specifies the high-level return values (allow, deny, allow-with-limits). It also includes billing and quota context. However, it does not describe the return object's structure (e.g., whether reasons or metadata are included), which would be helpful for an agent for full understanding, but the current coverage is adequate for basic invocation.

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 provides 100% coverage with descriptions for all parameters. The tool description does not add parameter-specific semantics beyond what the schema already contains, so it meets the baseline for good schema coverage without exceeding it.

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

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

The description uses a specific verb ('Apply') and resource ('treasury policy') and clearly states the outcome ('return allow, deny, or allow-with-limits'). This distinguishes it from sibling tools like 'risk_score' or 'simulate' by defining a distinct decision output.

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 intended use case is implied ('Apply treasury policy to a proposed action'), but the description does not explicitly state when to use this tool versus alternatives, nor does it provide exclusions or when-not-to-use guidance. Sibling tool names offer context but aren't referenced.

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 already indicate a non-read-only, idempotent, non-destructive operation. The description adds meaningful context beyond annotations by specifying the prepaid $1.00 credit amount and that the key is provisioned for the operator email, giving useful behavioral detail without contradicting the 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 one sentence, front-loaded with the action verb, and contains no superfluous words. Every phrase (prepaid, $1.00, starter credits, operator email) adds distinct value.

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

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

For a single-parameter tool with annotations and no output schema, the description covers the core action, recipient, and funding detail. It does not explicitly mention what the response returns (e.g., the key itself) or prerequisites like email verification, but these are minor given the annotations and the tool's 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 fully describes 'email' as the operator email that should own the key, and the description simply confirms this with 'for this operator email.' No additional parameter meaning is provided, so the schema carries the semantic burden; the description adds no new syntax or format 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 uses a specific verb ('Provision') and resource ('prepaid ActionGate API key') with precise details ($1.00 of starter credits, operator email). It clearly distinguishes this tool from siblings like 'top_up' (adding credits later) and 'balance' (checking credits).

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

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

The description implies this tool is used when an operator needs a new API key with initial credits, but it does not explicitly state when to use it versus alternatives like 'top_up' or 'balance'. There are no exclusions or alternative references, so usage guidance is only implied.

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 adds valuable behavioral context beyond the annotations, specifically that the tool is paid via x402 or API key credits with a free tier of 20 calls/day. This is not disclosed in the annotations or schema. The description does not contradict the readOnlyHint or idempotentHint.

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

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

The description is two sentences, front-loaded with the primary purpose, and every word earns its place. The second sentence provides critical billing/quota details without bloat.

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, combined with rich schema and annotations, provides enough context for an agent to select and invoke the tool correctly. It covers purpose, payment, and rate limits, though it does not describe the exact return format (risk score value/range), which is not critical for selection.

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

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

The input schema has 100% description coverage for all parameters, including nested objects. The description itself adds no parameter-specific meaning, but the schema already does the heavy lifting. Baseline of 3 is appropriate.

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

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

The description clearly states the tool's function: scoring the risk of a proposed agent action before execution. It uses a specific verb ('score') and resource ('risk of a proposed agent action'), and the timing ('before execution') distinguishes it from other tools like simulate or policy_gate.

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 for when to use the tool (before executing an agent action), but it does not explicitly mention alternatives or when not to use it. The payment and rate-limit information also helps set expectations for usage.

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 already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds valuable behavioral context about billing and quotas: 'Paid via x402 or API key credits. Free tier: 20 simulate calls/day per client.' This goes beyond the annotations and helps the agent understand cost implications. No contradiction with 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 exceptionally concise: two sentences, zero wasted words. It front-loads the core purpose in the first sentence and adds the critical billing/rate-limit context in the second. 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?

For a tool with 4 parameters, nested objects, and no output schema, the description is complete enough: it identifies the three output components (cost, failure risk, side effects) and covers key usage context (pricing/free tier). While it doesn't describe return formatting or error cases, the core information needed to invoke and interpret the tool 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 description coverage is 100%, so the input schema fully documents all parameters. The description does not add any additional parameter-level meaning beyond what the schema already provides, meeting the baseline for good 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 the tool's function: 'Estimate cost, failure risk, and notable side effects for a proposed action.' This specific verb+resource combination distinguishes it from siblings like risk_score, which likely only provides a risk score, and balance/top_up, which deal with funds. The scope is explicit 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 for pre-action evaluation ('for a proposed action') and mentions payment/rate limits, but it does not explicitly state when to use this tool versus alternatives like policy_gate or risk_score. No exclusions or alternative tools are named, so guidance is only implied rather than explicit.

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 already indicate this is not read-only and not idempotent, and the description adds that it involves Stripe Checkout and human operator action. It does not disclose the full flow (e.g., whether credits are applied immediately or only after payment), but the annotation coverage lowers the burden. The description adds some context beyond annotations without contradiction.

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, front-loaded sentence that begins with the action verb 'Generate' and immediately communicates purpose. Every word is informative, and there is no redundancy or filler.

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 only two parameters and no output schema, the description adequately conveys the core purpose and context. It explains the external integration (Stripe) and the actor (human operator). It stops short of describing follow-up steps or edge cases, but given the simplicity of the tool, the description is sufficiently 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 description coverage is 100%, so the baseline is 3. The description does not add extra parameter semantics beyond what the schema already provides for api_key and tier. It mentions prepaid credits and existing API key but does not elaborate on tier options or validation, making this a neutral contribution.

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 generates a Stripe Checkout link for adding prepaid credits to an existing ActionGate API key. It uses a specific verb (generate) and resource (Stripe Checkout link), and distinguishes itself from siblings like request_api_key (which creates new keys) and balance (which checks balance).

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: it is for a human operator to add credits to an existing key. It implies use when an existing key needs topping up, but does not explicitly mention alternatives or exclusion criteria. The 'existing' qualifier and mention of 'human operator' offer practical guidance without naming sibling tools.

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