Add credits via credit card with volume bonuses. Returns a checkout_url. Tiers: $5 = 500 credits, $10 = 1,050 (+5%), $25 = 2,750 (+10%), $50 = 5,750 (+15%), $100 = 12,000 (+20%). Credits never expire. Requires api_key.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | Your ICME API key | |
| amount_usd | Yes | Top-up amount in USD: 5, 10, 25, 50, or 100 |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / amount_usd / descriptionPrevious value: -"Top-up tier in USD (5, 10, 25, 50, or 100)"New value: +"Top-up amount in USD: 5, 10, 25, 50, or 100"Input schema / properties / api_key / descriptionAdded value: +"Your ICME API key"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It discloses several key behaviors: volume bonuses, tier rewards, 'Returns a checkout_url,' 'Credits never expire,' and 'Requires api_key.' This provides a solid understanding of the tool's behavior beyond a simple 'add credits' statement.
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 front-loaded with the primary action. The tier list is necessary detail and presented in a clear, scannable format. It avoids fluff, and 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 the tool's simplicity (2 params, no output schema, no annotations), the description is quite complete. It explains the purpose, return value, bonus tiers, expiration policy, and authentication requirement. It lacks error-handling or post-payment expectations, but for a top-up tool, this is acceptable.
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 covers both parameters and their descriptions (100% coverage), so the baseline is 3. The description adds value by explaining the volume bonus structure (e.g., '$10 = 1,050 (+5%)'), which is not in the schema, and reiterates the api_key requirement. This enriches the meaning of the 'amount_usd' parameter.
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: 'Add credits via credit card with volume bonuses.' It specifies the payment method and the resource (credits), and the tier details further clarify the behavior. This distinguishes it from the sibling tool 'top_up', which likely handles a different payment method.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (when adding credits via credit card) but does not explicitly mention alternatives or exclusions. For example, it doesn't say 'use this instead of top_up for card payments.' So usage guidance is present but implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct role, but the presence of payment-method variants (check_action vs check_action_paid, create_account vs create_account_card, top_up vs top_up_card) introduces minor overlap that is clearly explained. The check tools are differentiated by output detail and purpose, though quick_check and check_action could be confused at a glance.
Names predominantly follow a verb_noun pattern (check_action, create_account, run_tests), with consistent _paid and _card suffixes for payment variants. Minor deviations like quick_check (adjective_noun) and top_up (phrasal verb) are understandable but break the pattern slightly.
With 14 tools, the set covers the full lifecycle of policy creation, testing, action checking, payment, and proof verification without bloat. Each tool serves a clear purpose within the service's scope.
The primary workflow (create policy, test policy, check actions, verify proofs) is well covered, including multiple payment options. Missing utilities like listing or deleting policies and credit balance checks are minor gaps that don't block the core use case.