Same formal verification as check_action, but pay per call with x402 ($0.10 USDC on Base) instead of using credits. No API key or account needed — any agent with a wallet can verify actions on the fly. Returns SAT (allowed) or UNSAT (blocked) with extracted values and optional ZK proof.
| Name | Required | Description | Default |
|---|---|---|---|
| action | Yes | The agent action to verify against the policy (max 2000 chars) | |
| policy_id | Yes | Policy ID from make_rules |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / action / descriptionPrevious value: -"Natural language agent action to verify (max 2000 chars)"New value: +"The agent action to verify against the policy (max 2000 chars)"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries the burden. It discloses the payment amount and method, the absence of account requirements, and the return format including optional ZK proof. It doesn't disclose potential failures or side effects, but verification implies non-mutating.
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 with high information density, front-loading the relationship to check_action and covering cost, authentication, and output.
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 2-parameter verification tool without output schema, the description fully covers the key aspects: payment, return type, and optional proof. The reference to check_action provides additional context.
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% coverage with descriptive parameter texts, so the description doesn't need to add much. It also doesn't add parameter-specific details 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?
The description clearly states the tool's function: formal verification of actions, similar to check_action, with the key differentiator of x402 payment. It specifies the output (SAT/UNSAT) and distinguishes it from siblings by 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?
It explicitly compares to check_action, indicating this is for paying per call with x402 instead of credits, and notes no API key or account needed. It implies usage when the agent has a wallet and wants on-the-fly verification, but doesn't provide explicit when-not-to-use scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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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.