Review auto-generated test scenarios for a compiled policy. Shows example actions that should pass and fail, so you can verify the policy behaves as intended before deploying it. Requires api_key.
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | Yes | Your ICME API key | |
| policy_id | Yes | Policy ID from make_rules |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / api_key / descriptionAdded value: +"Your ICME API key"Input schema / properties / policy_id / descriptionAdded value: +"Policy ID from make_rules"Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. The word 'Review' and 'Shows' indicate a read-only operation, and the phrase 'before deploying it' implies non-destructive verification. It also notes the prerequisite that the policy must be compiled. It does not disclose potential side effects or limitations, but the read-only nature is strongly implied.
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 purpose. The first sentence states the core function, the second explains the value, and the redundant note about api_key is minimal. Every sentence contributes to understanding without unnecessary fluff.
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?
There is no output schema, so the description must convey what the tool returns. It does so by stating that it 'Shows example actions that should pass and fail,' which gives a clear idea of the output type. It also provides enough context for use. Minor gaps include not describing the output format in more detail, but it is sufficient for a tool of this complexity.
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 both parameters (api_key and policy_id), so the schema already provides full meaning. The description only restates that api_key is required, adding no new parameter semantics. 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 clearly states the tool's function: 'Review auto-generated test scenarios for a compiled policy.' It uses a specific verb ('review'), identifies the resource ('test scenarios'), and adds detail ('Shows example actions that should pass and fail'). This distinguishes it from siblings like run_tests and check_action, which have different purposes.
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 gives clear context for when to use the tool: 'so you can verify the policy behaves as intended before deploying it.' However, it does not explicitly mention alternatives or provide exclusion criteria, which would merit a 5. The context is clear enough to guide appropriate use.
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.