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GuardEntry MCP Server

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guardentry_evaluate_action

Evaluate proposed agent actions against policy to decide if allowed, blocked, or needs approval, returning a reasoned decision for pre-execution gating.

Instructions

Evaluate whether a proposed agent action is allowed, blocked, or requires approval based on the agent's policy. Returns a decision with reasoning. Use before any agent executes a sensitive task, tool call, or prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoEvaluation depth: fast (rules only), balanced (rules + LLM), strict (LLM with reasoning model)
policyNoInline policy object — when provided, skips store lookup entirely. Useful for testing policies without saving them.
agent_idNoUUID of the agent proposing the action (optional)
policy_idNoLoad a specific policy by ID from the store instead of the default cascade lookup
agent_nameNoHuman-readable agent name (used for policy inference if no policy exists)
agent_typeNoAgent type for policy lookup (e.g. 'compliance', 'vulnerability')
agent_toolsNoTools available to the agent (used for policy inference)
subject_typeYesType of subject being evaluated
subject_contentYesThe action text to evaluate (task description, tool argument, prompt, etc.)
Behavior3/5

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 reports the return type ('decision with reasoning') and implies non-execution via 'Evaluate' and 'Use before', but it does not explicitly state that the action is not executed or that there are no side effects. It also omits policy fallback/inference behavior, though the schema covers these details.

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

Conciseness5/5

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

Two sentences, front-loaded with the main purpose and followed by a direct usage directive. Every word earns its place; no redundancy or filler.

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

Completeness4/5

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

Given the tool's complexity (9 params, nested policy object, enums) and the rich schema descriptions, the description adequately orients the agent to core purpose and timing. It does not enumerate all subject types (missing 'plan' and 'tool_result') or the policy resolution cascade, but those gaps are largely filled by the extensive schema.

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

Parameters3/5

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 adds no extra parameter-level meaning; it does not explain how to choose mode, provide inline policy, or select subject_type beyond what the schema already documents.

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

Purpose5/5

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

The description uses a specific verb ('Evaluate') and clearly defines the decision output (allowed/blocked/requires approval). It distinguishes the tool from siblings like guardentry_get_agent_policy and guardentry_list_pending by focusing on policy-based action evaluation rather than policy retrieval or pending item listing.

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

Usage Guidelines4/5

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 before any agent executes a sensitive task, tool call, or prompt.' This provides clear invocation context. It does not name alternatives or exclusions, but the timing guidance is sufficient for most decision-making.

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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