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xultrax-web

agent-memory-mcp

by xultrax-web

check_action

Check a proposed action against enforcement rules to obtain a compliance receipt for destructive operations or receive structured violation warnings.

Instructions

v0.11.3 · the protocol enforcement point. Pass a proposed action description + its category; the server matches against rule memories (type=rule) and either:

  • APPROVES: returns a short-lived Compliance Receipt (HMAC-signed, 60s default) the agent can pass to destructive tools (e.g. delete_memory) as proof of compliance.

  • DENIES: returns structured hard_violations (severity:hard rules that block) and/or soft_warnings (severity:soft rules that warn but allow).

Tier 1 (deterministic) matches the action against rule.matches regexes + rule.enforce_on category filter. Works on every MCP client. Tier 2 (v0.11.7+) calls back to the client via MCP sampling/createMessage to judge rule.applies_when natural-language conditions. Auto-enabled on clients that declared the sampling capability; silently skipped on clients that didn't.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesDescription of the proposed action. Plain prose · 'delete the memory called X', 'push to main branch', 'commit with message Y', etc.
session_idNoOptional session identifier · binds the issued receipt to this session via a caveat.
action_typeYesAction category for rule.enforce_on matching. Examples: 'deletions', 'commits', 'pushes', 'file_writes', 'chat_responses', 'tool_calls'.
use_samplingNoOpt out of Tier-2 Sampling enrichment (default true). Set false for batched/scripted use where the Sampling round-trip would add latency. CLI invocations default this to false automatically.
Behavior5/5

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

With no annotations, the description fully carries the burden. It details two enforcement tiers, conditions for approval/denial, session caveats, and sampling behavior. No contradictions and provides complete behavioral insight.

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

Conciseness4/5

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

Well-structured with bullet points and subheadings, but slightly verbose. Every sentence is meaningful and front-loaded with a clear summary line. Minor reduction in length possible without losing clarity.

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

Completeness5/5

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

Despite no output schema, the description explains the two possible returns (Compliance Receipt or violations) and their structure. Covers all relevant aspects for tool usage including tiers and sampling. Complete for its complexity.

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

Parameters5/5

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

Schema coverage is 100%, but the description adds significant value: provides examples for 'action' (e.g., 'delete the memory called X'), explains 'action_type' categories, specifies 'session_id' binds via a caveat, and clarifies 'use_sampling' defaults. Greatly enhances understanding beyond the schema.

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?

Clearly states it is a 'protocol enforcement point' that checks actions against rule memories. Provides specific verb 'check_action' and resource 'rule memories', and distinguishes from other tools like 'delete_memory' by explaining its role as a compliance gate.

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?

Explanation includes when to use ('before destructive tools') and opt-out for sampling. However, it does not explicitly list when not to use or mention direct alternatives, though the context is clear from the tool's purpose.

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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