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Mipiti
by Mipiti

Auto Remediate Compliance

auto_remediate_compliance

Automatically close compliance framework gaps by mapping existing controls, excluding non-applicable requirements, and adding or restoring assets and attackers until full coverage is achieved.

Instructions

Automatically close compliance gaps for a framework. Requires PRO tier.

Three-phase loop: (1) auto-map existing controls to unmapped requirements, (2) exclude requirements for non-applicable taxonomy primitives, (3) suggest and apply new assets/attackers for remaining gaps.

Phase (3) routes every proposal whose name matches a soft-deleted asset/attacker through the same restore-candidate LLM gate add_asset uses, so reanimating a previously removed entity reinstates its stable ID and every CO tombstone + control tied to it (rather than spawning a duplicate fresh ID). The response distinguishes assets_added / attackers_added (genuinely new) from assets_restored / attackers_restored (revived soft- deletes) and lists restored_asset_ids / restored_attacker_ids. Proposals the gate classified as similar (or that fail-closed on an unavailable / malformed gate response) appear under skipped with a per-entry reason — the operator decides whether to restore manually or rephrase.

Converges automatically: stops when fully covered or when no further progress can be made.

This runs automatically when a framework is selected, but can be re-triggered manually if the model changes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_idYesID of the threat model.
framework_idYesID of the compliance framework.
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.68.2

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and delivers exceptionally. It discloses the restore-candidate LLM gate shared with add_asset, the side effect of reinstating stable IDs along with CO tombstones and tied controls, fail-closed behavior when the gate is unavailable, per-entry skip reasons, response field distinctions (restored vs newly added), and automatic convergence.

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?

The description is long but information-dense, with purpose and prerequisite front-loaded before the phase breakdown. The phase-3 paragraph is the most verbose section, yet nearly every clause carries operational significance for a tool with this side-effect complexity. Minor tightening of the restore-candidate explanation would be possible without losing value.

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?

For a complex mutation tool with zero annotations, the description covers prerequisites, the full operational loop, side effects on soft-deleted entities, failure modes, concurrency behavior, and trigger conditions. The output schema covers return values, so the response-field explanation is bonus. The one real gap is server_version, a required parameter whose meaning appears nowhere in the schema or description.

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 coverage is 67%: model_id and framework_id are documented in the schema, and the description adds contextual meaning by tying framework to the remediation target and noting that model changes justify re-triggering. However, server_version is a required parameter with no schema description and no description-side compensation, leaving its semantics entirely unknown.

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 opening sentence states a specific verb and scope: "Automatically close compliance gaps for a framework." The three-phase loop then concretely defines what 'close' means (map controls, exclude non-applicable requirements, apply new assets/attackers), which clearly differentiates it from mapping-only siblings like auto_map_controls and check_control_gaps.

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 gives clear invocation context: it runs automatically when a framework is selected, can be manually re-triggered when the model changes, and requires PRO tier. However, it never explicitly names alternatives or states when not to use this tool (e.g., when only control mapping is needed versus full remediation with asset/attacker creation), leaving some routing inference to the agent.

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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