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Mipiti
by Mipiti

auto_remediate

Close compliance gaps for a framework by mapping controls, excluding non-applicable requirements, and adding or restoring assets and attackers until fully covered.

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

Behavior5/5

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

With no annotations, the description fully discloses the three-phase process, soft-delete restoration details, response structure, and convergence behavior. Highly transparent about side effects and conditions.

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 clear sections, but somewhat lengthy. Every sentence is informative, but could be slightly more concise without losing detail.

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?

Given the complex process and presence of an output schema, the description thoroughly covers what the tool does, its phases, return values, and edge cases. Leaves no critical ambiguity.

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?

The description does not mention parameters. Schema coverage is 67%, so baseline is 3. No additional semantic value beyond what the schema provides. server_version lacks description and is not explained.

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 the tool's purpose: 'Automatically close compliance gaps for a framework.' Describes a three-phase loop and convergence. Distinguishes itself from siblings by focusing on automated remediation, distinct from mapping or manual gap-checking tools.

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?

Mentions it runs automatically but can be re-triggered manually when the model changes. States PRO tier requirement. Does not explicitly list alternatives or when not to use, but the context is clear enough.

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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