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by Mipiti

import_compliance_framework

Import a custom compliance framework when built-in frameworks don't cover your program, making it selectable on threat models.

Instructions

Import a custom compliance framework. Requires PRO tier.

Use this when your customer's program (regulatory, contractual, or internal) is not covered by Mipiti's 11 built-in frameworks. After import, the framework is selectable on threat models exactly like a built-in.

Schema (top-level fields): - name (required): framework display name - version (optional): e.g. "1.0" - description (optional): one-paragraph description - level_definitions (optional, level-aware frameworks only): map keyed by stringified integer level ("1", "2", …) because the key IS the cumulative-filter ordinal (level <= target_level) and the level: int field on every requirement. Non-integer keys are rejected with HTTP 400. Human labels are decoupled — "Baseline" / "Hardened" / "SL3" / "CAL Critical" live in the name field, not the key. Each value is {"name", "description", "source"}. Ships the per-level legend to the LLM prompt and the framework-target UI. source is "authoritative" when paraphrased from the published standard, "mipiti_convention" when you defined the tiers yourself. - requirements (required, non-empty list): each entry takes id (required), description (required), level (optional integer, default 1), chapter_id / chapter_name / section_id / section_name / title (optional grouping), scope (optional, "component" default or "system" for requirements covered if ANY model satisfies them), level_specific_text (optional map of per-tier text; same stringified-integer-key rule as level_definitions).

Example minimal body::

{
  "name": "ACME Internal Baseline",
  "version": "2026.1",
  "requirements": [
    {"id": "ACME-1", "description": "All endpoints authenticate", "level": 1},
    {"id": "ACME-2", "description": "TLS 1.3 in transit", "level": 1}
  ]
}

Example with per-level legend + per-requirement parameters::

{
  "name": "ACME Tiered",
  "level_definitions": {
    "1": {"name": "Baseline", "description": "Minimum.",
          "source": "authoritative"},
    "2": {"name": "Hardened", "description": "Sensitive data.",
          "source": "mipiti_convention"}
  },
  "requirements": [
    {"id": "ACME-PWD",
     "description": "Passwords meet policy",
     "level": 1,
     "level_specific_text": {
       "1": "Min 8 characters.",
       "2": "Min 14 + MFA required."
     }}
  ]
}

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
framework_jsonYesA JSON string containing the framework body. (String not dict so the JSON shape stays explicit on the wire.)
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 provided, the description fully carries the behavioral disclosure burden. It details validation rules (HTTP 400 for non-integer keys), the structure of level_definitions and requirements, and clarifies that the framework becomes selectable on threat models. There are no contradictions.

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 well-structured with a clear opening purpose, usage guidance, schema breakdown, and examples. It is slightly lengthy but each section adds necessary detail. The structure is front-loaded and logically organized.

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 tool's complexity (importing a nested JSON framework), the description is highly complete. It covers the input schema thoroughly, provides validation details, and includes examples. The presence of an output schema means return values don't need to be described.

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 adds substantial semantic value for the 'framework_json' parameter, providing a field-by-field breakdown with examples. However, the 'server_version' parameter is completely undocumented in the description, and the schema only has a 50% coverage. The baseline is 3 due to high coverage on one parameter but none on the other.

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 clearly states the tool's purpose: 'Import a custom compliance framework.' It specifies the triggering condition (when built-in frameworks don't cover the customer's program) and distinguishes this from other compliance tools like list_compliance_frameworks.

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 requires 'PRO tier' and explains when to use this tool ('when your customer's program ... is not covered by Mipiti's 11 built-in frameworks'). It also describes the post-import behavior (selectable like built-in). However, it does not explicitly state when not to use it or mention alternative tools.

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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