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by Mipiti

import_compliance_framework

Import a custom compliance framework to add regulatory, contractual, or internal requirements not in built-in frameworks. After import, it becomes 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

Behavior4/5

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

Since no annotations are provided, the description carries the full burden. It discloses the PRO tier requirement (auth), post-import behavior (selectable on threat models), schema constraints (e.g., non-integer keys rejected with HTTP 400), and semantics of fields like 'source' and 'level_specific_text'. It does not mention processing time or limits, but is otherwise thorough.

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 quite long but well-structured with clear sections, bullet points, and code examples. It front-loads the essential purpose and usage. Some redundancy exists (e.g., repeating schema inline), but overall it's organized for easy comprehension.

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 and the presence of sibling tools for listing/selecting frameworks, the description adequately explains the import action and its place in the workflow. It covers prerequisites (PRO tier), behavioral impact, and schema details. It does not explicitly mention the output schema (though context indicates it exists), but that's not critical for usage.

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

Parameters4/5

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

Schema coverage is 50% (only 'framework_json' described). The description extensively details the expected JSON structure with examples, including required/optional fields, nested structure, and key constraints. This adds significant meaning beyond the schema. However, 'server_version' is not described, leaving a gap.

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 'Import a custom compliance framework' and explains the purpose: to bring in frameworks not covered by Mipiti's 11 built-in ones. It also specifies that after import, the framework behaves like a built-in (selectable on threat models). This distinguishes it from siblings like 'list_compliance_frameworks' or 'select_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 says 'Use this when your customer's program is not covered by Mipiti's 11 built-in frameworks', providing clear when-to-use guidance. It also mentions the PRO tier requirement. However, it doesn't explicitly state when not to use (e.g., if the framework already exists), but the context is sufficient.

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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