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Mipiti
by Mipiti

Set Control Assumption Groups

set_control_assumption_groups

Define or replace assumption groups for a control, using AND within groups and OR across them. Pass '{}' to clear all assignments.

Instructions

Declaratively set the assumption group structure for a control.

Replaces all assumption group assignments for this control. Each group is a set of assumption IDs that together externally handle the control; any one group being fully active+attested is sufficient.

  • Within a group: AND — all referenced assumptions must be active and attested for the group to count as complete

  • Across groups: OR — any one complete group marks the control as externally handled for mitigation purposes

To clear all assumption groups (revert to "not externally handled"), pass an empty JSON object: {}.

AI relevance gate (per group, no override): Each non-empty proposed group is evaluated independently. The behavior depends on how many groups pass:

  • All groups accepted → 200 success, structure persisted as submitted.

  • Some groups accepted (partial): the accepted groups ARE persisted (runtime OR-semantics activate immediately), the rejected groups are NOT saved, the call raises with HTTP 422 detailing both persisted_groups and rejected_groups (with per-group reasoning). Resubmit only the rejected groups with assumptions that cover the control, or sharpen those assumptions' descriptions.

  • All groups rejected: existing groups on this control are re-evaluated through the same gate. Relevant existing groups are preserved; irrelevant existing groups are dropped (assumptions themselves remain in the model — only this control's linkage is removed). The call raises with HTTP 422 detailing what was persisted, what was rejected, and what existing was dropped.

  • Empty submission ({}): clears all groups, no evaluation.

There is no force-override. To get a group accepted, choose assumptions whose descriptions actually cover the control or refine an assumption's description so coverage is explicit.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
groupsYesJSON object mapping group numbers to assumption ID lists. Example: '{"1": ["AS1", "AS2"], "2": ["AS3"]}' Empty object `{}` clears all groups.
model_idYesID of the threat model.
control_idYesID of the control (e.g., "CTRL-03").
justificationNoWhy this group structure is appropriate (10 to 2000 characters when groups is non-empty; optional when clearing, at most 2000 characters if given).
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.77.1
    • changedInput schema / properties / justification / description
      Previous value: -"Why this group structure is appropriate (min 10 chars\nwhen groups is non-empty; optional when clearing)."New value: +"Why this group structure is appropriate (10 to 2000\ncharacters when groups is non-empty; optional when clearing, at\nmost 2000 characters if given)."
  2. Addedv0.62.2
  3. Removedv0.62.0
  4. First observedv0.57.0

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It thoroughly explains the AI relevance gate, partial persistence, HTTP 422 behavior, preservation/dropping of existing groups, and the impossibility of force-override, which is far beyond a basic mutation description.

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 the complexity demands detail. Information is front-loaded with the core replacement behavior, followed by group semantics and edge cases. There is some redundancy around 'no force-override,' but the overall structure remains focused and useful.

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?

For a complex mutation tool with no annotations, the description covers the main operation, success and failure modes, side effects on existing data, clearing behavior, and remediation guidance. Since an output schema exists, the lack of return-value detail is acceptable.

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 80%, so the baseline is 3. The description adds important semantic meaning beyond the schema, especially the AND-within-group / OR-across-groups interpretation and the consequence of submitting rejected groups. This enriches the groups parameter meaning beyond the schema's simple JSON mapping.

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 opens with a specific verb and resource: 'Declaratively set the assumption group structure for a control.' It clearly states the full replacement behavior, which distinguishes it from get-style or mitigation/foundation sibling tools, even though no sibling is named explicitly.

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 operational guidance, including how to clear groups with an empty object, how partial acceptance behaves, and how to recover from rejected groups. It does not explicitly compare against alternatives like set_mitigation_groups, but the usage context is otherwise well defined.

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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