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Mipiti
by Mipiti

set_control_assumption_groups

Replace the assumption group structure for a control: groups are OR'd, with all assumptions in a group AND'd. Pass an empty object to clear all groups and revert to not externally handled.

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 (min 10 chars when groups is non-empty; optional when clearing).
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations are provided, so the description bears full burden. It thoroughly discloses the tool's behavior: replacement semantics, clearing, AI gate with HTTP 422 responses, partial persistence, no force-override, and that assumptions remain in the model. This is exceptional transparency.

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 clear bullet points and sections, front-loading the main purpose. While somewhat lengthy, each section adds necessary detail for correct usage. Minor trimming could improve, but it remains effective.

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 complexity of the tool (AI relevance gate, partial acceptance) and lack of annotations, the description covers all essential aspects: invocation, parameters, success/failure responses, and edge cases. The presence of an output schema (not shown) reduces the burden, but the description is still very complete.

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?

The schema has 80% description coverage; the description adds value by explaining the groups JSON format, the justification length requirement (min 10 chars when non-empty), and the behavior of the groups parameter. It does not explain 'server_version', but overall adds useful semantics beyond the schema.

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: 'Declaratively set the assumption group structure for a control.' It explains the AND/OR semantics and how it replaces all assignments. This distinguishes it from siblings like 'set_mitigation_groups' and 'get_control_assumption_groups'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides detailed guidance on when to use the tool, including how to clear groups with an empty object, and explains the AI relevance gate behavior (partial/full acceptance, resubmit strategy). It covers the main usage scenarios comprehensively.

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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