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Mipiti
by Mipiti

set_control_assumption_groups

Set the assumption group structure for a control using OR across groups and AND within each group. AI evaluates relevance before persisting.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It comprehensively covers the tool's behavior: declarative replacement, AND/OR semantics across groups, clearing with empty object, AI relevance gate with per-group evaluation and outcome details (partial, all rejected, existing re-evaluation), and the lack of force-override. This is highly transparent.

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 relatively long but well-structured with clear bullet points and sections. It front-loads the main purpose and then details edge cases. Every sentence contributes value, though it could be slightly more concise without losing clarity.

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 (5 parameters, output schema exists), the description is thoroughly complete. It explains all edge cases: partial acceptance, all rejection, empty submission, AI gate behavior, and existing group re-evaluation. With the output schema, return values are adequately covered for agent invocation.

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 description coverage is 80% (4 of 5 parameters described in schema). The description adds critical context beyond schema, such as the grouping logic, AI gate behavior, and an example for the 'groups' parameter. The 'justification' parameter gets additional context ('min 10 chars when non-empty'). The description significantly enriches parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

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 specifies that it replaces all assignments and explains the group semantics. However, it does not explicitly differentiate from sibling tools like set_mitigation_groups or set_functional_satisfaction_groups, which have similar patterns.

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 provides extensive guidance on when to use the tool, including detailed scenarios for partial acceptance, all rejection, and empty submissions. It explains the AI relevance gate and notes that there is no force-override. However, it does not explicitly mention when not to use this tool or suggest alternative tools, which would be helpful.

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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