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Mipiti
by Mipiti

regenerate_controls

Regenerate controls from control objectives, preserving implementation status and mappings for unchanged descriptions, and soft-deleting altered ones. Optionally target specific control objectives.

Instructions

Regenerate controls from control objectives.

Controls whose descriptions survive regeneration unchanged preserve their implementation status, evidence, notes, assertions, Jira mappings, and compliance mappings. Controls with changed or removed descriptions are soft-deleted (queryable via include_deleted=True).

When co_ids is specified, only the controls for those COs are regenerated — other controls are preserved as-is.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNo"batch" (default) or "per_co" (most thorough, one LLM call per CO).batch
co_idsNoOptional comma-separated CO IDs to regenerate (e.g. "CO1,CO5"). When omitted, regenerates all controls.
model_idYesID of the threat model.
batch_sizeNoCOs per batch in batch mode (default: 15). Smaller = more accurate + granular progress, more LLM calls.
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description carries full burden. It discloses key behaviors: unchanged controls preserve status, changed/removed controls are soft-deleted (queryable via include_deleted=True), and selective regeneration via co_ids. This goes beyond bare functionality.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, front-loaded, and structured. First sentence provides purpose, second paragraph explains behavior, third provides selective usage. Every sentence adds value with zero waste.

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 existence of an output schema, return value explanation is unnecessary. The description covers regeneration behavior, mode options, and selective regeneration. It could mention prerequisites (e.g., model_id, server_version) but those are in the schema. It is fairly complete for a mutation tool.

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?

Schema description coverage is 80% (server_version undocumented). The description does not add significant meaning beyond schema descriptions for most parameters. It reinforces 'mode' and 'co_ids' usage but adds no new semantics for batch_size or model_id.

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 action ('Regenerate controls from control objectives') using a specific verb and resource. It distinguishes from sibling tools like 'refine_control' or 'auto_map_controls' by focusing on regeneration from control objectives.

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

Usage Guidelines3/5

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

The description explains how to use the tool (e.g., specifying co_ids for selective regeneration) but lacks explicit guidance on when to use this tool versus alternatives like 'refine_control'. It provides context on modes but no exclusion criteria.

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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