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legal_litigation_hold_issue

Destructive

Issue a litigation hold by sending a message to the legal domain agent, optionally including structured inputs to define the preservation scope and requirements.

Instructions

Run the legal domain agent action litigation_hold_issue.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNo{}
messageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior3/5

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

The annotations already flag destructiveHint=true and readOnlyHint=false, and the description adds useful routing/scope context: it dispatches under the caller's JWT, tenant, and company scope. However, it does not disclose what changes when a hold is issued, what side effects or downstream obligations exist, or any authorization nuance beyond the generic scope statement. It does not contradict the annotations.

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 compact and front-loaded with the action name, followed by a short routing note and a clearly structured Args block. Every sentence serves a purpose, though the routing sentence could arguably be folded into the first line without loss.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having an output schema and only two optional parameters, this is a specialized legal action in a large sibling set. The description does not explain what a litigation hold is, what information is needed to issue one, or how this relates to `legal_litigation_hold_refresh` and `legal_litigation_hold_release`, leaving the agent under-equipped to invoke it confidently.

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 0%, and the description provides minimal compensation: `message` is a free-text objective and `inputs` is an optional JSON string. This is enough for a basic invocation, but it does not describe what structured inputs are expected or how they map to litigation hold semantics, so the agent still lacks concrete guidance for richer calls.

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 names a specific resource — the legal domain agent action `litigation_hold_issue` — and states that it runs through the platform's dispatcher. However, it does not explain what 'issue' means in business terms or differentiate it from siblings like `legal_litigation_hold_refresh` and `legal_litigation_hold_release`, so it is clear but not fully distinguishing.

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

Usage Guidelines2/5

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

There is no guidance about when to use this tool versus its litigation-hold siblings or other legal actions. The description only says to run the action; it does not state triggering conditions, exclusions, or alternatives, leaving the agent to infer usage from the tool name.

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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