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create_assistant

Create an AI assistant persona in a workspace to customize investigation and action behavior. The short_name becomes the persona_name for workspace_chat.

Instructions

Create a new AI assistant (persona) in a workspace.

Skill: runwhen-skill://create-ai-assistant (full setup workflow).

An assistant is a persona that tailors how the RunWhen AI investigates and acts — e.g. an "Azure DevOps Helper" focused on a specific tech stack. The short_name you choose becomes the persona_name for workspace_chat.

After creating the assistant, shape its behavior by attaching persona-scoped rules and commands:

create_chat_rule(scope_type="persona", scope_id=short_name, ...)
create_chat_command(scope_type="persona", scope_id=short_name, ...)

This is an UPSERT — calling it again with an existing short_name REPLACES the assistant's full configuration (omitted fields reset to defaults). To change a few fields on an existing assistant, use update_assistant.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
avatar_urlNoOptional avatar image URL (e.g. '/personas/Man1-Happy.svg').
run_configNoRun configuration: allow/disallow/budget settings (advanced).
short_nameYesAssistant short name (lowercase-kebab-case, e.g. 'azure-devops'). Workspace prefix optional (e.g. 'my-ws--azure-devops'). This is the value you pass as persona_name to workspace_chat.
descriptionNoWhat this assistant specializes in (e.g. tech stack, team).
display_nameNoHuman-readable display name (e.g. 'Azure DevOps Helper').
filter_scopeNoOptional scope filter for results (advanced).
search_filtersNoVector-search filter operators (e.g. {'codebundleTaskTags': ['kubernetes'], 'slxGroup': ['my-group']}).
workspace_nameYesThe workspace to create the assistant in.
filter_stop_wordsNoWords stripped from search queries before matching.
run_confidence_thresholdNoConfidence threshold for automatic task runs (0-1).
filter_codebundle_task_tagsNoOnly surface tasks tagged with these (e.g. ['azure', 'devops']). Empty/omitted means no tag filter.
filter_confidence_thresholdNoConfidence threshold for filtering results (0-1).
filter_issue_selection_strategyNoIssue selection strategy (e.g. 'MOST_SEVERE').MOST_SEVERE

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Absent annotations, the description fully discloses behavior: it's an upsert, omitted fields reset to defaults, and the short_name becomes persona_name. It also explains the broader workflow of shaping behavior with chat rules/commands.

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 bullet points, but slightly verbose (e.g., repeating 'assistant' multiple times). Nonetheless, it is clear and front-loaded.

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?

With 13 parameters, no annotations, and output schema present, the description adequately covers creation behavior, upsert, and context. It doesn't detail return values (schema handles that). Missing some edge case handling notes, but sufficient.

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 coverage is 100%, so baseline 3. The description adds context for short_name (mapping to persona_name) and upsert behavior, but does not significantly elaborate on other parameters beyond schema definitions.

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 creates a new AI assistant persona in a workspace, distinguishes it from update_assistant and delete_assistant, and explains its relation to workspace_chat via persona_name.

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?

It explicitly says when to use (create new assistant), when to use update_assistant (to change few fields), and mentions attaching rules/commands afterward. No ambiguity.

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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