Skills

Skills are reusable prompt templates that you invoke in AI chat using the / slash syntax. They let your team codify repeatable workflows like bug triage, spec writing, standup summaries, and more — so anyone can get consistent, high-quality AI assistance without crafting the perfect prompt each time.

How Skills Work

Type / in the AI chat input to open the skill list
Select a skill from the dropdown (or keep typing to filter)
Add any additional context to your message
Press Enter to send

The skill's prompt is injected as system context for the AI, guiding its response. You can combine skills with regular text, file attachments, and references to people or records.

Referencing People and Records

Skills support three types of inline references that provide the AI with additional context:

Syntax	What It Does	Example
`@member`	References a team member — the AI receives their name, role, and organization	`@alice`
`#DISPLAY-ID`	References a record — the AI receives the full record content	`#TSK-001`
`/skill`	Chains another skill — its prompt is included alongside the current one	`/triage-issue`

These references work in both your chat messages and inside skill prompt bodies. When the AI processes your message, all references are resolved into rich context automatically.

Built-in Skills

A fresh workspace starts with no skills — the list is empty until you (or an installed plugin) add them.

Some plugins ship their own built-in skills that appear automatically once the plugin is installed. Built-in skills cannot be edited directly. To customize one, click Duplicate to create your own editable version.

Creating Custom Skills

From the Operator App

Space administrators can create skills available to all workspace members:

Open the Operator app from the sidebar
Click the Assets button (the layers icon) in the top toolbar to open the Assets panel
In the Assets tree, use the New Skill action to open the skill editor
Fill in the skill details:
- Name: A descriptive name (e.g., "Sprint Retrospective")
- Shortcut: Auto-generated from the name (e.g., /sprint-retrospective) — this is what users type in chat
- Description: A short summary shown in the skill list
- Instruction: A plain-English description of what you want the AI to do — the primary authoring surface
- Prompt Body: The engineered prompt sent to the AI. Leave blank to use the Instruction as-is, or use Build Prompt to generate one automatically.
Set the visibility (Space, Organization, Team, or Private)
Save the skill

Instruction vs Prompt Body

Field	Purpose
Instruction	Plain-English description of what the skill should do. Written by you. Used as fallback when Prompt Body is blank.
Prompt Body	The full engineered prompt sent to the AI — with workspace references, structured instructions, and tone guidance. Can be hand-written or generated using Build Prompt.

If Prompt Body is left blank, the Instruction is used directly. This means a skill is immediately usable with just an Instruction — no prompt engineering required.

Writing Effective Prompts

The prompt body editor supports rich formatting:

Text formatting: Bold, italic, underline, strikethrough
Structure: Headings (H1-H3), bullet lists, numbered lists, blockquotes
References: @member mentions, #record references, /skill chains

Tips for writing good skill prompts:

Be specific about the role: Start with "You are a [role]" to set context
Define the output format: Describe what the response should look like
Reference workspace resources: Use #id or /skill to point the AI at relevant records, schemas, and playbooks — it will look them up at runtime rather than relying on static text
Keep it focused: One skill should do one thing well
Use chaining: Reference other skills with / to compose complex workflows

Skill Chaining

Skills can reference other skills using the / syntax in their prompt body. When a skill is invoked, any referenced sub-skills are resolved recursively (up to 3 levels deep) and their prompts are included in the AI context.

For example, a /weekly-review skill could reference /summarize-week and /triage-issue to combine their capabilities.

Advanced: Build Prompt Wizard

The Build Prompt button in the skill editor runs an AI agent that explores your workspace and constructs a high-quality prompt automatically. The agent reads your databases, schemas, documents, and existing skills — and produces a prompt that references your specific workspace resources by ID rather than copying their content.

How It Works

Write an Instruction and add Evaluation Criteria (see below)
Click Build Prompt in the skill editor header
A readiness check scores your setup — the more criteria and sample inputs you provide, the better the output
Click Build Prompt to start — the wizard runs 8 steps in sequence:
- Prepares your criteria and sample inputs (in parallel)
- Builds an initial workspace-anchored prompt
- Runs each sample through the prompt and scores the results
- Produces three refined candidates (incremental patch, structural redesign, clean-slate rewrite)
- Synthesizes feedback across all three into a prioritised recommendation list
Review the three candidates — the highest-scoring one is pre-selected
Read the synthesized feedback to understand what the AI recommends improving
Click Apply selected prompt to write it to the Prompt Body field

Temperature Mode

Below the Instruction field, a Temperature dropdown controls how the AI balances creativity vs. groundedness:

Mode	Behaviour
Whimsical	Fully creative; draws freely on imagination and general knowledge
Creative	Free to make inferences and suggest ideas beyond the source material
Balanced (default)	Balances workspace material with general knowledge; notes gaps
Grounded	Prefers workspace material; flags areas of uncertainty
Strict	Only states what can be directly confirmed from workspace resources

The temperature setting applies to all run, score, and refine steps in the wizard — and is embedded in the generated prompt so the AI uses the same posture at execution time.

Advanced: Evaluation Criteria

Evaluation Criteria are binary (pass/fail) assertions used to judge the quality of prompt output — e.g. "Does the response reference the contract register?" or "Is the response under 250 words?".

They are used by both the Build Prompt Wizard (to score candidates during refinement) and the Autoresearch Loop (to score prompts across many iterations).

Adding Criteria

In the skill editor, scroll to the Evaluation Criteria section:

Click Add to type a criterion manually
Click Auto-generate to let an AI agent propose 5–8 criteria based on your Instruction and workspace context

Good criteria:

Are answerable YES or NO by reading the AI's response
Assert what the response contains or does (not what the prompt says)
Reference specific workspace materials the AI should consult

Sample Inputs

Sample inputs are example inputs you'd give to the skill in real use. The Build Prompt Wizard and Autoresearch Loop use them to run the prompt against real-world scenarios and score the output.

To add a sample:

Upload a file (PDF, Word, TXT, or Markdown) — the text is extracted automatically
Or type the sample text directly
Optionally add sample-specific criteria that only apply to that input

The more samples you provide (3+ is recommended), the more accurately the wizard can evaluate prompt quality.

Advanced: Autoresearch Loop

The Autoresearch Loop runs the prompt improvement process repeatedly in the background — useful when you want to explore many candidates without waiting. It uses the same scoring logic as the Build Prompt Wizard but runs autonomously for N iterations.

Starting a Loop

Open a skill and navigate to the Autoresearch panel (button in the Evaluation section)
Optionally upload a sample input file to run real output evaluations
Set the number of iterations (default: 3)
Click Start Loop

The loop runs as a background job — you can close the browser and return later. Each iteration generates a new candidate prompt and scores it; the best result is tracked throughout.

Reading the Results

Results appear as a stepped line chart:

Y axis: cumulative pass count against your criteria
X axis: iteration number
Hover a dot: see the candidate prompt, per-criterion pass/fail breakdown, and an Accept button

Click Accept on any candidate to apply it to the skill's Prompt Body. The "Best Prompt" section below the chart shows the overall winner.

Managing Skills

Editing

Select any skill from the list to edit its name, description, or prompt body. Changes take effect immediately for all users who can see the skill.

Editing the shortcut will update references in other skills you have access to, but may break references in skills you cannot see.

Archiving and Deleting

Archive: Soft-deletes the skill. It will no longer appear in the skill list.
Delete: Permanently removes the skill and cannot be undone.

Access Control

Skills support granular access control:

Space: Visible to all workspace members
Organization: Visible to members of your organization
Team: Visible to members of your team
Private: Visible only to you

After creating a skill, you can fine-tune access using the sharing controls.

Frequently Asked Questions

Can I use skills without the AI chat? Skills are currently available through the AI chat interface. External tools can also access skills via the MCP integration (Enterprise plan).

What happens if I reference a skill that does not exist? The /slug text remains in your message but is treated as plain text. The AI will not receive any special context for unresolved skills.

Is there a limit to how many skills I can create? There is no hard limit on the number of skills. Skills are available on plans that include AI capabilities.

Do I need to set up Evaluation Criteria before using Build Prompt? No — the wizard will generate fallback criteria if none are defined. However, the output is significantly better when you provide at least 3 criteria and 3 sample inputs.

What is the difference between Build Prompt and Autoresearch? Build Prompt runs a single end-to-end wizard that produces 3 polished candidates with structured feedback — best for one-shot prompt engineering. Autoresearch runs many lightweight iterations in the background — best when you want to explore a wider space of candidates over time.

Can I see what context the AI receives? The resolved system prompt is logged in the system logs for debugging. Contact your workspace administrator for access.