Build and deploy an Atris app from a natural language description. Use when users ask to create chat apps, workflow apps, or API-driven autonomous apps.
Install
npx skillscat add atrislabs/atris/create-app Install via the SkillsCat registry.
Create App
Build and deploy an Atris app from a natural language description.
When to Use
User says something like:
- "I want daily analytics from my Mixpanel"
- "Make me a chat app for job screening"
- "Set up a workflow that monitors my app reviews"
- "Build an app that qualifies leads from a CSV"
What an App Is
An app is a container: data in, agent processes, data out. Three independent parts:
- App = the box (storage, API, schedule, auth)
- Skill = the brain (what to do with the data)
- Member = the operator (the agent that runs it)
Not every app needs all three. A chat widget just needs config. An autonomous workflow needs all three.
Bootstrap
Get the user's Atris API token:
TOKEN=$(node -e "console.log(require('$HOME/.atris/credentials.json').token)" 2>/dev/null)
if [ -z "$TOKEN" ]; then
TOKEN=$(python3 -c "import json,os; print(json.load(open(os.path.expanduser('~/.atris/credentials.json')))['token'])" 2>/dev/null)
fi
if [ -z "$TOKEN" ]; then
echo "Not logged in. Run: atris login"
exit 1
fi
echo "Ready."Base URL: https://api.atris.ai
Auth header: Authorization: Bearer $TOKEN
Flow
Adapt the flow based on what the user described. Skip steps that don't apply.
Step 1: Create the App
Ask the user for a name. Generate a slug (lowercase, hyphens, no spaces).
curl -s -X POST "https://api.atris.ai/api/apps" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{
"name": "APP_NAME",
"description": "DESCRIPTION",
"instructions": "SYSTEM_PROMPT",
"share_token": "SLUG",
"app_type": "external",
"access_mode": "private",
"ui_template": "chat",
"config": {}
}'Save the returned id as APP_ID and share_token as SLUG.
Decisions:
access_mode:"private"for personal workflows,"public"for shared appsui_template:"chat"for conversational, omit for headless workflowsinstructions: the system prompt if it's a chat app, or a description of purpose for workflows
Step 2: Store API Keys (if needed)
Only if the workflow needs external API access (Mixpanel, GitHub, Stripe, etc).
Ask the user for each key. Store one at a time:
curl -s -X PUT "https://api.atris.ai/api/apps/SLUG/secrets/KEY_NAME" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{"value": "THE_SECRET_VALUE"}'Never log or display the secret value after storing it.
Skip this step if the app doesn't need external API keys (chat apps, simple forms).
Step 3: Create the Agent + Skill (if needed)
For autonomous workflows, the app needs an agent with a skill that knows what to do.
3a. Create or pick an agent:
If the user already has an agent, use it. Otherwise create one:
curl -s -X POST "https://api.atris.ai/api/agent" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{
"name": "AGENT_NAME",
"instructions": "AGENT_INSTRUCTIONS",
"access_mode": "api"
}'Save the returned id as AGENT_ID. If access_mode is "api", also save the api_key (shown once).
3b. Write the skill:
The skill is the logic. Write it as a markdown file that describes what the agent should do. Store it in the agent's file memory:
curl -s -X POST "https://api.atris.ai/api/agent/AGENT_ID/files" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{
"name": "skills/APP_SLUG.md",
"content": "SKILL_CONTENT"
}'The skill content should include:
- What data to pull and how (API endpoints, auth patterns)
- What analysis to run
- What output to produce
- Where to store results
Example skill for Mixpanel analytics:
# Mixpanel Analytics Skill
Pull daily event data from Mixpanel, analyze user segments, report insights.
## Steps
1. Use MIXPANEL_API_KEY to call Mixpanel Export API
2. Pull events from last 24 hours
3. Segment users by: first-generation completion, paid conversion, feature usage
4. Compare against previous day's data (read from app storage)
5. Identify: what grew, what dropped, any anomalies
6. Store results in app data (collection: "daily-analysis")
7. Email summary to owner
## Output Format
- 3-5 bullet points of what changed
- One recommendation
- Raw numbers for verification3c. Add agent as app member:
curl -s -X POST "https://api.atris.ai/api/apps/SLUG/members" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{"agent_id": "AGENT_ID", "role": "operator"}'Skip this step for chat apps that don't need an autonomous agent.
Step 4: Set Schedule (if needed)
For apps that run on a schedule:
curl -s -X POST "https://api.atris.ai/api/scheduled-tasks" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{
"agent_id": "AGENT_ID",
"task_type": "pulse",
"cron_expression": "0 8 * * *",
"enabled": true
}'Common schedules:
"0 8 * * *"— daily at 8am UTC"0 */6 * * *"— every 6 hours"0 9 * * 1"— weekly Monday 9am UTC
Skip this step for on-demand apps (manual trigger only) or chat apps.
Step 5: Test It
Trigger the first run to verify everything works:
curl -s -X POST "https://api.atris.ai/api/apps/SLUG/trigger" \
-H "Authorization: Bearer $TOKEN" \
-H "Content-Type: application/json" \
-d '{"trigger_type": "manual"}'Check status:
curl -s "https://api.atris.ai/api/apps/SLUG/status" \
-H "Authorization: Bearer $TOKEN"Check run result:
curl -s "https://api.atris.ai/api/apps/SLUG/runs?limit=1" \
-H "Authorization: Bearer $TOKEN"If the run succeeded, show the user. If it failed, read the error and fix.
Step 6: Confirm
Tell the user:
- App name and slug
- What it does
- When it runs (schedule or manual)
- Where output goes (email, API, feed)
- How to check status:
GET /api/apps/SLUG/status - How to query data:
GET /api/apps/SLUG/data
App Runtime API Reference
All endpoints use the app's share_token as {slug}.
POST /api/apps/{slug}/trigger — run the app now
POST /api/apps/{slug}/ingest — push data in
POST /api/apps/{slug}/ingest/batch — push multiple items
GET /api/apps/{slug}/data — read stored data
GET /api/apps/{slug}/data/{collection} — read specific collection
GET /api/apps/{slug}/status — health, last run, next run
GET /api/apps/{slug}/runs — execution history
GET /api/apps/{slug}/runs/{run_id} — single run details
PUT /api/apps/{slug}/secrets/{key} — store an API key (owner only)
GET /api/apps/{slug}/secrets — list key names (owner only)
DELETE /api/apps/{slug}/secrets/{key} — remove a key (owner only)
POST /api/apps/{slug}/members — add agent operator
GET /api/apps/{slug}/members — list members
DELETE /api/apps/{slug}/members/{agent_id} — remove memberExamples
"I want daily analytics from Mixpanel"
→ Steps 1-5. Private app, Mixpanel key stored, agent with analytics skill, daily schedule, email output.
"Make a chat app for screening candidates"
→ Steps 1 only. Public app, chat template, instructions define the interview flow. No agent, no schedule, no keys.
"Set up a webhook that collects app feedback"
→ Steps 1, 3. Private app, agent processes inbound data. No schedule (webhook-triggered). User posts to /ingest, agent analyzes on trigger.
"Qualify leads from a CSV"
→ Steps 1-3, 5. Private app, agent with qualification skill. Manual trigger (upload CSV via /ingest/batch, then /trigger). No schedule.