atrislabs

create-app

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.

atrislabs 61 2 Updated 3mo ago
GitHub

Install

npx skillscat add atrislabs/atris/create-app

Install via the SkillsCat registry.

SKILL.md

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 apps
  • ui_template: "chat" for conversational, omit for headless workflows
  • instructions: 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 verification

3c. 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 member

Examples

"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.