by-session

name	by-session
description	Session initialization and configuration for BY projects. Use this skill when: (1) Opening a new session in a BY project directory, (2) Running first-time setup (config questionnaire), (3) Checking environment and compute availability, (4) Reading or updating .by/config.json or .by/environment.json.
category	session
tags	["session","config","environment","setup","initialization"]

BY Session & Config Skill

This skill defines the full session start sequence and the first-run configuration questionnaire for BY projects. It is NOT optional -- it runs every time a new session opens in a BY project directory.

---

1. First-Run Setup (when .by/config.json does NOT exist)

When .by/config.json is missing, run the full setup questionnaire before anything else. Use AskUserQuestion for all structured choices.

Round 1 -- Compute Provider

AskUserQuestion(
  header: "Compute Provider",
  question: "Where should BY run design computations?",
  options: [
    "Auto-detect (Recommended)" -- Check what's available and pick the best,
    "Local GPU" -- NVIDIA GPU with tools installed (fastest, no cost),
    "Tamarind Bio" -- Cloud compute, free tier available (no GPU needed),
    "SSH Remote" -- Cloud GPU instances (Lambda.ai, RunPod, HPC)
  ]
)

If user selects "Auto-detect"

Run the same checks as "Local GPU" silently. If local tools are found, use them. If not, check for Tamarind API key. Report what was found and which provider was selected.

If user selects "Local GPU" -- follow-up questions

BoltzGen path:

AskUserQuestion(
  header: "BoltzGen Path",
  question: "Where is BoltzGen installed?",
  options: [
    "Auto-detect" -- Search PATH and common locations,
    "Custom path" -- I'll provide the path
  ]
)

If "Custom path" is selected, ask inline for the path. Validate the path exists.

Protenix path:

AskUserQuestion(
  header: "Protenix Path",
  question: "Where is Protenix installed?",
  options: [
    "Auto-detect" -- Search PATH and common locations,
    "Custom path" -- I'll provide the path
  ]
)

Same flow -- if "Custom path", ask inline and validate.

PXDesign path:

AskUserQuestion(
  header: "PXDesign Path",
  question: "Where is PXDesign installed?",
  options: [
    "Auto-detect" -- Search PATH and common locations,
    "Custom path" -- I'll provide the path
  ]
)

Same flow -- if "Custom path", ask inline and validate.

After collecting paths, run environment checks:

1. Which conda envs exist?

   conda env list 2>/dev/null | grep -E 'bg|protenix|pxdesign'
   

2. Are the tools actually runnable? Quick --help check for each:

   conda run -n bg boltzgen --help 2>/dev/null | head -1
   conda run -n protenix protenix --help 2>/dev/null | head -1
   conda run -n pxdesign pxdesign --help 2>/dev/null | head -1
   

3. Are model weights downloaded? Check for expected weight directories:

   • BoltzGen: {path}/weights/ or {path}/models/
   • Protenix: {path}/model_data/ or {path}/release/
   • PXDesign: {path}/weights/

4. GPU detection:

   nvidia-smi --query-gpu=name,memory.total --format=csv,noheader
   

Report findings in this format:

Local GPU Setup:
  BoltzGen  ✓ /data/proteus/proteus-design (conda: bg, weights: ✓)
  Protenix  ✓ /data/proteus/Protenix (conda: protenix, model: 2025 base)
  PXDesign  ✓ /data/proteus/PXDesign (conda: pxdesign, weights: ✓)
  GPU       NVIDIA RTX PRO 6000 (98GB VRAM)

Use ✗ and a reason for any tool that fails validation:

  PXDesign  ✗ not found (conda env 'pxdesign' does not exist)

If user selects "Tamarind Bio"

1. Check if TAMARIND_API_KEY is set in environment or .env file:

   grep -q TAMARIND_API_KEY .env 2>/dev/null && echo "found" || echo "missing"
   

2. If not found, guide the user:

   Tamarind Bio API key not found.
   
   To get a free key:
   1. Go to https://tamarind.bio
   2. Sign up / log in
   3. Copy your API key from the dashboard
   4. Add to .env: TAMARIND_API_KEY=your_key_here
   

3. If found, check quota via mcp__by-cloud__cloud_list_providers and report:

   Tamarind Bio: ✓ connected
     Tier: free | GPU-hours remaining: 87
     Models: BoltzGen, Protenix, PXDesign available
   

If user selects "SSH Remote"

Ask for connection details inline:

• Host: hostname or IP
• User: SSH username
• Key path: path to SSH private key (default: ~/.ssh/id_rsa)
• GPU type: what GPU is on the remote (for VRAM estimation)

Test the SSH connection:

ssh -o ConnectTimeout=5 -o BatchMode=yes user@host echo "ok" 2>/dev/null

Report success or failure. Write connection details to config.

Round 2 -- Model Profile

AskUserQuestion(
  header: "AI Model Profile",
  question: "Which AI models for sub-agents?",
  options: [
    "Balanced (Recommended)" -- Sonnet for most agents, good quality/cost ratio,
    "Quality" -- Opus for research/design agents, deeper analysis,
    "Budget" -- Haiku where possible, fastest and lowest cost
  ]
)

Round 3 -- Campaign Defaults

AskUserQuestion(
  header: "Default Campaign Size",
  question: "Default designs per campaign?",
  options: [
    "Preview (~500)" -- Fast testing, feasibility checks,
    "Standard (~5,000)" -- Good sampling per scaffold (Recommended),
    "Production (~20,000)" -- Thorough coverage, difficult targets
  ]
)

Write config.json

After all rounds, write .by/config.json with the collected settings:

{
  "model_profile": "balanced",
  "compute": {
    "preferred_provider": "local",
    "local": {
      "boltzgen": {
        "path": "/data/proteus/proteus-design",
        "conda_env": "bg",
        "weights": true
      },
      "protenix": {
        "path": "/data/proteus/Protenix",
        "conda_env": "protenix",
        "model": "protenix_base_20250630_v1.0.0"
      },
      "pxdesign": {
        "path": "/data/proteus/PXDesign",
        "conda_env": "pxdesign",
        "weights": true
      }
    },
    "tamarind": {
      "tier": "free",
      "api_key_configured": true
    },
    "ssh": {
      "host": null,
      "user": null,
      "key_path": null,
      "gpu_type": null
    },
    "gpu": {
      "name": "NVIDIA RTX PRO 6000",
      "vram_gb": 98
    }
  },
  "campaign_defaults": {
    "tier": "standard",
    "fold_validation": true
  }
}

Only include sections that apply. For example, if the user selected "Tamarind Bio", omit the local block (or set paths to null). If no SSH was configured, omit the ssh block.

Then show: "Configuration saved to .by/config.json. Ready."

---

2. Session Start (when .by/config.json EXISTS)

When .by/config.json already exists, skip the questionnaire and go straight to the session banner and status.

Step 1: Show banner

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 BY ► Protein Design Agent
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Step 2: Read config and environment

Read .by/config.json for user preferences. Read .by/environment.json if it exists (written by the SessionStart hook). Determine:

• Which compute providers are available and configured
• Current model profile
• Default campaign tier
• API keys present (without exposing values)

Step 3: Check for existing campaigns

ls .by/campaigns/*/campaign_log.json 2>/dev/null

Count campaigns, check for any in active (non-complete) state.

Step 4: Display status

Build the compute status line from config:

• Local GPU: show tool names if local tools are configured Compute: Local GPU ✓ (BoltzGen, Protenix, PXDesign)
• Tamarind Bio: show tier Compute: Tamarind Bio ✓ (free tier)
• SSH Remote: show host Compute: SSH Remote ✓ (gpu-node.example.com)
• Multiple: list all with preferred marked Compute: Local GPU ✓ (preferred) | Tamarind Bio ✓

Full display:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 BY ► Protein Design Agent
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

Compute: Local GPU ✓ (BoltzGen, Protenix, PXDesign)
Profile: balanced | Default: standard (5,000/scaffold)
Campaigns: [N] previous

Ready:
  "Design [modality] against [target]"
  /by:plan-campaign -- guided setup
  /by:status -- existing campaigns

If there are campaigns in active state, highlight them:

Campaigns: 3 previous, 1 active (anti-HER2 -- designing 80%)

If there are zero campaigns:

Campaigns: none yet

Ready:
  "Design nanobodies against [target]" -- start your first campaign
  /by:welcome -- first-time walkthrough
  /by:plan-campaign -- guided setup

---

3. Environment Awareness

On every session start, read .by/environment.json for available tools and compute:

• Which compute providers are configured (Tamarind, SSH hosts, local GPU)
• Remaining quota / tier for cloud providers
• Available local tools (Protenix, PXDesign, BoltzGen) with paths
• API keys present (without exposing values)
• GPU hardware details (model, VRAM)

Read .by/config.json for user preferences:

• Model profile (quality / balanced / budget)
• Default compute provider
• Campaign defaults (tier, fold_validation)

If .by/environment.json is stale (>24h), suggest running /by:setup to refresh.

---

4. Config Update

When the user wants to change settings after initial setup:

• /by:set-profile changes model_profile in config.json
• /by:setup re-runs environment discovery and updates environment.json
• Direct requests like "switch to Tamarind" update compute.preferred_provider

Always read the existing config, modify only the changed fields, and write back. Never overwrite unrelated settings.