/load

name: by:load
description: Load a protein target and analyze it for design
argument-hint: "<target name or PDB/UniProt ID>"

/load — Load and Analyze a Protein Target

Load a protein target by name, PDB ID, or UniProt accession and run initial research analysis to prepare for a design campaign.

Instructions

Step 0: Show BY banner and read model profile

Display the BY session banner first:

━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
 BY ► LOADING TARGET
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Then read model profile:

MODEL_PROFILE=$(cat .by/config.json 2>/dev/null | grep -o '"model_profile"[[:space:]]*:[[:space:]]*"[^"]*"' | grep -o '"[^"]*"$' | tr -d '"' || echo "balanced")

Model lookup for this command: | Agent | quality | balanced | budget | |-------|---------|----------|--------| | by-research | opus | sonnet | sonnet |

Step 1: Parse input

Determine the input type:

• **PDB ID**: 4-character alphanumeric (e.g., `1ABC`, `7XYZ`)
• **UniProt accession**: alphanumeric with pattern like `P12345` or `Q9UHD2`
• **Free text**: treat as a target name or description for search

Step 2: Create campaign directory

CAMPAIGN_ID="campaign_$(date +%Y%m%d_%H%M%S)"
mkdir -p .by/campaigns/$CAMPAIGN_ID/{designs,screening,logs,research}
echo ".by/campaigns/$CAMPAIGN_ID" > .by/active_campaign

Initialize `state.json` with phase=RESEARCH, round=1, target info.

Step 3: Spawn by-research agent

Delegate to a **by-research** agent via Task() (model per profile table above).

Use MCP research tools (PDB, UniProt, SAbDab) -- NOT web search. The by-research agent has access to all structured databases via MCP servers.

> Analyze target: `{user_argument}` > > Tasks: > 1. Resolve the target to a PDB structure and UniProt entry using MCP tools > 2. Identify chains, domains, and key binding interfaces > 3. Search SAbDab for existing antibodies against this target > 4. Identify known epitopes and druggable sites > 5. Assess target difficulty (structured/disordered, glycosylation, flexibility) > 6. Recommend design strategy: binder vs antibody vs nanobody > 7. Suggest initial parameters (scaffold, CDR lengths, seed count) > > Write analysis to `{campaign_dir}/research/target_analysis.json`. > Write human-readable summary to `{campaign_dir}/research/summary.md`.

Step 4: Review research output

Verify the agent produced:

• Valid target_analysis.json with required fields
• A clear design strategy recommendation
• Reasonable parameter suggestions

Step 5: Report to user

Display results using BY display format:

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 BY ► TARGET: {target_name}
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Include:

• Target name and identifiers (PDB, UniProt)
• Key structural features table
• Design strategy recommendation
• Campaign ID for reference

Then show next steps:

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## ▶ Next Up

**Design campaign** -- launch nanobody/antibody/binder design against {target_name}

"Design nanobodies against {target_name}" -- start campaign with defaults

**Also available:**
- `/by:plan-campaign` -- guided campaign setup with custom preferences
- `/by:status` -- check environment and campaign state

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