Add prek git hooks (#1)

* Add prek git hooks

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Add prek.toml config

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Add lefthook commit-msg and pre-push hooks

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Complete lefthook to prek migration

Move commit-msg and pre-push hooks from lefthook.yml
into prek.toml as local shell hooks. Build prek from
source in flake.nix instead of using nixpkgs. Remove
lefthook from dev shell.

* Add prek CI workflow and document nix commands

Add GitHub Actions workflow using Determinate Nix to
run prek checks on push/PR. Document nix develop
commands in README.md and AGENTS.md.

* Fix beads-rust x86_64-linux hash for upstream tarball change

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Fix trailing whitespace and end-of-file issues

Auto-fixed by prek builtin hooks (trailing-whitespace,
end-of-file-fixer).

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Use self-hosted runner with fallback for prek CI

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Trigger CI

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: javdl

.beads/metadata.json

@@ -1,4 +1,4 @@
 {
   "database": "beads.db",
   "jsonl_export": "issues.jsonl"
-}
+}

.github/workflows/prek.yml

@@ -0,0 +1,39 @@
+name: Prek
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+
+concurrency:
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+permissions:
+  contents: read
+
+jobs:
+  determine-runner:
+    runs-on: ubuntu-latest
+    outputs:
+      runner: ${{ steps.runner.outputs.use-runner }}
+    steps:
+      - name: Determine runner
+        id: runner
+        uses: mikehardy/runner-fallback-action@v1
+        with:
+          github-token: ${{ secrets.GH_RUNNER_TOKEN }}
+          primary-runner: self-hosted-16-cores
+          fallback-runner: ubuntu-latest
+          organization: fuww
+          fallback-on-error: true
+
+  prek:
+    runs-on: ${{ fromJson(needs.determine-runner.outputs.runner) }}
+    needs: [determine-runner]
+    steps:
+      - uses: actions/checkout@v4
+      - uses: DeterminateSystems/nix-installer-action@main
+      - uses: DeterminateSystems/magic-nix-cache-action@main
+      - name: Run prek checks
+        run: nix develop --command prek run --all-files

AGENTS.md

@@ -87,3 +87,9 @@ All content is markdown and JSON — edit directly, no build step required. When
 - NEVER stop before pushing - that leaves work stranded locally
 - NEVER say "ready to push when you are" - YOU must push
 - If push fails, resolve and retry until it succeeds
+
+## Code Quality
+
+```bash
+nix develop --command prek run --all-files  # Run all pre-commit checks
+```

PROMPT_plan.md

@@ -8,7 +8,7 @@
    - For each epic, verify child tasks cover all aspects of the specification
    - Check for missing dependencies using `bd dep cycles` (should be empty)
    - Identify any tasks that should block others but don't
-   
+
 2. Update the beads database to fix any issues found:
    - Create missing tasks with `bd create "title" -t task -p <priority> -d "description"`
    - Add missing dependencies with `bd dep add <child> <parent> --type blocks`
@@ -20,7 +20,7 @@
    - `bd blocked` should show tasks waiting on dependencies
    - `bd stats` should show accurate counts
 
-IMPORTANT: Plan only. Do NOT implement anything. Do NOT assume functionality is missing; 
+IMPORTANT: Plan only. Do NOT implement anything. Do NOT assume functionality is missing;
 use `bd list` and code search to verify first.
 
-ULTIMATE GOAL: Refactor all knowledge-work plugins from generic Anthropic templates to FashionUnited-specific workflows, tools, and domain context. Ensure all necessary tasks exist as beads with proper dependencies so `bd ready` always shows the right next work.
+ULTIMATE GOAL: Refactor all knowledge-work plugins from generic Anthropic templates to FashionUnited-specific workflows, tools, and domain context. Ensure all necessary tasks exist as beads with proper dependencies so `bd ready` always shows the right next work.

README.md

@@ -96,3 +96,10 @@ Plugins are just markdown files. Fork the repo, make your changes, and submit a
 ## License
 
 This fork is licensed under Apache 2.0, same as the [original Anthropic repository](https://github.com/anthropics/knowledge-work-plugins). See [LICENSE](LICENSE) for details.
+
+## Development Environment
+
+```bash
+nix develop                              # Enter dev shell with all tools
+nix develop --command prek run --all-files  # Run pre-commit checks
+```

archived/bio-research/skills/clinical-trial-protocol/SKILL.md

@@ -21,7 +21,7 @@ description: Generate clinical trial protocols for medical devices or drugs. Thi
 
 ## Overview
 
-This skill generates clinical trial protocols for **medical devices or drugs** using a **modular, waypoint-based architecture** 
+This skill generates clinical trial protocols for **medical devices or drugs** using a **modular, waypoint-based architecture**
 
 ## What This Skill Does
 
@@ -504,5 +504,3 @@ When this skill is invoked:
    - **Research Only:** Display research summary location and offer to continue with full protocol
    - **Full Protocol:** Congratulate user, display protocol location and next steps
    - Remind user of disclaimers
-
-

archived/bio-research/skills/clinical-trial-protocol/references/00-initialize-intervention.md

@@ -198,4 +198,4 @@ If `waypoints/intervention_metadata.json` already exists:
 - Ensure the intervention_id is filesystem-safe (no spaces, special chars)
 - Validate that required fields are not empty
 - Write clean, formatted JSON with proper indentation
-- Handle both device and drug interventions appropriately with the right terminology
+- Handle both device and drug interventions appropriately with the right terminology

archived/bio-research/skills/clinical-trial-protocol/references/02-protocol-foundation.md

@@ -250,11 +250,11 @@ STATEMENT OF COMPLIANCE
 **Content to Generate:**
 
 STATEMENT OF COMPLIANCE
-Provide a statement that the trial will be conducted in compliance with the protocol, International Conference on Harmonisation Good Clinical Practice (ICH GCP) and applicable state, local and federal regulatory requirements. Each engaged institution must have a current Federal-Wide Assurance (FWA) issued by the Office for Human Research Protections (OHRP) and must provide this protocol and the associated informed consent documents and recruitment materials for review and approval by an appropriate Institutional Review Board (IRB) or Ethics Committee (EC) registered with OHRP. Any amendments to the protocol or consent materials must also be approved before implementation. Select one of the two statements below: 
+Provide a statement that the trial will be conducted in compliance with the protocol, International Conference on Harmonisation Good Clinical Practice (ICH GCP) and applicable state, local and federal regulatory requirements. Each engaged institution must have a current Federal-Wide Assurance (FWA) issued by the Office for Human Research Protections (OHRP) and must provide this protocol and the associated informed consent documents and recruitment materials for review and approval by an appropriate Institutional Review Board (IRB) or Ethics Committee (EC) registered with OHRP. Any amendments to the protocol or consent materials must also be approved before implementation. Select one of the two statements below:
 
-(1)	[The trial will be carried out in accordance with International Conference on Harmonisation Good Clinical Practice (ICH GCP) and the following: 
+(1)	[The trial will be carried out in accordance with International Conference on Harmonisation Good Clinical Practice (ICH GCP) and the following:
 
-•	United States (US) Code of Federal Regulations (CFR) applicable to clinical studies (45 CFR Part 46, 21 CFR Part 50, 21 CFR Part 56, 21 CFR Part 312, and/or 21 CFR Part 812) 
+•	United States (US) Code of Federal Regulations (CFR) applicable to clinical studies (45 CFR Part 46, 21 CFR Part 50, 21 CFR Part 56, 21 CFR Part 312, and/or 21 CFR Part 812)
 
 National Institutes of Health (NIH)-funded investigators and clinical trial site staff who are responsible for the conduct, management, or oversight of NIH-funded clinical trials have completed Human Subjects Protection and ICH GCP Training.
 
@@ -341,7 +341,7 @@ This section contains three major components. Generate each with appropriate det
 
 #### Section 1.2: Schema (30 lines)
 
-**Generate a text-based flow diagram** showing study progression. 
+**Generate a text-based flow diagram** showing study progression.
 
 **Required Elements:**
 - **Screening Period:** Show duration (e.g., "Within 28 days") and key activities (eligibility assessment)

archived/bio-research/skills/instrument-data-to-allotrope/references/flattening_guide.md

@@ -29,11 +29,11 @@ ASM Hierarchy                    → Flat Column
 device-system-document.
   device-identifier              → instrument_serial_number
   model-number                   → instrument_model
-  
+
 measurement-aggregate-document.
   analyst                        → analyst
   measurement-time               → measurement_datetime
-  
+
 measurement-document[].
   sample-identifier              → sample_id
   viable-cell-density.value      → viable_cell_density
@@ -185,43 +185,43 @@ import pandas as pd
 def flatten_asm(asm_dict, technique="cell-counting"):
     """
     Flatten ASM JSON to pandas DataFrame.
-    
+
     Args:
         asm_dict: Parsed ASM JSON
         technique: ASM technique type
-        
+
     Returns:
         pandas DataFrame with one row per measurement
     """
     rows = []
-    
+
     # Get aggregate document
     agg_key = f"{technique}-aggregate-document"
     agg_doc = asm_dict.get(agg_key, {})
-    
+
     # Extract device info
     device = agg_doc.get("device-system-document", {})
     device_info = {
         "instrument_serial_number": device.get("device-identifier"),
         "instrument_model": device.get("model-number")
     }
-    
+
     # Get technique documents
     doc_key = f"{technique}-document"
     for doc in agg_doc.get(doc_key, []):
         meas_agg = doc.get("measurement-aggregate-document", {})
-        
+
         # Extract common metadata
         common = {
             "analyst": meas_agg.get("analyst"),
             "measurement_datetime": meas_agg.get("measurement-time"),
             **device_info
         }
-        
+
         # Extract each measurement
         for meas in meas_agg.get("measurement-document", []):
             row = {**common}
-            
+
             # Flatten measurement fields
             for key, value in meas.items():
                 if isinstance(value, dict) and "value" in value:
@@ -232,9 +232,9 @@ def flatten_asm(asm_dict, technique="cell-counting"):
                         row[f"{col}_unit"] = value["unit"]
                 else:
                     row[key.replace("-", "_")] = value
-            
+
             rows.append(row)
-    
+
     return pd.DataFrame(rows)
 
 # Usage

archived/bio-research/skills/instrument-data-to-allotrope/scripts/export_parser.py

@@ -63,16 +63,16 @@
 def convert_to_asm(filepath: str) -> Optional[Dict[str, Any]]:
     """
     Convert {instrument_name} file to ASM format.
-    
+
     Args:
         filepath: Path to input file
-        
+
     Returns:
         ASM dictionary or None if conversion fails
     """
     if not ALLOTROPY_AVAILABLE:
         raise ImportError("allotropy library required. Install with: pip install allotropy")
-    
+
     try:
         asm = allotrope_from_file(filepath, Vendor.{vendor})
         return asm
@@ -84,36 +84,36 @@ def convert_to_asm(filepath: str) -> Optional[Dict[str, Any]]:
 def flatten_asm(asm: Dict[str, Any]) -> list:
     """
     Flatten ASM to list of row dictionaries for CSV export.
-    
+
     Args:
         asm: ASM dictionary
-        
+
     Returns:
         List of flattened row dictionaries
     """
     technique = "{technique}"
     rows = []
-    
+
     agg_key = f"{{technique}}-aggregate-document"
     agg_doc = asm.get(agg_key, {{}})
-    
+
     # Extract device info
     device = agg_doc.get("device-system-document", {{}})
     device_info = {{
         "instrument_serial_number": device.get("device-identifier"),
         "instrument_model": device.get("model-number"),
     }}
-    
+
     doc_key = f"{{technique}}-document"
     for doc in agg_doc.get(doc_key, []):
         meas_agg = doc.get("measurement-aggregate-document", {{}})
-        
+
         common = {{
             "analyst": meas_agg.get("analyst"),
             "measurement_time": meas_agg.get("measurement-time"),
             **device_info
         }}
-        
+
         for meas in meas_agg.get("measurement-document", []):
             row = {{**common}}
             for key, value in meas.items():
@@ -125,7 +125,7 @@ def flatten_asm(asm: Dict[str, Any]) -> list:
                 else:
                     row[clean_key] = value
             rows.append(row)
-    
+
     return rows
 
 
@@ -134,36 +134,36 @@ def main():
     parser.add_argument("input", help="Input file path")
     parser.add_argument("--output", "-o", help="Output JSON path")
     parser.add_argument("--flatten", action="store_true", help="Also generate CSV")
-    
+
     args = parser.parse_args()
-    
+
     input_path = Path(args.input)
     if not input_path.exists():
         print(f"Error: File not found: {{args.input}}")
         return 1
-    
+
     # Convert to ASM
     print(f"Converting {{args.input}}...")
     asm = convert_to_asm(str(input_path))
-    
+
     if asm is None:
         print("Conversion failed")
         return 1
-    
+
     # Write ASM JSON
     output_path = args.output or str(input_path.with_suffix('.asm.json'))
     with open(output_path, 'w') as f:
         json.dump(asm, f, indent=2, default=str)
     print(f"ASM written to: {{output_path}}")
-    
+
     # Optionally flatten
     if args.flatten and PANDAS_AVAILABLE:
         rows = flatten_asm(asm)
         df = pd.DataFrame(rows)
         flat_path = str(input_path.with_suffix('.flat.csv'))
         df.to_csv(flat_path, index=False)
         print(f"CSV written to: {{flat_path}}")
-    
+
     return 0