--- name: profile-report description: Unified personal genomic profile report — reads a PatientProfile JSON and synthesizes all skill results into a single "Your Genomic Profile" document. license: MIT metadata: version: 0.1.0 author: Manuel Corpas tags: - profile - report-synthesis - personal-genomics openclaw: requires: bins: - python3 always: false emoji: 📋 homepage: https://github.com/ClawBio/ClawBio os: - darwin - linux trigger_keywords: - profile report - unified report - my profile - genomic profile - personal profile outputs: - name: profile_report.md type: file format: - md description: Unified markdown profile report - name: result.json type: file format: - json description: Machine-readable result envelope with input_checksum - name: reproducibility/commands.sh type: file format: - sh description: Portable replay command preserving --demo or --profile mode and output path - name: reproducibility/environment.yml type: file format: - yml description: Runtime environment summary with Python minor version - name: reproducibility/checksums.sha256 type: file format: - sha256 description: Output-relative SHA256 manifest for report, result, commands, environment, and inputs - name: reproducibility/inputs.json type: file format: - json description: Input hash manifest for the PatientProfile source without copying raw profile data --- # 📋 Profile Report You are **Profile Report**, a specialised ClawBio agent for generating unified personal genomic profile reports. Your role is to read a populated PatientProfile JSON file and synthesize all skill results into a single human-readable markdown document. ## Why This Exists - **Without it**: A user who has run PharmGx, NutriGx, PRS, and Genome Compare has four separate reports with no cross-referencing - **With it**: One unified document that highlights cross-domain insights (e.g., CYP1A2 appears in both PGx and caffeine metabolism) - **Why ClawBio**: Reads validated skill outputs only — never re-computes or hallucinates results ## Core Capabilities 1. **Profile Loading**: Read and validate PatientProfile JSON files, identifying which skills have been run 2. **Report Synthesis**: Combine results from pharmgx, nutrigx, prs, and genome-compare into a unified report 3. **Cross-Domain Insights**: Identify connections between skill results (e.g., CYP1A2 in both PGx and caffeine metabolism) 4. **Graceful Degradation**: Produce a useful report even when only some skills have been run ## Input Formats | Format | Extension | Required Fields | Example | |--------|-----------|-----------------|---------| | PatientProfile JSON | `.json` | `metadata`, `genotypes`, `skill_results` | `profiles/PT001.json` | ## Workflow 1. **Load Profile**: Read and validate the PatientProfile JSON 2. **Identify Skills**: Determine which skill results are available (pharmgx, nutrigx, prs, compare) 3. **Generate Sections**: Render each skill section using its `result.json` data; show placeholder for missing skills 4. **Cross-Domain Insights**: Scan for genes/variants that appear across multiple skill results 5. **Executive Summary**: Generate a top-level summary with key findings and action items 6. **Assemble Report**: Combine all sections with header, summary, skill details, insights, and disclaimer 7. **Write Reproducibility Bundle**: For successful `--demo` and `--profile ` runs, write `reproducibility/commands.sh`, `environment.yml`, `checksums.sha256`, and `inputs.json` using shared `ReproCommand`, `ReproPath`, `write_portable_commands_sh`, `write_environment_yml`, and `write_checksums` ## CLI Reference ```bash # From a populated PatientProfile JSON python skills/profile-report/profile_report.py \ --profile --output # Demo mode (pre-built 4-skill profile) python skills/profile-report/profile_report.py --demo --output /tmp/profile_demo # Via ClawBio runner python clawbio.py run profile --demo python clawbio.py run profile --profile profiles/PT001.json --output ``` ## Demo ```bash python clawbio.py run profile --demo ``` Expected output: A unified report combining PharmGx (12 genes, 51 drugs), NutriGx (40 SNPs, 13 dietary domains), PRS (polygenic risk for selected traits), and Genome Compare (IBS vs George Church + ancestry). Includes an executive summary and cross-domain insights section. ## Output Structure ``` output_directory/ ├── profile_report.md # Unified markdown report │ ├── Executive Summary │ ├── Pharmacogenomics (from pharmgx) │ ├── Nutrigenomics (from nutrigx) │ ├── Polygenic Risk Scores (from prs) │ ├── Genome Comparison (from compare) │ ├── Cross-Domain Insights │ └── Disclaimer ├── result.json # Machine-readable result envelope; input_checksum matches inputs.json └── reproducibility/ ├── commands.sh # Replay command preserving --demo or --profile mode ├── environment.yml # Python minor version; no skill-specific pip dependencies ├── checksums.sha256 # Output-relative SHA256 manifest, excluding itself └── inputs.json # PatientProfile source hash manifest; no raw profile copy ``` `commands.sh` preserves the effective mode: `--demo` for demo runs or `--profile` with the original external PatientProfile path. Paths are shell-quoted for replay, including output directories and profile paths with spaces or shell metacharacters. The report never modifies the source PatientProfile file and never re-runs old skill analyses. `inputs.json` records `input_sha256`, `input_kind`, and `checksum_kind`. Prebuilt `demo_full_profile.json` and explicit `--profile ` inputs use the original file SHA256 with `checksum_kind: file-bytes` and `input_kind: demo-file` or `profile-file`. If the prebuilt demo is absent and the existing generated demo fallback is used, `input_sha256` is the SHA256 of the canonical generated PatientProfile JSON, with `input_kind: generated-demo` and `checksum_kind: canonical-json`. `result.json` keeps the same hash in its existing `input_checksum` field. Generated demo fallbacks include fresh timestamps, so replay can produce a new fingerprint; this records the effective input rather than promising byte-identical regeneration. `checksums.sha256` uses paths relative to the output directory and covers `profile_report.md`, `result.json`, `reproducibility/commands.sh`, `reproducibility/environment.yml`, and `reproducibility/inputs.json`. It does not hash itself. ## Dependencies **Required**: - Python 3.11+ with the repo core environment No skill-specific pip dependencies are added. `environment.yml` records the Python minor version used for the run, but replay in another checkout still requires the repo core environment installed from the current `uv sync` / lockfile. For portable replay, set `CLAWBIO_ROOT` to the checkout root and `PYTHON` to the intended Python interpreter; external `--profile` inputs must remain accessible at the recorded path. The reproducibility bundle is not a self-contained patient data package. ## Safety - **Local-first**: No data upload — reads local profile JSON only - **No re-computation**: Reads existing skill outputs; never re-runs analyses - **Disclaimer**: Included in every report - **Graceful degradation**: Missing skills produce informative placeholders, not errors ## Integration with Bio Orchestrator **Trigger conditions** — the orchestrator routes here when: - User asks for "profile report", "personal profile", or "my profile" - User wants a unified view of all their genomic results **Chaining partners**: - `full-profile pipeline`: Run `python clawbio.py run full-profile` first (pharmgx → nutrigx → prs → compare), then profile-report - `Individual skills`: Run any combination of pharmgx, nutrigx, prs, compare, then profile-report to unify ## PRS evidence scope Preserve `gwas-prs` evidence assessments in unified reports. Research percentiles are not individual disease-risk categories. Withheld or unknown evidence status must suppress even a stale non-null top-level percentile. Explicit synthetic demo results remain illustrative. Legacy records without evidence/scope fields retain their existing rendering; this compatibility change does not retrospectively validate them.