Agent skill

Profile Report

by ClawBio in ClawBio/ClawBio

Unified personal genomic profile report — reads a PatientProfile JSON and synthesizes all skill results into a single "Your Genomic Profile" document.

MITAuto-check passedResearch & Science

Install Profile Report

skills CLI
$ npx skills add ClawBio/ClawBio --skill profile-report -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ClawBio/ClawBio profile-report --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ClawBio/ClawBio.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/profile-report .claude/skills/profile-report && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
profile-report
GitHub stars
1.2k
Used in
2 other repos
Token cost
~2.1k tokens
SKILL.md length
698 words
Files
8
Skills in repo
104
Repo updated
First seen
Licence
MIT

At a glance

Unified personal genomic profile report — reads a PatientProfile JSON and synthesizes all skill results into a single "Your Genomic Profile" document.

  • Works in 4 steps: Profile Loading: Read and validate… → Report Synthesis: Combine results from… → Cross-Domain Insights: Identify… → …
  • Tasks that involve Bioinformatics
  • SKILL.md covers Why This Exists, Core Capabilities, Input Formats and Workflow, plus 7 more sections
  • Runs Python scripts from its folder; calls python and uv

What it does

Profile Report is an agent skill from ClawBio/ClawBio. Unified personal genomic profile report — reads a PatientProfile JSON and synthesizes all skill results into a single "Your Genomic Profile" document.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 9 other files (for example `INTENTS.json`, `demo_full_profile.json` and `profile_report.py`).

It sits in Research & Science, covering Bioinformatics. The repository describes itself as: 🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free. The licence is MIT.

When your agent uses it

  • Tasks that involve Bioinformatics

Example prompts

  • “Your Genomic Profile”
  • “/profile-report”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit 5e045e3. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Profile Report loads about 2.1k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 698 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ClawBio/ClawBio at commit 5e045e3, republished under its MIT licence (© ClawBio). 698 words, ~2,104 tokens.

Download SKILL.mdSave it as .claude/skills/profile-report/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
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
metadata.author
Manuel Corpas
metadata.tags
profile, report-synthesis, personal-genomics

📋 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

FormatExtensionRequired FieldsExample
PatientProfile JSON.jsonmetadata, genotypes, skill_resultsprofiles/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 <file> 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 <profile.json> --output <report_dir>

# 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 <dir>

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 <file> 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.

Show full SKILL.md (226 more words)Show less

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.

© ClawBio, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 7 other files in skills/profile-report of ClawBio/ClawBio.

  • SKILL.md
  • INTENTS.json
  • demo_full_profile.json
  • profile_report.py
  • tests/__init__.py
  • tests/fixtures/mock_profile.json
  • tests/test_profile_report.py
  • tests/test_profile_reproducibility.py

Open the folder on GitHubat commit 5e045e3

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in ClawBio/ClawBio, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Profile Report next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Profile Report compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Profile Report this skillClawBio/ClawBio1.2k2 repos~2.1kAutomated safety check: PassMIT
Dbsnp Databasegoogle-deepmind/science-skills3.2k3 repos~3.4kAutomated safety check: NotesApache-2.0
Metabolic Study Planneraiming-lab/AutoResearchClaw15k—~1.9kAutomated safety check: PassMIT
13C Metabolic Flux AnalysisK-Dense-AI/scientific-agent-skills48k1 repos~3.2kAutomated safety check: PassMIT
Alphagenome Single Variant Analysisgoogle-deepmind/science-skills3.2k2 repos~3kAutomated safety check: NotesApache-2.0
MFA Pipeline Orchestratoraiming-lab/AutoResearchClaw15k—~923Automated safety check: PassMIT

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Questions about Profile Report

What does Profile Report do?

Unified personal genomic profile report — reads a PatientProfile JSON and synthesizes all skill results into a single "Your Genomic Profile" document. Profile Report is an agent skill from ClawBio/ClawBio. Unified personal genomic profile report — reads a PatientProfile JSON and synthesizes all skill results into a single "Your Genomic Profile" document.

When should I use Profile Report?

Profile Report fits situations like: tasks that involve Bioinformatics.

How do I install Profile Report in Claude Code?

Run `npx skills add ClawBio/ClawBio --skill profile-report -a claude-code`. Or copy the skill folder (skills/profile-report in ClawBio/ClawBio) into .claude/skills/profile-report in your project. Claude Code loads it when a task matches its description.

How do I install Profile Report in Codex?

Run `npx skills add ClawBio/ClawBio --skill profile-report -a codex`. Or copy the skill folder (skills/profile-report in ClawBio/ClawBio) into .agents/skills/profile-report in your project. Codex loads it when a task matches its description.

Can I use Profile Report in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ClawBio/ClawBio --skill profile-report -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/profile-report, .gemini/skills/profile-report, .github/skills/profile-report and .opencode/skills/profile-report in your project.

What does Profile Report need to run?

Going by SKILL.md and its folder, Profile Report needs Python for the scripts in its folder and the command-line tools its instructions call (python and uv). Our summary lists: Python 3.

Does Profile Report access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Profile Report safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Profile Report use?

Profile Report is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Profile Report use?

About 2.1k tokens (SKILL.md is roughly 8.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Profile Report?

Skills that share tags, products or a category with Profile Report: Dbsnp Database (google-deepmind/science-skills, 3.2k stars), Metabolic Study Planner (aiming-lab/AutoResearchClaw, 15k stars), 13C Metabolic Flux Analysis (K-Dense-AI/scientific-agent-skills, 48k stars) and Alphagenome Single Variant Analysis (google-deepmind/science-skills, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Profile Report?

ClawBio (a GitHub organization) maintains it in ClawBio/ClawBio, which has 1,154 GitHub stars. The repository holds 104 skills in this directory. The repository was last updated on October 7, 2026.

Source: ClawBio/ClawBio on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.