Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add beita6969/ScienceClaw --skill profile-reportgit clone --depth 1 https://github.com/beita6969/ScienceClawWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/beita6969/scienceclaw/profile-report)<a href="https://agentmods.dev/skills/beita6969/scienceclaw/profile-report"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/profile-report/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/beita6969/scienceclaw/profile-report"><img src="https://agentmods.dev/badge/skills/beita6969/scienceclaw/profile-report.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.01098 |
| Opus 5 | $0.00015 | $0.00549 |
| Sonnet 5 | $0.00006 | $0.00220 |
| Haiku 4.5 | $0.00003 | $0.00110 |
Grade A, and why
profile-report scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
📋 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
- Profile Loading: Read and validate PatientProfile JSON files, identifying which skills have been run
- Report Synthesis: Combine results from pharmgx, nutrigx, prs, and genome-compare into a unified report
- Cross-Domain Insights: Identify connections between skill results (e.g., CYP1A2 in both PGx and caffeine metabolism)
- 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
- Load Profile: Read and validate the PatientProfile JSON
- Identify Skills: Determine which skill results are available (pharmgx, nutrigx, prs, compare)
- Generate Sections: Render each skill section using its
result.jsondata; show placeholder for missing skills - Cross-Domain Insights: Scan for genes/variants that appear across multiple skill results
- Executive Summary: Generate a top-level summary with key findings and action items
- Assemble Report: Combine all sections with header, summary, skill details, insights, and disclaimer
CLI Reference
# 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>
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 121 lines · 31 tokens per session scan A 0c7e42c287c8
profile-report is a skill published in the GitHub repository beita6969/ScienceClaw (898 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 1,098 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
biopython
Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use…
scanpy
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and visualization. Best for exploratory scRNA-seq analysis with established workflows. For deep learning models use scvi-tools; for data format questions use…
structure-prediction
Protein structure prediction from sequence. ESMFold-based, single GPU, no MSA needed. Predicts 3D structures with pLDDT confidence scores for drug discovery targets.
biomcp
Search and retrieve biomedical data - genes, variants, clinical trials, diagnostic tests, articles, drugs, diseases, pathways, proteins, adverse events, pharmacogenomics, and phenotype-disease matching. Use for gene function, variant pathogenicity, trials, diagnostics, drug safety, pathway context, disease workups…
biomcp-research
Do biomedical literature and variant research with the BioMCP CLI, and file what you learn about the tool itself as issues in the biomcp repo.
biological-expert
Expert-level biology, biotechnology, genetics, bioinformatics, and computational biology. Use when the user mentions biology, biotechnology, genetics, bioinformatics, or genomics, or when the task involves Molecular Biology, Genomics & Bioinformatics, Systems Biology, or Data Analysis.