molclaw-run-bioemu

molclaw-run-bioemu is a skill for Claude Code, Codex from InternScience/MolClaw. It costs 24 tokens per session (1,692 once invoked), scanned A, original, MIT.

A tool for sampling possible protein shapes from an amino-acid sequence with BioEmu. It can save run metadata and optionally export each sampled shape as a PDB structure file.

In plain words
What is it for?
Use it to generate a chosen number of protein-shape samples, validate inputs with a dry run, save results, and export individual PDB files.
Why use it?
Proteins can adopt multiple shapes, so a single structure may not show the range needed for analysis. This tool creates an ensemble of sampled structures for downstream work.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to generate a chosen number of protein-shape samples, validate inputs with a dry run, save results, and export individual PDB files.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/internscience/molclaw/molclaw-run-bioemu
Install

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.

Any agent
npx skills add InternScience/MolClaw --skill molclaw-run-bioemu
Clone the repo
git clone --depth 1 https://github.com/InternScience/MolClaw

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for molclaw-run-bioemu

README.md
[![agentmods](https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-run-bioemu/github.svg)](https://agentmods.dev/skills/internscience/molclaw/molclaw-run-bioemu)
Your own site
<a href="https://agentmods.dev/skills/internscience/molclaw/molclaw-run-bioemu"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-run-bioemu/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.

agentmods 80×15 button for molclaw-run-bioemu

Your own site · 80×15
<a href="https://agentmods.dev/skills/internscience/molclaw/molclaw-run-bioemu"><img src="https://agentmods.dev/badge/skills/internscience/molclaw/molclaw-run-bioemu.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,692 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.01692
Opus 5 $0.00012 $0.00846
Sonnet 5 $0.00005 $0.00338
Haiku 4.5 $0.00002 $0.00169

Measured 9d ago against content hash 06925f9d3721, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

molclaw-run-bioemu 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.

skills/L1_tools/molclaw-run-bioemu/SKILL.md · 203 lines

How it starts

The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.

BioEmu Sampling and Structure Extraction

Note:

  • Local files are not directly accessible by the server. Please upload them to the server using molclaw-file-transfer before execution.
  • For PDB file inputs, it is recommended to preprocess them using molclaw-pdbfixer before execution.
  • Please refer to skill molclaw-scp-server to complete tool invocation.

Usage

1. BioEmu Sampling

The description of tool run_bioemu.

Generate BioEmu conformational samples for a sequence, store outputs under the shared result root, and return run metadata and key artifacts.
Args:
    sequence (str): Input sequence string or a path (FASTA/A3M) readable by BioEmu.
    num_samples (int): Number of conformational samples to generate.
    export_pdbs (bool): If True, export individual PDB files for each sample (default False).
    dry_run (bool): If True, validate inputs and create run directory without executing BioEmu.
Return:
    status (str): 'success' or 'error'.
    msg (str): Human-readable summary or error message.
    command (str): The invoked command ('run_bioemu').
    run_dir (str|None): Path to the run-specific output directory under tool_result/bioemu_result.
    output_dir (str|None): Same as `run_dir` for compatibility.
    files (List[str]|None): Sorted list of generated files under the run directory.
    pdb_path (str|None): First detected PDB file path if present.
    xtc_path (str|None): First detected XTC file path if present.
    sampling_statistics (dict|None): Parsed sampling statistics if available.
    sampling_statistics_path (str|None): Path to sampling_statistics.json if present.
    sequence_input (str|None): Resolved sequence or input path echoed by BioEmu.
    num_samples_requested (int|None): Number of requested samples echoed back.
    export_pdbs (bool|None): Whether PDB export was requested.

How to use tool run_bioemu :

response = await client.session.call_tool(
    "run_bioemu",
    arguments={
        "sequence": "GYDPETGTWG",
        "num_samples": 5,
        "export_pdbs": False,
        "dry_run": True
    }
)
result = client.parse_result(response)
key_output = result["run_dir"]

Read the full file on GitHub · 203 lines

Changes

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.

  1. 9d ago First seen · 203 lines · 24 tokens per session scan A 06925f9d3721

Subscribe to this mod's changes

molclaw-run-bioemu is a skill published in the GitHub repository InternScience/MolClaw (33 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 1,692 once invoked, about $0.0001 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 2026-08-30.

Related

Other skills, from other repositories

instrument-data-to-allotrope

Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…

anthropics/knowledge-work-plugins · 123 tokens

exploratory-data-analysis

Perform bounded, local exploratory analysis of explicitly supported scientific files. Use for redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…

K-Dense-AI/scientific-agent-skills · 83 tokens

matlab

Build, review, migrate, and safely plan MATLAB or GNU Octave numerical workflows, including arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.

K-Dense-AI/scientific-agent-skills · 42 tokens

phylogenetics

Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree. For evolutionary analysis, microbial genomics, viral phylodynamics, protein family analysis, and molecular clock studies.

K-Dense-AI/scientific-agent-skills · 68 tokens

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

mapping-to-snomed

Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…

maziyarpanahi/openmed · 205 tokens