molclaw-equiscore-tool

molclaw-equiscore-tool is a skill for Claude Code, Codex from InternScience/MolClaw. It costs 86 tokens per session (2,272 once invoked), scanned A, original, MIT.

A scientific workflow for extracting molecular binding pockets and scoring molecules with EquiScore. A binding pocket is the part of a protein where another molecule may attach; PDB and SDF are common molecular structure file formats.

In plain words
What is it for?
Use it with docking-result SDF files and receptor PDB files to extract pockets, prepare individual molecule files, and run or validate EquiScore screening.
Why use it?
It organizes the file preparation and scoring steps needed to evaluate molecules against a protein target.

Skill for Claude CodeCodex

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

Good fit Use it with docking-result SDF files and receptor PDB files to extract pockets, prepare individual molecule files, and run or validate EquiScore screening.

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Install with agentmods
npx agentmods add skills/internscience/molclaw/molclaw-equiscore-tool
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-equiscore-tool
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-equiscore-tool

README.md
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Your own site
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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.

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Your own site · 80×15
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Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,272 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 warn 7 Sept 2026
SkillSpector: 1 finding, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Prompt Injection · line 98
    This pattern attempts to override system instructions or ignore safety constraints. Without LLM analysis, manual review is recommended.
    Fix: Remove or rewrite any text that instructs the agent to ignore prompts, override safety rules, or trust unverified content. Ensure skill content cannot be injected to alter agent behavior.
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 $0.00086 $0.02272
Opus 5.5 $0.00034 $0.00909
Sonnet 5.5 $0.00017 $0.00454
Haiku 4.5 $0.00009 $0.00227

Measured 1mo ago against content hash 3ddf3bb30e88, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

molclaw-equiscore-tool 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 1mo 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-equiscore-tool/SKILL.md · 245 lines

How it starts

The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.

EquiScore Multi-Tool Workflow

Invocation

Use the exact tool name and parameter schema exposed by the current harness. Tool names in SDK examples below are raw MCP names, not model-facing aliases. Local files must be uploaded with molclaw-file-transfer before a server tool can use them. Repair PDB inputs first when the workflow requires it.

[!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-fix-pdb before execution.

Usage

1. Pocket Extraction

The description of tool equiscore_pocket.

Extract binding pockets from docking results and prepare split single-molecule SDFs for EquiScore screening.
Args:
    docking_result (str): Path to a docking-result SDF file.
    receptor_pdb (str): Path to the receptor PDB file.
    pocket_cutoff (float|None): Optional numeric cutoff for pocket detection.
    dry_run (bool|None): If True, validate inputs and prepare outputs without executing EquiScore.
Return:
    status (str): 'success' or 'error'.
    msg (str): Human-readable summary or error message.
    command (str): The subcommand executed ('get_pocket').
    run_dir (str|None): Run-specific directory under tool_result/equiscore_result.
    single_sdf_dir (str|None): Path to directory containing split single-molecule SDFs.
    pocket_dir (str|None): Path to the generated pocket folder.
    split_sdf_count (int|None): Number of split SDF files created.
    pocket_item_count (int|None): Number of pocket entries generated.
    sample_single_sdfs (List[str]|None): Sample single-SDF filenames.
    sample_pockets (List[str]|None): Sample pocket directory names.

How to use tool equiscore_pocket :

response = await client.session.call_tool(
    "equiscore_pocket",
    arguments={
        "docking_result": "relative/path/to/docking_result.sdf",
        "receptor_pdb": "relative/path/to/receptor.pdb",
        "pocket_cutoff": 10.0,
        "dry_run": True
    }
)
result = client.parse_result(response)
key_output = result["single_sdf_dir"]

Read the full file on GitHub · 245 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. 1mo ago Changed · -1 lines · +56 tokens per session 3ddf3bb30e88
  2. 1mo ago First seen · 246 lines · 30 tokens per session scan A 357023211a57

Subscribe to this mod's changes

molclaw-equiscore-tool is a skill published in the GitHub repository InternScience/MolClaw (38 stars, last pushed 1mo ago), licensed MIT. It adds 86 tokens to every session and 2,272 once invoked, about $0.0003 per session on Opus 5.5. 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.

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