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Trust Report v1

adme-property-predictor

Predict ADME (Absorption, Distribution, Metabolism, Excretion) properties for drug candidates using cheminformatics models and molecular descriptors. Evaluates drug-likeness, bioavailability, and pharmacokinetic profile to guide lead optimization and candidate selection in drug d

Overall
81
Trust
69
Utility
88
Momentum
95

Install caution

Needs manual review

Risk: Medium

Source: OpenClaw Master Skills

Path: skills/adme-property-predictor/SKILL.md

Review flags: filesystem/home-directory access, shell command snippets. These are review signals, not definitive security judgments; inspect before installing.

Required permissions

  • Environment variables / secrets
  • Shell commands
  • Filesystem/home access

Permissions are inferred from SKILL.md text only. They are review prompts, not guarantees about runtime behavior.

Risk flags explained

filesystem_write_or_home_accessmedium

Mentions filesystem writes, deletes, home-directory paths, or config/key locations.

shell_commandmedium

Contains shell command snippets. Review commands before copy/paste or agent execution.

Score explanation

Trust

  • Trust starts at 90 before review-signal penalties and metadata bonuses.
  • Risk-signal penalty: -23 from 2 detected flag(s).
  • Metadata bonus: +2 from author/version/description fields.

Utility

  • Utility starts at 55 and rewards clear descriptions, runnable examples, and explicit setup needs.
  • Description present: yes.
  • Command examples detected: 3.
  • Environment variables detected: 1.

Momentum

  • Momentum starts at 45 and uses public repo activity signals.
  • Recent commit activity: latest repo update was 6 day(s) ago.
  • Recent commit volume: 6 commit(s) in the lookback window (+18).
  • Source has strong public adoption: 2049 stars.
  • Fork activity suggests reuse: 309 forks.

Overall

  • Overall score weights trust 45%, utility 35%, and momentum 20%.

Detected signals

Env vars

  • API

Commands

  • python scripts/main.py --input library.smi --properties absorption,distribution --format csv --output library_adme.csv
  • python scripts/main.py --input library_adme.csv --filter "lipinski_pass=True,hia>80" --rank-by qed --top-n 100 --output top_candidates.csv
  • python scripts/main.py --smiles "CC(=O)Oc1ccccc1C(=O)O" --properties all --output aspirin_adme.json

URLs

None detected in SKILL.md text scan.

Provenance & evidence

SkillRadar makes each review traceable back to the exact source path, source blob SHA, scanner version, and text-only policy that produced the report.

source
github.com/LeoYeAI/openclaw-master-skills@main
path
skills/adme-property-predictor/SKILL.md
source blob SHA
8b81af7084b070bf755a1308cadd112040b57476
scanner version
0.3.0
security model
text_only_no_execute_no_install_no_secrets
scan policy
Fetched and scored as text only; no install, no execution, no runtime loading.

Evidence snippets

filesystem_write_or_home_access

{"allowed-tools": ["Read", "Write", "Bash", "Edit"], "description": "Predict ADME (Absorption, Distribution, Metabolism, Ex…

shell_command

…bsorption (A) Prediction Predict intestinal absorption, solubility, and permeability: ```python from scripts.adme_predictor import ADMEPredictor predictor = ADMEPredictor() # Predict absorption properties absorption = predictor.predict_absorption( smiles="CC(

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Methodology note

SkillRadar scans SKILL.md as hostile text only. It does not execute commands, install packages, or load third-party skills.