SMILES De-salter
v1.0.0Analyze data with `smiles-de-salter` using a reproducible workflow, explicit validation, and structured outputs for review-ready interpretation.
⭐ 0· 45·0 current·0 all-time
byAIpoch@aipoch-ai
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name/description match the provided artifacts: a single Python script (scripts/main.py) plus SKILL.md and references. Declared dependencies (RDKit, pandas) align with chemical SMILES parsing and tabular IO. No unrelated binaries, credentials, or config paths are requested.
Instruction Scope
SKILL.md restricts runtime actions to validating inputs, compiling/running scripts/main.py, and processing input files. The instructions do not ask the agent to read unrelated system files, access secrets, or transmit data externally. Fallback/error handling is explicit and limited to local reporting.
Install Mechanism
This is an instruction-only skill (no install spec) and includes a requirements.txt listing pandas and rdkit. That is proportionate. Note: installing RDKit can be non-trivial on some systems (often requiring conda or platform-specific wheels); the SKILL.md suggests `pip install rdkit pandas`, which may fail in many environments. This is an operational/compatibility note, not a security concern.
Credentials
No environment variables, credentials, or config paths are required. The script operates on user-provided input/output files only, which is proportionate to the stated functionality.
Persistence & Privilege
Flags show normal defaults (always: false, model invocation allowed). The skill does not request permanent presence or attempt to modify other skills or global configs.
Assessment
This skill appears to do what it claims: locally parse SMILES and remove salt fragments. Before installing/using it: 1) Run the recommended smoke checks (python -m py_compile scripts/main.py and python scripts/main.py --help) in a sandboxed environment. 2) Ensure RDKit is installed correctly for your platform (many users install RDKit via conda rather than pip). 3) Test with a small sample file to confirm behavior and edge cases (the heuristic may misclassify unusual ions). 4) Review inputs for any sensitive data before processing and ensure outputs are stored where you intend. 5) If you need network-isolated execution or stricter auditing, run the script in a contained environment (container or VM).Like a lobster shell, security has layers — review code before you run it.
latestvk97231t855zpbdktb4mgkzrje983zcj6
License
MIT-0
Free to use, modify, and redistribute. No attribution required.