Txt Chunker
v1.0.0Splits large text files into smaller chunks by line count for easier processing of logs, datasets, or documents.
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
The name/description match the included Python tool: tool.py reads a text file and writes line-count-based chunks. The capability requested is proportionate to the stated purpose.
Instruction Scope
SKILL.md only describes running a command to split files and does not instruct reading unrelated files or exfiltrating data. Minor mismatch: SKILL.md shows a command named 'txt_chunker' while the bundle contains tool.py and no install wrapper — the README assumes a CLI name that isn't provided by an install spec.
Install Mechanism
There is no install spec (instruction-only). The Python script is present but not packaged or installed automatically; the user would need to run python tool.py or create a wrapper. No downloads or external installers are present.
Credentials
The skill requests no environment variables, no credentials, and touches only files provided as input/output. This is proportional for a local file-splitting utility.
Persistence & Privilege
always is false and the skill does not request persistent privileges or modify other skills/config. Autonomous invocation is allowed by default but the skill itself has no elevated persistence or system-wide changes.
Assessment
This appears to be a straightforward, local file-splitting script. Before using: (1) Note SKILL.md references a 'txt_chunker' CLI but the bundle only includes tool.py — you'll need Python 3 and can run it as 'python tool.py inputfile ...' or create a wrapper. (2) Review tool.py (already included) if you want to verify behavior; it only reads the provided input file and writes chunk files to the current directory. (3) Run it in a directory where writing many files is acceptable to avoid disk clutter. (4) Be aware the SKILL.md shows a price ($2.50) but there is no payment mechanism in the files — confirm payment/installation details from the publisher before paying. (5) Because the source/homepage are unknown, prefer running it on non-sensitive sample files first.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.