PBE Extractor

v1.0.3

Extract invariant principles from any text — find the ideas that survive rephrasing.

6· 1.7k·6 current·6 all-time
byLee Brown@leegitw
MIT-0
Download zip
LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
VirusTotalVirusTotal
Benign
View report →
OpenClawOpenClaw
Benign
high confidence
Purpose & Capability
Name and description align with the runtime instructions (principle extraction, normalization, confidence tagging). The skill requests no binaries, env vars, or config paths that would be out of scope for the stated task.
Instruction Scope
SKILL.md confines operations to analyzing user-provided text, normalizing candidate principles, and producing structured JSON output. It does not instruct the agent to read unrelated files, access system configuration, or send data to third-party endpoints. It explicitly states it uses the agent's configured model and does not write files to disk.
Install Mechanism
Instruction-only skill with no install spec and no code files; nothing is written to disk and no external packages are fetched.
Credentials
No environment variables, credentials, or config paths are required. The data handling note correctly states that if the agent uses a cloud LLM, content will be processed by that provider as part of normal operation.
Persistence & Privilege
always is false and there is no install-time persistence. The skill does not request elevated privileges or modify other skills or system-wide settings.
Assessment
This skill appears coherent and low-risk: it only processes user-supplied text and emits structured extractions. Before submitting sensitive content, remember that the text will be processed by whatever LLM your agent is configured to use (so redact anything you don't want sent to that provider). Review normalized principles and confidence levels before acting on them (the skill cannot verify truth or external validity). Because the skill is instruction-only and requests no credentials, the main remaining concerns are operational: ensure you trust the agent's LLM provider and validate high-impact recommendations before applying them.

Like a lobster shell, security has layers — review code before you run it.

analysisvk97184ay9awn6b94xmzy61g33s83km9tbest-practicesvk97184ay9awn6b94xmzy61g33s83km9tdocumentationvk97184ay9awn6b94xmzy61g33s83km9textractionvk97184ay9awn6b94xmzy61g33s83km9tknowledge-managementvk97184ay9awn6b94xmzy61g33s83km9tlatestvk97184ay9awn6b94xmzy61g33s83km9tmethodologyvk97184ay9awn6b94xmzy61g33s83km9topenclawvk97184ay9awn6b94xmzy61g33s83km9tprinciplesvk97184ay9awn6b94xmzy61g33s83km9tsummarizationvk97184ay9awn6b94xmzy61g33s83km9t

License

MIT-0
Free to use, modify, and redistribute. No attribution required.

Comments