RALSTP Consultant
v1.0.1Analyze problems using RALSTP (Recursive Agents and Landmarks Strategic-Tactical Planning). Based on PhD thesis by Dorian Buksz (RALSTP). Identifies agents,...
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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 (RALSTP analysis, conceptual + optional formal mode) matches the provided SKILL.md and the included scripts. The provided scripts implement a lightweight PDDL parser and RALSTP heuristics — which is exactly what a formal-mode helper would need. There are no unrelated dependencies, binaries, or credentials requested.
Instruction Scope
The SKILL.md stays within the declared purpose: it describes conceptual use with LLMs and an optional formal mode that requires user-provided domain/problem PDDL files. The runtime instructions do not request system-wide data or secrets. Note: the included analyze.py reads local files you pass to it and uses heuristic/regex parsing (not a full secure parser). This is an accuracy/robustness concern rather than a security incoherence — validate untrusted PDDL inputs if you care about correctness.
Install Mechanism
There is no install specification (instruction-only except for an included script). Nothing is downloaded or written by an installer. This is the lowest-risk class for installation.
Credentials
The skill declares no required environment variables, no credentials, and no config paths. The script only opens the domain/problem paths supplied by the user; that is proportional to the claimed formal-mode functionality.
Persistence & Privilege
The skill is not forced-always, is user-invocable, and does not request any persistent/system privileges or attempt to modify other skills or system configuration. Autonomous invocation is permitted by platform default but is not combined with other red flags here.
Assessment
This skill appears to do what it says: conceptual analysis via LLM and an optional formal mode that parses PDDL files with the included script. Before using: (1) Only run the analyze.py on PDDL files you trust or run it in a sandbox — it will read any local files you point it at but does not perform network access or execute code from those files. (2) Expect the script to be heuristic and approximate (regex-based parsing); results may be incorrect on complex PDDL. (3) No credentials or external endpoints are requested, so installing it does not expose secrets. If you want extra safety, inspect the script (it's short) or run it in an isolated environment.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.