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RALSTP Consultant
by
thedragosexperience
· GitHub ↗
· v1.0.1
720
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Install in OpenClaw
/install ralstp-consultant
Description
Analyze problems using RALSTP (Recursive Agents and Landmarks Strategic-Tactical Planning). Based on PhD thesis by Dorian Buksz (RALSTP). Identifies agents,...
Usage Guidance
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.
Capability Analysis
Type: OpenClaw Skill
Name: ralstp-consultant
Version: 1.0.1
The skill bundle provides a RALSTP consultant, designed to analyze problems using a specific planning methodology. The `SKILL.md` clearly outlines its purpose and usage, including an optional 'Formal Mode' that utilizes `scripts/analyze.py` for PDDL file analysis. The `analyze.py` script is a self-contained Python program that parses PDDL files, identifies agents, and calculates difficulty metrics. It does not perform any network requests, execute external commands, access sensitive files beyond its stated purpose, or use `eval`/`exec` on untrusted input. There is no evidence of data exfiltration, persistence mechanisms, or prompt injection attempts designed to subvert the agent's core functionality for malicious ends. The code and documentation align with the stated purpose of a planning analysis tool.
Capability Assessment
Purpose & 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.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install ralstp-consultant - After installation, invoke the skill by name or use
/ralstp-consultant - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Clarified Natural Language vs PDDL capability to fix security flag. Added Implementation Note explaining Conceptual Mode (LLM) vs Formal Mode (PDDL).
v1.0.0
Initial release of ralstp-consultant skill.
- Analyzes complex problems using RALSTP (Recursive Agents and Landmarks Strategic-Tactical Planning) method.
- Identifies dynamic agents, passive objects, and maps agent dependencies.
- Assesses problem difficulty with entanglement and agent count metrics.
- Provides both strategic (abstract) and tactical (detailed) breakdowns.
- Suggests decomposition strategies for parallelism and risk management.
- Output includes structured analysis for workflows with multiple actors or resource contention.
Metadata
Frequently Asked Questions
What is RALSTP Consultant?
Analyze problems using RALSTP (Recursive Agents and Landmarks Strategic-Tactical Planning). Based on PhD thesis by Dorian Buksz (RALSTP). Identifies agents,... It is an AI Agent Skill for Claude Code / OpenClaw, with 720 downloads so far.
How do I install RALSTP Consultant?
Run "/install ralstp-consultant" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is RALSTP Consultant free?
Yes, RALSTP Consultant is completely free (open-source). You can download, install and use it at no cost.
Which platforms does RALSTP Consultant support?
RALSTP Consultant is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created RALSTP Consultant?
It is built and maintained by thedragosexperience (@thedragosexperience); the current version is v1.0.1.
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