Goal Clarifier
v0.6.0Warm multi-turn goal clarification and action planning. Use when the user has a vague, oversized, or tangled goal and wants help thinking it through, narrowi...
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MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
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OpenClaw
Benign
high confidencePurpose & Capability
Name, description, and included reference documents all align with a conversational goal-clarification and planning skill. There are no unrelated required binaries, env vars, or config paths.
Instruction Scope
Runtime instructions stay within the stated purpose: they direct multi-turn clarification, limited questioning, periodic reflection, plan generation, and weekly-plan JSON output. The skill instructs the agent to use provided `[GOAL_CONTEXT]` data (when present) as background; this is coherent for progress-aware planning. All referenced files are bundled with the skill.
Install Mechanism
No install spec or external downloads; this is an instruction-only skill so nothing is written to disk or fetched at install time.
Credentials
The skill requires no environment variables or credentials. It uses system-provided context blocks (e.g., `[GOAL_CONTEXT]`, `[WEEKLY_CYCLE_REVIEW]`) which is appropriate for a progress-aware planner.
Persistence & Privilege
Flags are default (not always:true). The skill does not request permanent presence or attempt to modify other skills or system settings. Autonomous invocation is enabled by default (normal) but not excessive here.
Assessment
This is an instruction-only 'goal clarifier' skill that uses the bundled reference files and (when provided by the platform) system context blocks like `[GOAL_CONTEXT]` to reference task progress. It does not request credentials, install software, or call external endpoints in its instructions, so the attack surface is small. Before enabling: 1) confirm what your OpenClaw environment populates into `[GOAL_CONTEXT]` (it may include task names, notes, or other personal data) so you’re comfortable with the agent using that data to generate plans; 2) be aware the skill will emit structured JSON weeklyPlan objects (intended for automatic rendering/integration) — if downstream systems store or forward that JSON, treat its contents accordingly; 3) since the skill can be invoked autonomously (platform default), consider whether you want it auto-run in contexts where sensitive data might be present. Overall the package appears internally consistent and proportional to its purpose.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.
Runtime requirements
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