Goal PlanCAUTION
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Overview
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
ef7d4f0535e5OBSERVED · 2026-09-26What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
--- name: goal-plan description: Create and execute Goal-Oriented Action Plans (GOAP) with precondition analysis, cost optimization, and adaptive replanning argument-hint: "<goal-description>" allowed-tools: mcp__plugin_ruflo-core_ruflo__task_create mcp__plugin_ruflo-core_ruflo__task_list mcp__plugin_ruflo-core_ruflo__task_status mcp__plugin_ruflo-core_ruflo__task_assign mcp__plugin_ruflo-core_ruflo__task_update mcp__plugin_ruflo-core_ruflo__task_complete mcp__plugin_ruflo-core_ruflo__task_summary mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__neural_predict mcp__plugin_ruflo-core_ruflo__workflow_create mcp__plugin_ruflo-core_ruflo__workflow_execute mcp__plugin_ruflo-core_ruflo__workflow_status mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-start mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-step mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-end Bash Read Write Edit --- # Goal Plan Create and execute intelligent plans using Goal-Oriented Action Planning (GOAP). ## When to use When you have a complex objective that requires multiple steps, has dependencies between steps, and may need adaptive replanning as conditions change. ## Steps 1. **Define goal state** — what does "done" look like? List concrete success criteria 2. **Assess current state** — what's true now? What assets, code, infrastructure exist? 3. **Identify gap** — what must change between current and goal state? 4. **Inventory actions** — list available actions with: - Preconditions (what must be true before this action) - Effects (what becomes true after this action) - Cost estimate (time, complexity, risk) 5. **Generate plan** — find the optimal action sequence using A* through the state space 6. **Record trajectory** — call `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-start` to begin tracking 7. **Create tasks** — call `mcp__plugin_ruflo-core_ruflo__task_create` for each action in the plan 8. **Execute** — work through tasks in dependency order: - Before each action: verify preconditions still hold - After each action: verify effects achieved - Record each step via `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-step` 9. **Monitor & replan** — if an action fails or produces unexpected results: - Reassess current state - Recalculate optimal path from new state - Update remaining tasks 10. **Complete trajectory** — call `mcp__plugin_ruflo-core_ruflo__hooks_intelligence_trajectory-end` 11. **Store successful plan** — call `mcp__plugin_ruflo-core_ruflo__memory_store` with namespace `goap-plans` ## Plan output format ``` Goal: [concrete objective] Current State: [key facts] Plan Cost: [estimated effort] Steps: 1. [action] — precondition: [X], effect: [Y], cost: [Z] 2. [action] — precondition: [Y], effect: [W], cost: [Z] ... Risk Factors: [what could force a replan] Fallback: [alternative approach if primary path fails] ``` ## Replanning triggers - Action fails (precondition no longer met) - Unexpected side effects detected - New information changes goal definition - Cost exceeds threshold - External dependency becomes unavailable
Trust audit
CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (4)
crates
plugin/agents
plugin/commands
plugin/skills
Gates applied: no_behavioural_pass.
ef7d4f0535e5full audit observations/trust-audit/skill/ruvnet__goal-plan.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-09-26 | ef7d4f0535e5 | CAUTION | B | 89 | first audit |
Questions
What does the Goal Plan skill do?
🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, federation, vector RAG integration, and native Claude Code / Codex / Hermes and many more Integrated
Is Goal Plan safe to install?
With care. The audit graded it B (89/100) and found 4 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can Goal Plan access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (ef7d4f0535e5), read on 2026-09-26. The repository is watched, and a new audit runs when it changes — this is the first audit.