instruction-layer-auditor
by PromptSpace
Audit and de-conflict complex agent instruction stacks to fix inconsistent behavior and logic bloat.
- Identify conflicting rules across system prompts and repository-level docs.
- Reduce prompt token bloat by identifying redundant instructions across layers.
- Fix "over-cautious" behavior caused by overlapping safety or logic constraints.
Free
One-time purchase
Included in download
- Downloadable skill package
- Works with OpenClaw, Cursor
- Instant install
See it in action
LAYER MAP: System (Global), AGENTS.md (Repo), Memory (Context). CONFLICTS: System says 'Be concise'; AGENTS.md says 'Explain every step'. RISK: Agent will likely pause for confirmation unnecessarily. PROPOSAL: Delete 'verbose' rule in AGENTS.md; move 'step-by-step' logic to the 'Code-Review' skill.
instruction-layer-auditor
by PromptSpace
Audit and de-conflict complex agent instruction stacks to fix inconsistent behavior and logic bloat.
Free
One-time purchase
⚡ Skill ready to install in Claude Code, Gemini CLI, or any MCP-compatible client. Read the install guides →
Included in download
- Downloadable skill package
- Works with OpenClaw, Cursor
- Instant install
See it in action
LAYER MAP: System (Global), AGENTS.md (Repo), Memory (Context). CONFLICTS: System says 'Be concise'; AGENTS.md says 'Explain every step'. RISK: Agent will likely pause for confirmation unnecessarily. PROPOSAL: Delete 'verbose' rule in AGENTS.md; move 'step-by-step' logic to the 'Code-Review' skill.
About This Skill
Debug Your AI's Logic Stack
When an AI agent behaves inconsistently, it’s rarely a single prompt issue—it's usually a layer conflict. Modern AI development involves stacking system prompts, developer instructions, repository-level rules (like AGENTS.md), skill-specific logic, and persistent memory. These layers often collide, leading to "behavior drift" where the agent becomes over-cautious, ignores instructions, or hallucinates constraints.
What it does
The Instruction Layer Auditor acts as a debugger for your agent’s "operating system." It maps out every instruction layer, extracts operational rules, and identifies precise points of failure. Rather than just adding more instructions to fix a bug, this skill helps you prune and normalize your prompt stack for maximum reliability.
- Layer Mapping: Identifies conflicts between system prompts and local repo rules.
- Conflict Detection: Flags direct contradictions and hidden logic loops.
- Normalization: Provides a strategic rewrite plan to move rules to their high-precedence layers.
- Risk Assessment: Predicts when a stack will cause over-verbosity or tool-use failures.
Why use this skill?
Manually auditing thousands of lines of stacked prompts is error-prone. This skill uses a structured framework to find "misplaced" rules—like a global formatting constraint buried in a local memory file—and tells you exactly where they should live to avoid logic bloat.
Use Cases
- Identify conflicting rules across system prompts and repository-level docs.
- Reduce prompt token bloat by identifying redundant instructions across layers.
- Fix "over-cautious" behavior caused by overlapping safety or logic constraints.
- Normalize where rules live to ensure predictable agent behavior across a team.
- Clean up stale instructions in durable memory or long-term context windows.
How to Install
mkdir -p ~/.claude/skills/instruction-layer-auditor && curl -s -X POST 'https://api.promptspace.in/api/skills/instruction-layer-auditor/install' | python3 -c "import sys,json; sys.stdout.write(json.load(sys.stdin).get('installInstructions') or '')" > ~/.claude/skills/instruction-layer-auditor/SKILL.mdFree skills install directly. Paid skills require purchase - use the download button above after buying.
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OpenClaw, Cursor, Claude Code, Codex CLI
Creator
PromptSpace
We build AI agent skill packages for content creators. Specializing in Chinese social media automation.