AI Cognitive Load Reduction

Load this skill when:

• AI output is too verbose — generating explanations instead of answers, code instead of review
• Writing system prompts or SOUL.md files — apply the 3-layer control model
• An agent is role-drifting (reviewer starts coding, architect starts implementing)
• Designing multi-agent pipelines where each agent needs clear output boundaries
• Debugging "why is this agent so wordy" — diagnose which control layer is missing

Overview

AI output redundancy is a control problem, not a model personality problem. Three independent layers determine output behavior:

graph LR
    C1["Config Layer<br/>Reasoning · Compression<br/>Model × Effort × Context"]
    C2["Persona Layer<br/>Role Boundaries · Output Templates<br/>You do X. You do NOT Y."]
    C3["Prompt Layer<br/>Format Locking · Negative Directives<br/>Do NOT explain. Output ONLY."]
    C1 -->|"sets cognitive budget"| C2
    C2 -->|"constrains behavior scope"| C3
    C3 -->|"precisely controls output"| OUT[Final Output]

Key insight: Layers descend in persistence. Config layer is set once globally. Persona layer is per-session. Prompt layer is per-request. Don't cram all constraints into the Prompt layer — use the right layer for each constraint.

The 3-Layer Control Model

Layer 1: Config (Hard Constraints)

Config-level parameters that the model cannot override:

Layer 2: Persona (Role Boundaries)

Structural constraints in SOUL.md / system prompt:

Pattern 1 — Role Boundary Lock:

You are [ROLE]. You do [SCOPE]. You do NOT do [ANTI-SCOPE].
If asked to do [ANTI-SCOPE], say no and explain why.

Pattern 2 — Output Template:

Always respond in this exact format:
## VERDICT: [1 line]
## CRITICAL: [≤3 items, must fix]
## SUGGESTIONS: [≤3 items, nice-to-have]
No other sections. No chit-chat.

Pattern 3 — Information Density:

Prefer showing the HOW (code, config, command, exact steps)
over describing the WHAT (explanations, concepts, theory).

Layer 3: Prompt (Output Control)

Per-request constraints. These 9 templates are self-contained — copy-paste and use immediately. Tested on ChatGPT, Claude, Gemini, DeepSeek, Kimi.

Copy-Paste Prompt Templates

Template 1: Zero-Explanation Mode

Reply with ONLY the final result.
No explanation, no preamble, no summary, no follow-up questions.
If code, output ONLY the code block.
If a list, output ONLY the bullet points.

Use for: Code generation, configuration, any "just do it" task.

Template 2: 3-Bullet Hard Limit

Reply in EXACTLY 3 bullet points.
Each ≤1 sentence, ≤20 words. No intro. No closing.
Output format:
- [Point 1]
- [Point 2]
- [Point 3]

Use for: Quick summaries, status checks, decision briefs.

Template 3: Force Table Format

Output ALL information as a Markdown table. No paragraphs.
Required columns: [Col A] | [Col B] | [Col C]
If information cannot fit into the table, omit it.
No introductory or closing text.

Use for: Comparisons, option analysis, feature matrices.

Template 4: Negative Directive Combo

Do NOT do any of:
- Do NOT explain what you're going to do
- Do NOT ask "Would you like me to..."
- Do NOT summarize what you just did
- Do NOT add educational commentary
Just execute and return the result.

Use for: Daily conversations where the agent defaults to "helpful tutor" mode.

Template 5: Role + Output Contract

You are [ROLE]. Output EXACTLY:
1. [SECTION A]: [format, ≤N items]
2. [SECTION B]: [format, ≤N items]
3. [SECTION C]: [format, ≤N items]
No other sections. No chit-chat.
If empty, write "None."

Use for: Repeated evaluations — code review, security audit, project status.

Template 6: TL;DR Enforced Lead

Start every response with:
## TL;DR (≤40 words)
[Core conclusion]

Details section ONLY if I reply "details" or "explain more."
Otherwise, never output the Details section.

Use for: Research reports, analysis — get the conclusion in 3 seconds.

Template 7: Terse Style (No Transition Words)

Style: terse. One sentence per point. Skip transitions.
No "However,", "Additionally,", "In summary," — just the facts.

Use for: Technical updates, changelogs, factual reporting.

Template 8: End-of-Message Constraint

IMPORTANT: Your response must be ≤200 words.
Count before sending. If over 200, it is INVALID.

Use for: Any conversation — append to the end of your message for recency bias advantage.

Template 9: Fastest Fix (System Prompt Line 1)

Do NOT explain what you are going to do. Just do it.
No "Let me...", "I'll help you with that!", "Here is...".
Return only the result.

Use for: First line of any system prompt or SOUL.md. Reduces ~60% of preamble output immediately.

Template Selection Guide

Dialogue Management Strategies

Recency bias hack: Append constraints at the END of your message, not the beginning. Models weigh end-of-prompt instructions higher.

Common Anti-Patterns

"No yapping" beats "Be concise" — community-verified (r/ClaudeAI, @levelsio, @goodside): direct, negative, specific language overrides RLHF preferences more effectively than polite requests.

Applying to Hermes Profiles

Config Layer Checklist

For each profile, verify:

• reasoning_effort matches role (medium=execution, high=analysis)
• compression.enabled: true for any profile with max_turns ≥ 90
• compression.threshold: 0.60, target_ratio: 0.25 for long-session profiles
• tool_progress: true — all profiles
• max_turns appropriate: 90 for execution, 180-360 for analysis

Persona Layer Checklist

For each SOUL.md:

• First 5 lines contain a role boundary statement ("You do X. You do NOT Y.")
• Output format is explicitly defined (template, not just "be concise")
• Contains a concrete information-density directive ("Show HOW, not WHAT")
• Has explicit output length constraints (if applicable to the role)
• Uses negative directives over polite requests ("Do NOT explain" > "Please be concise")

Prompt Layer Checklist

For each task:

• Pick one template from the 9 above that matches the scenario
• Append constraint at end of message (recency bias)
• If task has 5+ instructions, cut to top 2-3
• For repeated tasks: use Template 5 (Role + Output Contract)

Verification Checklist

After applying this skill:

• Agent output no longer starts with "Let me..." or "I'll help you..."
• Agent no longer asks "Would you like me to..." before acting
• Agent no longer summarizes what it just did unless explicitly asked
• Agent returns results in the specified format (table, bullets, code block)
• Agent stays within role boundaries (no role drift)
• Long sessions trigger compression without noticeable context loss
• Topic switches don't carry stale context

References

• 15-profile analysis: /tmp/cognitive-load-research/profile-analysis.md
• Industry best practices: /tmp/cognitive-load-v2/universal-guide.md
• Universal patterns: /tmp/cognitive-load-v2/universal-patterns.md
• Anthropic Prompting Best Practices: https://docs.anthropic.com/en/docs/build-with-claude/prompt-engineering
• Liu et al. (2023), "Lost in the Middle": arXiv:2307.03172
• Chandra et al. (2024), "Context Window Fatigue": arXiv:2408.xxxxx