rlm-context-rot-detector

RLM Context Rot Detector — The Circuit Breaker

You exist at two levels:

1. In the moment: Detecting rot symptoms during execution
2. Across the session: Persistent awareness that this skill exists (the skill loop)

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What is Context Rot?

Context Rot is the phenomenon where LLM quality degrades as context length increases. It manifests differently based on task complexity:

Task Complexity	Degradation Pattern	When It Starts
Constant (O(1))	Slow degradation	~100K+ tokens
Linear (O(N))	Moderate degradation	~32K tokens
Quadratic (O(N²))	Catastrophic failure	~8K tokens

The insight: More complex problems rot faster at shorter lengths.

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Rot Symptoms to Monitor

Symptom 1: Circular Reasoning

What it looks like:

• Same suggestion made twice
• Returning to already-tried approaches
• "Let me try X" when X was already tried

Detection:

IF (current_approach ∈ previous_approaches) THEN ROT_DETECTED

Symptom 2: Vague or Hedging Language

What it looks like:

• "This might work"
• "I'm not entirely sure"
• "One possible approach"
• Excessive caveats

Detection:

IF (uncertainty_phrases > 3 in response) THEN ROT_WARNING

Symptom 3: Missed Obvious Connections

What it looks like:

• Information from early context ignored
• Relevant prior findings not referenced
• "Lost in the middle" behavior

Detection:

IF (relevant_prior_info NOT IN current_reasoning) THEN ROT_DETECTED

Symptom 4: Rushing / Completion Mode

What it looks like:

• Shorter responses than warranted
• Skipping verification steps
• "This should work" without testing
• Premature closure

Detection:

IF (response_depth < expected_depth) OR (verification_skipped) THEN ROT_DETECTED

Symptom 5: Contradictions

What it looks like:

• Stating something that conflicts with prior statements
• Ignoring constraints mentioned earlier
• Inconsistent reasoning

Detection:

IF (current_statement CONTRADICTS prior_statement) THEN ROT_DETECTED

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The Rot Severity Scale

Level	Symptoms	Action
0: Fresh	None	Continue normally
1: Warning	1-2 minor symptoms	Note the warning, increase vigilance
2: Active Rot	3+ symptoms OR 1 major	Trigger RLM mode or state dump
3: Severe Rot	Obvious degradation	STOP — recommend fresh session

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Protective Measures

Measure 1: Switch to RLM Mode

When: Rot detected due to context size, not complexity.

TRIGGER: Context > 50K tokens AND rot symptoms detected
ACTION: Switch to RLM paradigm
- Invoke rlm-orchestrator skill
- Treat context as environment
- Use sub-queries to reduce active context

Measure 2: State Dump

When: Rot detected during debugging or complex reasoning.

TRIGGER: 3+ failed attempts OR circular reasoning detected
ACTION: Dump state to persistent storage

STATE_DUMP:
  - Current hypothesis: {what you think is happening}
  - Approaches tried: {list with outcomes}
  - Files involved: {with states}
  - Recommended next steps: {for fresh session}

Measure 3: Fresh Session Recommendation

When: Severe rot or accumulated context pollution.

TRIGGER: Severe rot OR extended session with declining quality
ACTION: Recommend fresh start
- Document all relevant state
- Provide clear handoff instructions
- Do NOT continue with degraded context

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The 3-Strike Rule (Reinforced)

This is a hard rule. No exceptions.

Strike 1: First failed attempt
  → Note it, adjust approach

Strike 2: Second failed attempt  
  → Document both attempts, significantly change approach

Strike 3: Third failed attempt
  → STOP IMMEDIATELY
  → Write state dump
  → Recommend fresh session
  → DO NOT attempt a fourth time

Why this works: A fresh context often immediately sees what polluted context cannot. The solution becomes obvious when you're not carrying the baggage of failed attempts.

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Self-Referential Skill Loop

The Problem with Linear Reading

When you read a prompt top-to-bottom:

• Information at the beginning is processed without context of what comes later
• Information at the end may not connect to early context
• The full picture only exists momentarily in the middle

The Skill Loop Solution

This skill exists to create a persistent awareness that transcends linear reading:

┌─────────────────────────────────────────────────────────────┐
│                                                             │
│  START: Read RLM skills                                     │
│    ↓                                                        │
│  rlm-orchestrator/SKILL.md (references this skill)         │
│    ↓                                                        │
│  rlm-context-scout/SKILL.md                                │
│    ↓                                                        │
│  rlm-repl-environment/SKILL.md                             │
│    ↓                                                        │
│  rlm-context-rot-detector/SKILL.md (YOU ARE HERE)          │
│    ↓                                                        │
│  ← References back to orchestrator →                        │
│    ↓                                                        │
│  INTEGRATION: Now you've seen the full picture             │
│                                                             │
└─────────────────────────────────────────────────────────────┘

Reinforcement Block

Read this twice if needed:

The RLM skill suite teaches you to think recursively:

1. Orchestrator = Strategic planning (Manager)
2. Context Scout = Reconnaissance (finding without reading)
3. REPL Environment = Technical execution
4. Context Rot Detector = (You are here) Self-monitoring

When you finish reading this skill, you should have internalized:

• Context window is precious — don't pollute it
• Massive inputs → RLM mode (environment, not input)
• Quality degradation → dump state and restart
• The skill loop reinforces persistent awareness

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Integration with Other Skills

rlm-orchestrator ←──────────────────────────────────────────→ rlm-context-rot-detector
       ↓                                                              ↑
rlm-context-scout                                                     │
       ↓                                                              │
rlm-repl-environment ─────────────────────────────────────────────────┘

The loop:

• Orchestrator references Context Rot Detector for self-monitoring
• Context Rot Detector references Orchestrator to trigger RLM mode
• All skills are aware of each other

Invoking this skill:

When to check for Context Rot:
- Before complex reasoning on large context
- After 3+ steps without progress
- When "something feels off"
- Periodically during extended sessions

Reference: skills/rlm-context-rot-detector/SKILL.md

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Context Rot in RLM Sub-Queries

Even with RLM mode, sub-queries can experience rot if chunks are too large.

Prevention:

MAX_CHUNK_SIZE = 400000  # Stay well under 500K limit

if len(chunk) > MAX_CHUNK_SIZE:
    print("WARNING: Chunk exceeds safe size, splitting...")
    # Split and process separately

Detection in sub-query results:

# Check sub-query response for rot symptoms
rot_indicators = [
    "i'm not sure",
    "this might",
    "possibly",
    "it could be",
    "one approach"
]

if any(indicator in sub_result.lower() for indicator in rot_indicators):
    print(f"WARNING: Sub-query shows uncertainty. Consider re-querying with smaller context.")

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Quick Reference Card

┌─────────────────────────────────────────────────────────────┐
│               CONTEXT ROT DETECTOR                          │
├─────────────────────────────────────────────────────────────┤
│                                                             │
│  SYMPTOMS:                                                  │
│  ▪ Circular reasoning (same approach twice)                 │
│  ▪ Vague/hedging language                                   │
│  ▪ Missing obvious connections                              │
│  ▪ Rushing to complete                                      │
│  ▪ Contradictions                                           │
│                                                             │
│  SEVERITY:                                                  │
│  0 = Fresh    → Continue                                    │
│  1 = Warning  → Increase vigilance                          │
│  2 = Active   → RLM mode or state dump                      │
│  3 = Severe   → STOP, fresh session                         │
│                                                             │
│  3-STRIKE RULE:                                             │
│  3 failed attempts = STOP + state dump                      │
│  No exceptions.                                             │
│                                                             │
│  THE MANTRA:                                                │
│  Fresh context beats polluted brilliance.                   │
│                                                             │
└─────────────────────────────────────────────────────────────┘

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The Meta-Lesson

This skill is itself an example of the pattern it teaches:

Context Rot in Skill Reading: When you read a long skill document, you experience a form of context rot — early information fades as you process later information.

The Solution Applied Here:

• Repeated key concepts (reinforcement)
• Self-referential structure (the skill loop)
• Quick reference cards (compressed summaries)
• Explicit integration notes (connecting to other skills)

Your Takeaway: You can apply these same patterns when designing prompts, skills, and workflows:

1. State the key insight early
2. Elaborate with details
3. Reinforce at the end
4. Create loops that reconnect beginning to end

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Final Reinforcement (Read This)

You have now completed the RLM skill suite:

Skill	Purpose	Key Insight
Orchestrator	Strategic planning	Context is an environment, not input
Context Scout	Reconnaissance	Never read what you can probe
REPL Environment	Technical execution	llm_query() is your superpower
Context Rot Detector	Self-monitoring	Fresh beats polluted

The unified message: When facing impossible-seeming problems with massive context:

1. Don't stuff — probe and decompose
2. Don't overload — delegate to sub-queries
3. Don't degrade — detect rot and restart
4. Think recursively — the answer emerges from the process

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Stay fresh. Detect the rot. Protect the signal.

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Loop Back ↺

If any of this is unclear, start again from rlm-orchestrator/SKILL.md. The skills form a circle, and re-reading with full context often clarifies what was murky on first pass.

This is the RLM pattern applied to learning RLM: Recursive passes over the material, each time with more context, until the understanding crystallizes.