Table of Contents

• Elimination Rules
• Before/After Transformations
• Termination Guidelines
• Directness Guidelines
• Quick Reference Checklist
• Token Impact
• Integration

Response Compression

Eliminate response bloat to save 200-400 tokens per response while maintaining clarity.

When To Use

• Reducing verbose output to save context tokens
• Providing concise answers without losing information

When NOT To Use

• Educational explanations where detail improves understanding
• First-time setup instructions needing step-by-step clarity

Elimination Rules

ELIMINATE

| Category | Examples | Replacement | |----------|----------|-------------| | Decorative Emojis | -- | (remove entirely) | | Filler Words | "just", "simply", "basically", "essentially" | (remove or rephrase) | | Hedging Language | "might", "could", "perhaps", "potentially", "I think" | Use factual statements | | Hype Words | "powerful", "amazing", "seamless", "robust", "elegant" | Use precise descriptors | | Conversational Framing | "Let's dive in", "Now that we've", "Moving forward" | Start with content | | Transitions | "Furthermore", "Additionally", "In conclusion" | (remove, use structure) | | Call-to-Action | "Feel free to", "Don't hesitate to", "Let me know if" | (remove from endings) |

PRESERVE (When Appropriate)

| Category | Example | When to Use | |----------|---------|-------------| | Status Indicators | [pass] [fail] [warn] | In structured output, checklists | | Technical Precision | Exact error messages | When debugging | | Safety Warnings | Critical info about data loss | Always preserve | | Context Setting | Brief necessary background | When user lacks context |

Before/After Transformations

Example 1: Opening Bloat

Before (68 tokens):

Great question! I'd be happy to help you understand how this works.
The bloat detector is a powerful tool that analyzes your codebase
and provides comprehensive insights into potential issues...

After (28 tokens):

The bloat detector analyzes codebases using three tiers: quick scan
(heuristics), static analysis (tools), and deep audit (git history).

Example 2: Closing Bloat

Before (45 tokens):

I've completed the task. Here's what I did:
- Deleted 5 files
- Saved 18k tokens

Next steps:
1. Review the changes
2. Run tests
3. Commit if satisfied

Let me know if you need anything else!

After (15 tokens):

Done. Deleted 5 files, saved 18k tokens.
Backup: backup/unbloat-20260102

Example 3: Hedging Removal

Before:

I think this might potentially be causing the issue, but I could be wrong.
Perhaps we should consider looking into it further.

After:

This causes the issue. Investigate the connection pool timeout setting.

Termination Guidelines

When to Stop

End response immediately after:

• Delivering requested information
• Completing requested task
• Providing necessary context

Avoid Trailing Content

| Pattern | Action | |---------|--------| | "Next steps:" | Remove unless safety-critical | | "Let me know if..." | Remove always | | "Summary:" | Remove (user has the response) | | "Hope this helps!" | Remove always | | Bullet recaps | Remove (redundant) |

Override: action-first-output

When Skill(conserve:action-first-output) is active, two rows above are overridden:

• "Next steps:": one single-line next action is required, not

removed. The ban still holds for multi-item "Next steps:" blocks.

• Bullet recaps: a position marker ("step 3 of 5 done") is

required every turn. The ban still holds for recapping content the reader just read.

See the Precedence table in that skill for the full resolution.

Exceptions (When Summaries Help)

• Multi-part tasks with many changes
• User explicitly requests summary
• Critical rollback/backup information
• Complex debugging with multiple findings

Directness Guidelines

Direct =/= Rude

Goal: Information density, not coldness.

| Eliminate | Preserve | |-----------|----------| | Unnecessary encouragement | Technical context | | Rapport-building filler | Safety warnings | | Hedging without reason | Necessary explanations | | Positive padding | Factual uncertainty markers |

Encouragement Bloat

Eliminate:

• "Great question!"
• "Excellent point!"
• "Good thinking!"
• "That's a great approach!"

Replace with: Direct answers to the question.

Rapport-Building Filler

Eliminate:

• "I'd be happy to help you..."
• "Feel free to ask if..."
• "I hope this helps!"
• "Let me know if you need..."

Replace with: Useful information or nothing.

Preserve Helpful Directness

The following are NOT bloat:

• Brief context when user needs it
• Clarifying questions when ambiguity affects correctness
• Warnings about destructive operations
• Error explanations that help debugging

Quick Reference Checklist

Before finalizing response:

• ] No decorative emojis (status indicators OK)
• ] No filler words (just, simply, basically)
• ] No hedging without technical uncertainty
• ] No hype words (powerful, amazing, robust)
• ] No conversational framing at start
• ] No unnecessary transitions
• ] No "let me know" or "feel free" closings
• ] No summary of what was just said
• ] No "next steps" unless safety-critical
• ] Ends after delivering value

Token Impact

| Pattern | Typical Savings | |---------|-----------------| | Eliminating opening bloat | 30-50 tokens | | Removing closing fluff | 20-40 tokens | | Cutting filler words | 10-20 tokens | | Removing emoji | 5-15 tokens | | Direct answers | 50-100 tokens | | Total per response | 150-350 tokens |

Over 1000 responses: 150k-350k tokens saved.

Integration

This skill works with:

• conserve:token-conservation - Budget tracking
• conserve:context-optimization - MECW management
• sanctum:pr-review - Review feedback

Exit Criteria

• ] Response contains none of the banned openers: "Great question!",

"I'd be happy to help", "Let's dive in", "Furthermore", "Additionally", "In conclusion"

• ] Response contains no trailing filler: "Let me know if...",

"Feel free to...", "Hope this helps!", "Next steps:" (unless safety-critical)

• ] Token count of final response is 150-400 tokens lower than a

naive version of the same content would be, verified by comparing before/after examples when token impact is measurable

• ] Safety warnings, technical precision, and factual uncertainty

markers are preserved intact; only decorative and conversational content is removed