pi-defluffer

Pi extension that trims polite/filler text from user prompts before sending them to the model.

Inspired by GrahamTheDev's Defluffer idea: https://dev.to/grahamthedev/defluffer-reduce-token-usage-by-45-26jj

This is not magic compression. It is conservative prompt cleanup:

• removes pleasantries and filler
• collapses common phrases
• preserves code blocks, inline code, URLs, env vars, CLI flags, quoted strings
• protects detected JSON/YAML snippets while compressing surrounding text
• skips legal/policy/exact-file-output prompts
• skips slash commands and steering input
• shows a small TUI widget with estimated token savings

Install

pi install npm:pi-defluffer

From GitHub:

pi install git:github.com/RespectMathias/pi-defluffer

Commands

/defluff on
/defluff off
/defluff status
/defluff stats
/defluff profile off|safe|standardGuardedDedupe
/defluff min <0-80>
/defluff preview <text>
/defluff animation widget|off
/defluff reset-stats

Default profile: standardGuardedDedupe.

Testing

Run local tests:

npm test

This runs Vitest unit tests plus a pi extension load check.

We also tested whether prompt compression saved tokens without damaging intent.

Prompt-integrity proxy test

20 prompt fixtures across code, JSON/YAML, debugging, legal, math, creative, transcript, and agent tasks.

| Variant | Avg input savings | Quality proxy | Critical failures | | --------------------------- | ----------------: | ------------: | ----------------: | | no script | 0.0% | 5.00 | 0 | | original-ish/basic | 13.7% | 4.74 | 4 | | aggressive/extended | 13.7% | 4.78 | 3 | | standard/extended | 8.6% | 4.89 | 1 | | safe/extended | 5.6% | 5.00 | 0 | | guarded standard | 8.1% | 5.00 | 0 | | guarded + transcript dedupe | 9.5% | 5.00 | 0 |

Takeaway: aggressive compression saves more input tokens, but breaks exact terms. Guarded compression is safer.

LLM A/B test with Codex

We spawned Codex processes for baseline vs defluffed prompts, then used Codex as judge.

| Metric | Result | | ---------------------------------- | -----: | | fixtures | 6 | | avg input savings | 16.29% | | avg baseline score | 4.83 | | avg defluffed score | 4.50 | | judge ties | 5 | | baseline wins | 1 | | compression-caused critical losses | 0 |

Case breakdown:

| Case | Category | Input saved | Judge result | | -------------- | --------------- | ----------: | ------------------------------------ | | demo_001 | code refactor | 33.65% | tie | | code_002 | code generation | 4.23% | tie | | json_004 | structured | 2.94% | tie | | transcript_009 | transcript | 29.82% | tie | | legal_013 | legal | 0.00% | baseline win, not compression-caused | | copy_017 | creative | 27.08% | tie |

Estimated total tokens in LLM test went from 1779 to 1707, about 4% saved. Output length can grow, so input savings do not always equal total savings.

Practical conclusion

Use defluffing for:

• polite prompts
• noisy transcript prompts
• long natural-language task descriptions
• code tasks with fluff outside code blocks

Avoid or skip compression for:

• legal text
• policy text
• exact file-output prompts
• prompts where exact wording matters globally

For exact JSON prompts, the extension protects detected JSON/YAML snippets and still compresses safe surrounding prose.

This extension defaults to skip risky cases.