crisp

Terse mode for AI agents. Full technical accuracy. Zero fluff.

Before / After

Without crisp:

"Sure! I'd be happy to help you with that. The issue you're experiencing is likely caused by a problem in your authentication middleware where the token expiry check is using the wrong comparison operator..."

With crisp:

Bug in auth middleware. Token expiry check uses < not <=. Fix:

if (now <= expiry) { ... }

Same fix. A fraction of the words.

Attribution

crisp was inspired by existing terse-output and agent-behavior work, including:

• Caveman by Julius Brussee
• Caveman skill by Matt Pocock
• Common “no fluff” prompting patterns used in coding-agent workflows

crisp is my professional-tone variation of this idea: normal concise replies, no meme-style output, and clearer handling around code, errors, and risky operations.

Why crisp

crisp focuses on concise replies that still sound normal and professional.

The goal is not maximum compression at all costs. The goal is to remove filler while preserving clarity, especially in coding and technical workflows.

crisp stays terse by default, but stops compressing when clarity matters.

Destructive operations, security warnings, and irreversible actions automatically get clear full-sentence warnings — then crisp resumes immediately after. You get speed everywhere except where clarity actually matters.

// Destructive op — crisp switches to clear prose automatically:

Warning: This permanently destroys all data in `users`. Cannot be undone.

DROP TABLE users;

Verify backup first.   ← crisp resumes here

Install

crisp follows the Agent Skills specification. It works with any agent that supports skills.

npx skills add shubhamv123/crisp

Any other agent / browser:
Paste the contents of SKILL.md at the start of your conversation:

"Follow these instructions for this entire conversation: [paste SKILL.md]"

Usage

Once active, crisp stays on for the entire conversation — no need to re-trigger every message.

What crisp reduces

• Unnecessary openings: "sure", "happy to help", "great question"
• Soft filler: "basically", "actually", "simply", "just"
• Repeated context already present in the user’s message
• Long hedging phrases when the answer is already clear
• Over-explaining before the actual fix

crisp should not remove words when doing so would make the answer ambiguous, unsafe, or harder to follow.

What always stays

• All technical terms, exact and unchanged
• Code blocks, untouched
• Error messages, quoted exactly
• Numbers and specifics

Auto-Clarity Exception

crisp automatically switches to clear prose for:

• Destructive / irreversible operations
• Security warnings
• Multi-step sequences where fragment order could cause mistakes

It resumes crisp immediately after the warning is done. You don't need to manage this — it happens automatically.

crisp — benchmark results

Benchmarked using real Claude API output tokens across 3 runs per prompt averaged.
Baseline = plain Claude without crisp enabled.

Average Reduction

Highlights

• Up to 70% fewer output tokens
• Up to 70% shorter responses
• Works best on verbose reasoning-heavy answers
• Safety/clarity preserved for risky operations (drop-table intentionally less compressed)

Notes

• Output tokens measured from Claude API .modelUsage[model].outputTokens
• Input token usage is unchanged
• Benchmarks run on: 2026-05-20
• Reproduce locally:

chmod +x run_benchmark.sh && ./run_benchmark.sh

Built and tested following the Agent Skills specification. Inspired by existing terse-output skills, with a focus on normal professional concise output.