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Chisle

Skill Development Usable
Works inClaude Code
Usable Scanned — metadata only

Reduces AI coding agent operational costs by 40–60% through token optimization without sacrificing output quality, directly lowering inference spend across m…

Cut your AI coding agent's token bill on three axes: terse prose, YAGNI-first code, and tool-output compression. Claude Code, Pi, Cursor, Codex, Gemini + 4 more. Zero deps, published benchmarks including the runs it loses.

470 starsMIT (commercial OK)FreeQuick setup
Usable rating — This tool is functional but has notable gaps. Review the evaluation notes below before deploying.

Reduces AI coding agent operational costs by 40–60% through token optimization without sacrificing output quality, directly lowering inference spend across multiple LLM platforms.

Engineering teams running Claude Code or similar agents at scale seeking measurable cost reduction and published performance comparisons.

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https://github.com/JayPokale/Chisle

By JayPokale

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install JayPokale/Chisle

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.

First thing to try

After installing, paste this into Claude:

Help me reduce Claude's token usage by compressing verbose code outputs into terse formats
CostFree

Trust Signals Auto-scanned

Stars470Last updated2026-09-19LicenseMIT (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-09-19 · scanner v1

Community Pulse New

No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 470 GitHub stars; contributors unknown; last commit 0d ago; license MIT.

Things to check

  • Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
3/5
Versatility
4/5
Reliability
3/5
Security
3/5
Overall score3.25 / 5.00 UsableEvaluatedSep 2026
Scored from trust signals (evidence-eval-v1): 470 GitHub stars; contributors unknown; last commit 0d ago; license MIT.

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