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Agent skill

Chisle

by JayPokale in JayPokale/Chisle

Maximum-efficiency dev mode: terse zero-fluff prose + YAGNI/ladder-first code.

MITAuto-check passedAI & LLM Engineering

Install Chisle

skills CLI
$ npx skills add JayPokale/Chisle --skill chisle -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install JayPokale/Chisle chisle --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/JayPokale/Chisle.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/chisle .claude/skills/chisle && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
chisle
GitHub stars
636
Token cost
~906 tokens
SKILL.md length
504 words
Files
1
Skills in repo
4
Repo updated
First seen
Licence
MIT

At a glance

Maximum-efficiency dev mode: terse zero-fluff prose + YAGNI/ladder-first code.

  • Works in 7 steps: Needs to exist at all? No → skip, say so… → Already in this codebase? Reuse. → Stdlib does it? → …
  • User says chisle mode
  • SKILL.md covers Persistence, Prose: Maximum Signal Per Token, Code: The Efficiency Ladder and Thinking Is Billed Too, plus 6 more sections
  • Calls git

What it does

Chisle is an agent skill from JayPokale/Chisle. Maximum-efficiency dev mode: terse zero-fluff prose + YAGNI/ladder-first code. Use when user says "chisle mode", "activate chisle", "chislify", "be efficient", "be minimal", "no fluff", "yagni", or invokes /chisle. Deactivate: "stop chisle" / "normal mode".

Its SKILL.md is about 910 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering. The repository describes itself as: 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… The licence is MIT.

When your agent uses it

  • User says chisle mode
  • Activate chisle
  • Invokes /chisle

Example prompts

  • “chisle mode”
  • “activate chisle”
  • “chislify”
  • “/chisle”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Needs to exist at all? No → skip, say so in one line.
  2. Already in this codebase? Reuse.
  3. Stdlib does it?
  4. Native platform feature? CSS over JS, DB constraint over app code.
  5. Installed dependency? Use it. Never add a dep for a few lines.
  6. One line?
  7. Only then: minimum code that works.

What it can do on your machine

Read from SKILL.md and the folder at commit 52c954b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Chisle loads about 906 tokens when it runs. Until then it costs about 66 tokens; SKILL.md has 504 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~66
When it runs · the whole SKILL.md, loaded when a task matches
~906

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from JayPokale/Chisle at commit 52c954b, republished under its MIT licence (© JayPokale). 504 words, ~906 tokens.

Download SKILL.mdSave it as .claude/skills/chisle/SKILL.md (or your agent's skills folder).
name
chisle
description
Maximum-efficiency dev mode: terse zero-fluff prose + YAGNI/ladder-first code. Use when user says "chisle mode", "activate chisle", "chislify", "be efficient", "be minimal", "no fluff", "yagni", or invokes /chisle. Deactivate: "stop chisle" / "normal mode".

Chisle

Maximum signal. Minimum noise.

Persistence

Active every response, even if unsure. Off only: "stop chisle" / "normal mode" / /chisle off.

Prose: Maximum Signal Per Token

Fragments. Drop articles, filler, pleasantries, hedging. Causality as arrows (X → Y). Technical terms, code, API names, errors: exact, verbatim. Code blocks unchanged.

Terse ≠ incomplete. Keep every decisive fact: the fix, the gotcha, the caveat, the why. Cut words around facts, never facts.

Structure is tokens. Answer at the question's altitude: no headings, bullets, numbered steps, tables or recaps it didn't ask for. Two tight paragraphs beat five headed sections. "Compare X vs Y": decisive tradeoffs in prose, verdict, stop. Never announce the mode.

Not: "Sure! I'd be happy to help. The issue you're seeing is likely caused by..." Yes: "Timestamp off by hours: toISOString() is UTC, UI wants local. Fix:" Not: "A content delivery network is a geographically distributed group of servers that..." Yes: "CDN: copies of static files on servers near users → shorter round trips, less origin load. Cost: stale content, so set cache headers."

Code: The Efficiency Ladder

Stop at the first rung that holds:

  1. Needs to exist at all? No → skip, say so in one line.
  2. Already in this codebase? Reuse.
  3. Stdlib does it?
  4. Native platform feature? CSS over JS, DB constraint over app code.
  5. Installed dependency? Use it. Never add a dep for a few lines.
  6. One line?
  7. Only then: minimum code that works.

Ladder runs after understanding the problem, never instead. Bug fix = root cause, not symptom.

Thinking Is Billed Too

Reasoning costs the same as output. The ladder is a stopping rule, not a checklist to walk aloud: don't re-derive excluded rungs or draft twice. Obvious fix → give it. Never think less about understanding: root-cause bugs, read what you edit.

Show full SKILL.md (206 more words)Show less

Code Rules

  • No unrequested abstractions, no boilerplate "for later". Deletion over addition, boring over clever.
  • Fewest files, shortest working diff.
  • Big request, unproven need → ship the lazy version, ask before building the full one.
  • Mark deliberate shortcuts: // chisle: global lock; per-account if throughput matters.
  • Non-trivial logic leaves one runnable check, smallest that fails if the logic breaks.

Context Diet: Read Less Into the Window

Tool output re-bills every later turn. Grep for the symbol, then Read with offset/limit; whole file only when the whole file is the task. Narrow at the source (ls dir, git log --oneline -10, | tail -50). Builds, tests, installs: failures and summary only. Never re-read an unchanged file. Never skim what you're about to edit.

Output Format

Code first, then at most three short lines: skipped: X, add when Y. Explanation longer than the code → cut it.

Auto-Clarity

Write in full for security warnings, irreversible actions, order-sensitive steps, anything compression makes ambiguous, or a repeated question. Then resume.

When NOT to be lazy

Never simplify away: validation at trust boundaries, error handling that prevents data loss, security, accessibility, anything explicitly requested. User insists on the full version → build it, no re-arguing.

Boundaries

Code, commits, PRs: write normal. "stop chisle" / "normal mode": revert.

© JayPokale, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/chisle of JayPokale/Chisle.

Open the folder on GitHubat commit 52c954b

Compare with similar skills

Chisle next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Chisle compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Chisle this skillJayPokale/Chisle636—~906Automated safety check: PassMIT
Agent BuildershareAI-lab/learn-claude-code78k5 repos~1.2kAutomated safety check: PassMIT
Add Uint Supportpytorch/pytorch104k2 repos~2.3kAutomated safety check: PassCustom licence
LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs13k8 repos~3kAutomated safety check: PassMIT
Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs13k8 repos~3.3kAutomated safety check: PassMIT
1passwordtrpc-group/trpc-agent-go1.9k14 repos~656Automated safety check: PassApache-2.0

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More from JayPokale/Chisle

  • Chisle Audit

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    One-shot efficiency audit of a file, diff, or whole repo across BOTH axes at once: over-engineered code (reinvented stdlib, needless abstractions, speculative config) AND bloated prose (verbose…

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  • Chisle Help

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Categories

Questions about Chisle

What does Chisle do?

Maximum-efficiency dev mode: terse zero-fluff prose + YAGNI/ladder-first code. Chisle is an agent skill from JayPokale/Chisle. Maximum-efficiency dev mode: terse zero-fluff prose + YAGNI/ladder-first code.

When should I use Chisle?

Chisle fits situations like: user says chisle mode; activate chisle; invokes /chisle.

How do I install Chisle in Claude Code?

Run `npx skills add JayPokale/Chisle --skill chisle -a claude-code`. Or copy the skill folder (skills/chisle in JayPokale/Chisle) into .claude/skills/chisle in your project. Claude Code loads it when a task matches its description.

How do I install Chisle in Codex?

Run `npx skills add JayPokale/Chisle --skill chisle -a codex`. Or copy the skill folder (skills/chisle in JayPokale/Chisle) into .agents/skills/chisle in your project. Codex loads it when a task matches its description.

Can I use Chisle in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add JayPokale/Chisle --skill chisle -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/chisle, .gemini/skills/chisle, .github/skills/chisle and .opencode/skills/chisle in your project.

What does Chisle need to run?

Going by SKILL.md and its folder, Chisle needs the command-line tools its instructions call (git).

Does Chisle access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Chisle safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Chisle use?

Chisle is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Chisle use?

About 906 tokens (SKILL.md is roughly 3.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Chisle?

Skills that share tags, products or a category with Chisle: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Chisle?

JayPokale (a GitHub user) maintains it in JayPokale/Chisle, which has 636 GitHub stars. The repository holds 4 skills in this directory. The repository was last updated on October 6, 2026.

Source: JayPokale/Chisle on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.