by JayPokale
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.
# Add to your Claude Code skills
git clone https://github.com/JayPokale/ChisleLast scanned: 9/17/2026
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"scannedAt": "2026-09-17T09:13:50.575Z",
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}See how Chisle compares with popular alternatives.
Chisle is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by JayPokale. 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. It has 634 GitHub stars.
Yes. Chisle passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/JayPokale/Chisle" and add it to your Claude Code skills directory (see the Installation section above).
Chisle is primarily written in JavaScript. It is open-source under JayPokale on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh Chisle against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Chisle is a Claude Code plugin that makes Claude cheaper to run without making it dumber. It cuts what Claude writes: no filler, no hedging, no speculative abstractions, just the smallest code that works. It also cuts what Claude reads: a PostToolUse hook trims oversized tool output by ~46% before it re-enters the context window, where it would be re-billed on every later request. In agent-loop tests Claude with Chisle passes the same tasks as Claude without it. One npx chisle installs it, and the same ruleset ships to Pi, Cursor, Codex, Gemini, Copilot, OpenCode, Antigravity and four more agents. Every number here comes from committed raw transcripts, including the runs where it lost.
"Add debounce to a search input that currently fires an API call on every keystroke." Same model, same prompt, one difference: the injected ruleset. Both answers below are the verbatim committed output from benchmarks/results/raw/:
Opens with "Let me show you the most common approaches", then ships a reusable generic useDebounce<T> hook in its own file…
// useDebounce.ts
export function useDebounce<T>(
value: T, delay: number
): T {
const [debouncedValue, setDebouncedValue]
= useState<T>(value);
useEffect(() => { /* … */ }, [value, delay]);
return debouncedValue;
}
…then Option 2 and Option 3, a comparison table, and a caveats section.
Asks which framework, then answers the question that was actually asked: setTimeout in the effect you already have, no new file, no generic:
useEffect(() => {
const timer = setTimeout(async () => {
if (query.trim()) { /* fetch */ }
}, 300);
return () => clearTimeout(timer);
}, [query]);
Then two lines on why it works, and "use lodash.debounce if already installed."
Not golfed, boring. Same behaviour, one less abstraction, no second file, and it names the dependency you might already have instead of reinventing it.
| axis | what | how |
|---|---|---|
| Output: prose | filler, hedging, manufactured structure | zero-fluff ruleset, injected per session |
| Output: code | speculative abstractions, unrequested boilerplate | YAGNI efficiency ladder |
| Input: context | oversized tool output flooding the window | Claude PostToolUse / Pi tool_result: scrub, elide, dedup, plus prevention rules |
Where each one attaches to a session:
flowchart LR
subgraph S["Session start"]
H1["Ruleset injection<br/>once per active session"]
end
subgraph T["Every turn"]
H2["Mode tracking<br/>Claude + Pi"]
end
subgraph L["Every tool call"]
H3["PostToolUse / tool_result<br/>scrub → elide → dedup"]
end
H1 --> M(["Model"])
H2 --> M
M -->|writes| O["Output:<br/>terser prose,<br/>YAGNI-first code"]
M -->|calls a tool| TOOL[["Bash / grep / web / extension tools"]]
TOOL -->|raw output| H3
H3 -->|"compressed, rebuilt into<br/>the tool's own shape"| M
RE["Read / Edit / Write"] -.->|"never touched,<br/>exact bytes feed later edits"| M
style M fill:#1f2937,stroke:#d78a3c,color:#e6edf3
style O fill:#14532d,stroke:#2da44e,color:#e6edf3
style H3 fill:#1f2937,stroke:#2da44e,color:#e6edf3
style RE fill:#3f1d1d,stroke:#cf3b3b,color:#e6edf3
The loop on the right is the input axis: tool output is billed again on every later request in the session, so shrinking it once pays repeatedly. Read, Edit, and Write are deliberately outside it.
One command. Auto-detects your agents (Claude Code, Pi, Cursor, Windsurf, Cline, Kiro, Antigravity, Codex, Gemini, Copilot, OpenCode, Hermes) and wires each one. --uninstall puts everything back.
npx chisle
# or via curl
curl -fsSL https://raw.githubusercontent.com/JayPokale/Chisle/main/install.sh | bash
# Windows
irm https://raw.githubusercontent.com/JayPokale/Chisle/main/install.ps1 | iex
Preview first with npx chisle --dry-run, scope with --only claude or --only pi, see everything with npx chisle --help. Remove with npx chisle --uninstall.
Upgrading, per-agent setup, --stats and config: docs/usage.md.
Claude Code 2.1.285 on Haiku 4.5, 13 live prompts × 2 seeds = 26 cells per arm, billed output tokens vs the same model with no ruleset (writeup + raw cells):
| total bill | 95% CI | visible answer | worst cell | backfires | |
|---|---|---|---|---|---|
| caveman | 102% | 79–128% | 105% | 305% | 15 / 26 |
| ponytail | 105% | 86–129% | 97% | 493% | 16 / 26 |
| Chisle | 83% | 69–95% | 76% | 170% | 11 / 26 |
Chisle is the only arm below a bare model. It pays on long answers (77%) and coding prompts (76%); on short answers it breaks even (106%).
On Pi + GPT-5.5 Chisle again gives the shortest answers, 37% the length of a bare model's (caveman 56%, ponytail 49%), though on total billed tokens ponytail edges it, 59% to 61%:
Input side: tool output is 67.5% of context in 171 measured Claude Code sessions, and it is re-billed on every later request. The compressor cut ~46% off every eligible output there, and 27.4% of tool output on top of Pi's own truncation (receipts).
| prose | code judgment | input/context | worst-case guard | publishes failures | |
|---|---|---|---|---|---|
| caveman | ✅ | ❌ | ❌ | ❌ 305% | ❌ |
| ponytail | ❌ | ✅ | ❌ | ❌ 493% | ❌ |
| headroom | ❌ | ❌ | ✅ proxy | n/a | ❌ |
| Chisle | ✅ | ✅ | ✅ hook | 170% | ✅ |
Every table, chart and caveat, including the June suite and the Pi run in full: docs/benchmarks.md. Head to head: docs/comparison.md.
Before writing code, the agent stops at the first rung that holds:
flowchart TD
A[Request for code] --> R[Read the problem fully]
R --> Q1{Does this need<br/>to exist at all?}
Q1 -->|no| S1[Skip it. Say so in one line]
Q1 -->|yes| Q2{Already in<br/>this codebase?}
Q2 -->|yes| S2[Reuse it. Don't rewrite]
Q2 -->|no| Q3{Stdlib<br/>does it?}
Q3 -->|yes| S3[Use the stdlib]
Q3 -->|no| Q4{Native platform<br/>feature covers it?}
Q4 -->|yes| S4["CSS over JS, DB constraint<br/>over app code"]
Q4 -->|no| Q5{Already-installed<br/>dependency?}
Q5 -->|yes| S5[Use it. Never add a new dep<br/>for what a few lines do]
Q5 -->|no| Q6{Can it be<br/>one line?}
Q6 -->|yes| S6[One line]
Q6 -->|no| S7[The minimum code that works]
S1 & S2 & S3 & S4 & S5 & S6 & S7 --> OUT[Ship it + note what was skipped<br/>and when to add it]
style Q1 fill:#1f2937,stroke:#d78a3c,color:#e6edf3
style OUT fill:#14532d,stroke:#2da44e,color:#e6edf3
style R fill:#1f2937,stroke:#8b949e,color:#e6edf3
The ladder runs after reading, never instead of it. Note the exit: every rung lands on the same obligation: say what you skipped, so "later" doesn't quietly become "never".
The ladder runs after reading the code, lazy about the solution and never about understanding. Lazy is not negligent: trus