Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jtsang4/efficient-coding --skill prunegit clone --depth 1 https://github.com/jtsang4/efficient-codingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jtsang4/efficient-coding/prune)<a href="https://agentmods.dev/skills/jtsang4/efficient-coding/prune"><img src="https://agentmods.dev/badge/skills/jtsang4/efficient-coding/prune/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jtsang4/efficient-coding/prune"><img src="https://agentmods.dev/badge/skills/jtsang4/efficient-coding/prune.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00118 | $0.02859 |
| Opus 5.5 | $0.00047 | $0.01144 |
| Sonnet 5.5 | $0.00024 | $0.00572 |
| Haiku 4.5 | $0.00012 | $0.00286 |
Grade A, and why
prune scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 16d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 147 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prune
Agents add code more readily than they remove it. Each session solves its task locally: it writes a helper instead of finding the existing one, guards against failures that cannot happen, keeps the old path "just in case", and narrates the change in a comment. When the architecture gives code no obvious home, the same concept gets rebuilt in every corner. Over time, the project accumulates more code, concepts, and dependencies than its behavior needs.
This skill fights that entropy in periodic passes, from removing a dead function up to restructuring modules. The goal is a net reduction in what a reader must understand — fewer lines, files, concepts, and dependencies — with behavior unchanged except where the user explicitly agrees to remove a feature. Making code merely prettier is not the goal. A change that adds structure must pay for itself with measurable reduction: concepts merged, duplicates eliminated, dependency rules that stop a smell from recurring.
The skill operates on the current working tree and branch as it finds them. It does not create branches or worktrees; isolation is the caller's responsibility.
Scope
By default, every run surveys the whole project and considers every class of change. The user does not need to pass anything.
Narrow the run only when the user asks for it in their own words, e.g. "only src/server", "just what changed since last time", "only the safe stuff, don't ask me". Map such requests onto the knobs below and state the resulting scope at the start of the run:
- Paths — survey only the given paths. Candidates are still checked against the whole repository for duplicates and references.
- Since last run — survey only files changed since the most recent run record's end commit. If that commit is not an ancestor of
HEAD, fall back to the record's date withgit log --sinceand note the fallback. - Mechanical only — execute mechanical items without the confirmation stop; record everything else as deferred.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 16d ago First seen · 147 lines · 118 tokens per session scan A ec8d6c9d382f
prune is a skill published in the GitHub repository jtsang4/efficient-coding (2 stars, last pushed 8d ago), licensed MIT. It adds 118 tokens to every session and 2,859 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-04.
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