Agent skill

Cost Booster Edit

by ruvnet in ruvnet/ruflo

Apply a simple code transform via agent-booster's WASM engine — sub-millisecond, deterministic, $0 (no LLM call).

MITAuto-check: notes

Install Cost Booster Edit

skills CLI
$ npx skills add ruvnet/ruflo --skill cost-booster-edit -a claude-code

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

GitHub CLI
$ gh skill install ruvnet/ruflo cost-booster-edit --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/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ruflo-cost-tracker/skills/cost-booster-edit .claude/skills/cost-booster-edit && 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
cost-booster-edit
GitHub stars
74k
Token cost
~1.4k tokens
SKILL.md length
508 words
Files
1
Skills in repo
264
Repo updated
First seen
Licence
MIT

At a glance

Apply a simple code transform via agent-booster's WASM engine — sub-millisecond, deterministic, $0 (no LLM call).

  • Works in 6 steps: Take inputs — intent (one of the 6… → Read the source to a variable, derive… → Invoke — run from anywhere under v3/ so… → …
  • SKILL.md covers When to use, Steps, Measured benchmark… and What's verified locally, plus 1 more section
  • Calls node

What it does

Cost Booster Edit is an agent skill from ruvnet/ruflo. Apply a simple code transform via agent-booster's WASM engine — sub-millisecond, deterministic, $0 (no LLM call). Companion to cost-booster-route.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It works with WebAssembly. The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.

Example prompts

  • “/cost-booster-edit”

Requirements

  • Pre-approved tools (allowed-tools): Bash

Workflow steps

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

  1. Take inputs — intent (one of the 6 booster intents) and file path.
  2. Read the source to a variable, derive the intended edit text from the intent (caller supplies).
  3. Invoke — run from anywhere under v3/ so agent-booster resolves
  4. Check confidence — default threshold is 0.5. Below that, fail closed: do NOT write the file; report and escalate to Tier 2/3.
  5. Write back the output field if success && confidence >= 0.5.
  6. Persist outcome — memory_store --namespace cost-tracking --key "booster-edit-..." --value '{"intent":..., "latency":..., "confidence"…

What it can do on your machine

Read from SKILL.md and the folder at commit 58e0ae7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • node

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

  • Network

    No URLs in SKILL.md.

    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

Cost Booster Edit loads about 1.4k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 508 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash

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 ruvnet/ruflo at commit 58e0ae7, republished under its MIT licence (© ruvnet). 508 words, ~1,439 tokens.

Download SKILL.mdSave it as .claude/skills/cost-booster-edit/SKILL.md (or your agent's skills folder).
name
cost-booster-edit
description
Apply a simple code transform via agent-booster's WASM engine — sub-millisecond, deterministic, $0 (no LLM call). Companion to cost-booster-route.
allowed-tools
Bash
argument-hint
<intent> <file>

Cost Booster Edit

Direct wrapper around agent-booster.apply() (npm agent-booster v0.2.x, exposed via agentic-flow/agent-booster). Use when a transform is already classified as Tier 1 eligible — cost-booster-route recommends whether; this skill executes.

When to use

  • Bulk transforms across many files (var → const, add-types, remove-console, add-error-handling, async-await, add-logging).
  • Any simple, structural edit where an LLM would otherwise be called and billed.
  • Inside CI pipelines where determinism + zero-cost matter more than naturalness.

Do NOT use when the transform requires reasoning about intent, naming, or cross-file context — those are Tier 2/3 jobs.

Steps

  1. Take inputs — intent (one of the 6 booster intents) and file path.

  2. Read the source to a variable, derive the intended edit text from the intent (caller supplies).

  3. Invoke — run from anywhere under v3/ so agent-booster resolves:

    bash
    node --input-type=module -e '
      import("agent-booster")
        .then(async ({ AgentBooster }) => {
          const booster = new AgentBooster();
          const r = await booster.apply({
            code: process.argv[1],
            edit: process.argv[2],
            language: process.argv[3] || "javascript",
          });
          console.log(JSON.stringify({
            success: r.success, output: r.output, latency: r.latency,
            confidence: r.confidence, strategy: r.strategy,
            tokens: r.tokens,
          }));
        })
        .catch(e => console.log(JSON.stringify({ success: false, error: String(e.message) })));
    ' -- "$CODE" "$EDIT" "$LANG"
  4. Check confidence — default threshold is 0.5. Below that, fail closed: do NOT write the file; report and escalate to Tier 2/3.

  5. Write back the output field if success && confidence >= 0.5.

  6. Persist outcome — memory_store --namespace cost-tracking --key "booster-edit-..." --value '{"intent":..., "latency":..., "confidence":..., "strategy":..., "applied":true}'. Feed the routing learner via hooks_model-outcome (use the cost-optimize skill's step 8).

Measured benchmark (2026-05-04, this checkout)

5 representative intents run through AgentBooster.apply():

intentlatency (ms)wall (ms)confidencestrategysuccess
var-to-const550.65fuzzy_replacetrue
add-types110.64fuzzy_replacetrue
remove-console000.70fuzzy_replacetrue
add-error-handling000.85exact_replacetrue
async-await000.85exact_replacetrue

Avg measured latency ≈ 1.2 ms. All 5 above the default 0.5 confidence threshold. See docs/benchmarks/0002-baseline.md for the LLM-baseline comparison.

Show full SKILL.md (254 more words)Show less

What's verified locally

ClaimStatus here
100% win rateVerified — 12/12 on bench/booster-corpus.json (see runs/latest.json). Booster AND Gemini 2.0 Flash both score 12/12 — this is a structural-correctness corpus, not a hard adversarial one.
Sub-millisecond latencyVerified — avg 0.67 ms, p50 0 ms, p99 6 ms, max 6 ms.
$0 per editVerified structurally — no API call, no token billing.
Deterministic AST-based mergeVerified — same inputs reproduce the same output and strategy.
Confidence ≥ 0.5 ⇒ correctVerified on this corpus — 12/12 above 0.5 (min 0.551), all correct.
350× speedup vs. LLMVerified — exceeded against every tier: 1000.9× vs Gemini 2.0 Flash, 1838.7× vs Claude Sonnet 4.6, 2634.1× vs Claude Opus 4.7. Run BENCH_LLM_BASELINE=1 BENCH_ANTHROPIC=1 node scripts/bench.mjs to refresh.
Cost saved per editMeasured: $0.000020 vs Gemini, $0.000722 vs Sonnet 4.6, $0.004720 vs Opus 4.7 (the booster side is $0 in all cases).
Win parity with frontier LLMsVerified — Booster, Gemini 2.0 Flash, Sonnet 4.6, Opus 4.7 all scored 12/12 on this corpus. Booster matches LLM accuracy structurally for deterministic transforms.

To extend: add cases to bench/booster-corpus.json, run ( cd v3 && node ../plugins/ruflo-cost-tracker/scripts/bench.mjs ) (or with BENCH_LLM_BASELINE=1), commit runs/latest.json. Smoke step 23 fails the build if win rate drops below 0.80.

Override the LLM model: BENCH_LLM_MODEL='claude-sonnet-4' (when wired against api.anthropic.com) or BENCH_LLM_MODEL='models/gemini-2.5-flash' for a reasoning-model comparison. Pricing flags: BENCH_LLM_PRICE_IN, BENCH_LLM_PRICE_OUT.

fuzzy_replace is best-effort; for production transforms prefer cases that route to exact_replace (≥0.85 confidence in our sample).

Cross-references

ADR-0002 §"Decision 1" (route classifier) and §"Riskiest assumption" (Bash-shelled invocation) · cost-booster-route (classifier-side companion) · agent-booster npm README (3-mode install, MCP / npm / HTTP).

© ruvnet, 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 plugins/ruflo-cost-tracker/skills/cost-booster-edit of ruvnet/ruflo.

Open the folder on GitHubat commit 58e0ae7

Compare with similar skills

Cost Booster Edit 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.

Cost Booster Edit compared with similar skills
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Cost Booster Edit this skillruvnet/ruflo74k—~1.4kAutomated safety check: NotesMIT
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Update V86felixrieseberg/windows9524k—~1.7kAutomated safety check: PassCustom licence
Dotlottie WebLottieFiles/dotlottie-web892—~3.5kAutomated safety check: PassMIT
Adding Internal API RouteTriliumNext/Trilium38k—~3.3kAutomated safety check: PassAGPL-3.0

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Works with

Questions about Cost Booster Edit

What does Cost Booster Edit do?

Apply a simple code transform via agent-booster's WASM engine — sub-millisecond, deterministic, $0 (no LLM call). Cost Booster Edit is an agent skill from ruvnet/ruflo. Apply a simple code transform via agent-booster's WASM engine — sub-millisecond, deterministic, $0 (no LLM call).

How do I install Cost Booster Edit in Claude Code?

Run `npx skills add ruvnet/ruflo --skill cost-booster-edit -a claude-code`. Or copy the skill folder (plugins/ruflo-cost-tracker/skills/cost-booster-edit in ruvnet/ruflo) into .claude/skills/cost-booster-edit in your project. Claude Code loads it when a task matches its description.

How do I install Cost Booster Edit in Codex?

Run `npx skills add ruvnet/ruflo --skill cost-booster-edit -a codex`. Or copy the skill folder (plugins/ruflo-cost-tracker/skills/cost-booster-edit in ruvnet/ruflo) into .agents/skills/cost-booster-edit in your project. Codex loads it when a task matches its description.

Can I use Cost Booster Edit 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 ruvnet/ruflo --skill cost-booster-edit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cost-booster-edit, .gemini/skills/cost-booster-edit, .github/skills/cost-booster-edit and .opencode/skills/cost-booster-edit in your project.

What does Cost Booster Edit need to run?

Going by SKILL.md and its folder, Cost Booster Edit needs the command-line tools its instructions call (node). Its frontmatter pre-approves these tools: Bash.

Does Cost Booster Edit access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Cost Booster Edit safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Cost Booster Edit use?

Cost Booster Edit 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 Cost Booster Edit use?

About 1.4k tokens (SKILL.md is roughly 5.8k 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 Cost Booster Edit?

Skills that share tags, products or a category with Cost Booster Edit: RuView CLI, API and WASM (ruvnet/RuView, 97k stars), Nginx To Higress Migration (higress-group/higress, 9.5k stars), Update V86 (felixrieseberg/windows95, 24k stars) and Dotlottie Web (LottieFiles/dotlottie-web, 892 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cost Booster Edit?

ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,159 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 9, 2026.

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