cli-cycle

A tool that runs a complete continuous-improvement review of a project by coordinating the available cli- tools. It collects their findings, groups corrections by severity, and repeats the review after changes.

In plain words
What is it for?
Use it for a full project review, health check, weekly improvement cycle, or audit of all applicable cli- checks.
Why use it?
It brings several project checks into one review so issues can be prioritized and followed through to a clean result.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/destynova2/cli-code-skills/cli-cycle
Any agent
npx skills add Destynova2/cli-code-skills --skill cli-cycle
Clone the repo
git clone --depth 1 https://github.com/Destynova2/cli-code-skills

Made for: Claude Code, Codex.

Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,464 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00093 $0.03464
Opus 5 $0.00046 $0.01732
Sonnet 5 $0.00019 $0.00693
Haiku 4.5 $0.00009 $0.00346

Measured yesterday against content hash 2949b9d38d22, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

cli-cycle 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 yesterday.

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.

cli-cycle/SKILL.md · 270 lines

How it starts

The opening of the file, as written. The whole thing — 270 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Optimization: This skill uses on-demand loading. Heavy content lives in references/ and is loaded only when needed.

Language rule: Skill instructions are written in English. When generating user-facing output (reports, files, documentation), detect the project's primary language (from README, comments, docs, commit messages) and produce the output in that language. If the project is bilingual, ask the user which language to use before proceeding.

Cycle — Phoenix Continuous Improvement

"The phoenix does not die — it burns what is impure and is reborn stronger. Each cycle consumes the flaws. When there is nothing left to burn, the project is born."

Run every applicable cli-* skill on the current project, collect results, deliver the complete list of corrections in 3 tiers, and loop until clean.

Core Principles

  1. You don't duplicate logic — you delegate. Each sub-agent reads the real SKILL.md and follows its instructions. You orchestrate, collect, and judge.
  2. Show everything. Never truncate the correction list. The user sees ALL issues, organized by severity.
  3. Phoenix loop. Audit → user fixes → re-audit → repeat until convergence.
  4. Autonomous convergence. When invoked with --converge, run the entire loop in an isolated worktree, then present a single unified plan. Read references/convergence.md for the full algorithm.
  5. Flow graph. Skills form a DAG: audit detects → forge corrects → git commits → re-audit verifies. No cycles allowed. Read references/skill-flow.md for the complete trigger graph, deduplication rules, and cycle detection.

Gotchas — read ../gotchas.md before producing output to avoid known mistakes.

Workflow

Step 0.5 — Determine scope

$ARGUMENTS can be:

  • Empty or project root → full project audit (all directories, all skills)
  • A subdirectory (e.g., src/features/dlp/) → scoped audit (vertical slice)

Scoped audit rules:

  1. Only scan files within the scope directory (and its subdirectories)
  2. Pass the scope directory as $ARGUMENTS to every sub-agent: /cli-audit-code {scope}, /cli-audit-test {scope}, etc.
  3. Skills that don't accept a directory scope (e.g., cli-forge-pipeline, cli-forge-github) are skipped — they are project-wide by nature
  4. The scorecard, triage, and report are titled with the scope: # Cycle — {project} / {scope}
  5. Co-located tests are detected within the scope: {scope}/**/test*, {scope}/**/*_test.*, {scope}/**/tests/
  6. Co-located docs are detected within the scope: {scope}/**/*.md, {scope}/**/README*

Read the full file on GitHub · 270 lines

Files

What ships with it

3 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.

Changes

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.

  1. yesterday First seen · 270 lines · 93 tokens per session scan A 2949b9d38d22

Subscribe to this mod's changes

cli-cycle is a skill published in the GitHub repository Destynova2/cli-code-skills (5 stars, last pushed 9d ago), licensed MIT. It adds 93 tokens to every session and 3,464 once invoked, about $0.0005 per session on Opus 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 2026-08-31.