cli-creator – Coding skill for AI agents
Build a composable CLI for Codex from API docs, an OpenAPI spec, existing curl examples, an SDK, a web app, an admin tool, or a local script. Use when the user wants Codex to create a command-line tool that can run from any repo, expose composable read/write commands, return stable JSON, manage auth, and pair with a co
Install the cli-creator skill with one command
Pick the tool you use, copy the command and paste it in your terminal. The skill lands in that tool's skills folder and is ready in your next session.
Claude Code
mkdir -p ~/.claude/skills && curl -fsSL https://skill.dn1nguoi.com/z/cli-creator-0efc7.tgz | tar xz -C ~/.claude/skills
Call it in Claude Code: /cli-creator – then describe the task you want done.
Codex
mkdir -p ~/.codex/skills && curl -fsSL https://skill.dn1nguoi.com/z/cli-creator-0efc7.tgz | tar xz -C ~/.codex/skills
Call it in Codex: $cli-creator – then describe the task you want done.
Hermes Agent
mkdir -p ~/.hermes/skills && curl -fsSL https://skill.dn1nguoi.com/z/cli-creator-0efc7.tgz | tar xz -C ~/.hermes/skills
Call it in Hermes Agent: /cli-creator – then describe the task you want done.
DeepSeek
mkdir -p ~/.deepcode/skills && curl -fsSL https://skill.dn1nguoi.com/z/cli-creator-0efc7.tgz | tar xz -C ~/.deepcode/skills
Call it in DeepSeek: /cli-creator – then describe the task you want done.
SKILL.md content
CLI Creator
Create a real CLI that future Codex threads can run by command name from any working directory.
This skill is for durable tools, not one-off scripts. If a short script in the current repo solves the task, write the script there instead.
Start
Name the target tool, its source, and the first real jobs it should do:
- Source: API docs, OpenAPI JSON, SDK docs, curl examples, browser app, existing internal script, article, or working shell history.
- Jobs: literal reads/writes such as
list drafts,download failed job logs,search messages,upload media,read queue schedule. - Install name: a short binary name such as
ci-logs,slack-cli,sentry-cli, orbuildkite-logs.
Prefer a new folder under ~/code/clis/<tool-name> when the user wants a personal tool and has not named a repo.
Before scaffolding, check whether the proposed command already exists:
command -v <tool-name> || trueIf it exists, choose a clearer install name or ask the user.
Choose the Runtime
Before choosing, inspect the user's machine and source material:
command -v cargo rustc node pnpm npm python3 uv || trueThen choose the least surprising toolchain:
- Default to Rust for a durable CLI Codex should run from any repo: one fast binary, strong argument parsing, good JSON handling, easy copy/install into
~/.local/bin. - Use TypeScript/Node when the official SDK, auth helper, browser automation library, or existing repo tooling is the reason the CLI can be better.
- Use Python when the source is data science, local file transforms, notebooks, SQLite/CSV/JSON analysis, or Python-heavy admin tooling that can still be installed as a durable command.
Do not pick a language that adds setup friction unless it materially improves the CLI. If the best language is not installed, either install the missing toolchain with the user's approval or choose the next-best installed option.
State the choice in one sentence before scaffolding, including the reason and the installed toolchain you found.
Command Contract
Sketch the command surface in chat before coding. Include the binary name, discovery commands, resolve or ID-lookup commands, read commands, write commands, raw escape hatch, auth/config choice, and PATH/install command.
When designing the command surface, read [references/agent-cli-patterns.md](references/agent-cli-patterns.md) for the expected composable CLI shape.
Build toward this surface:
tool-name --helpshows every major capability.tool-name --json doctorverifies config, auth, version, endpoint reachability, and missing setup.tool-name init ...stores local config when env-only auth is painful.- Discovery commands find accounts, projects, workspaces, teams, queues, channels, repos, dashboards, or other top-level containers.
- Resolve commands turn names, URLs, slugs, permalinks, customer input, or build links into stable IDs so future commands do not repeat broad searches.
- Read commands fetch exact objects and list/search collections. Paginated lists support a bounded
--limit, cursor, offset, or clearly documented default. - Write commands do one named action each: create, update, delete, upload, schedule, retry, comment, draft. They accept the narrowest stable resource ID, support
--dry-run,draft, orpreviewfirst when the service allows it, and do not hide writes inside broad commands such asfix,debug, orauto. --jsonreturns stable machine-readable output.- A raw escape hatch exists:
request,tool-call,api, or the nearest honest name.
Do not expose only a generic request command. Give Codex high-level verbs for the repeated jobs.
Document the JSON policy in the CLI README or equivalent: API pass-through versus CLI envelope, success shape, error shape, and one example for each command family. Under --json, errors must be machine-readable and must not contain credentials.
Auth and Config
Support the boring paths first, in this precedence order:
1. Environment variable using the service's standard name, such as GITHUB_TOKEN.
2. User config under ~/.<tool-name>/config.toml or another simple documented path.
3. --api-key or a tool-specific token flag only for explicit one-off tests. Prefer env/config for normal use because flags can leak into shell history or process listings.
Never print full tokens. doctor --json should say whether a token is available, the auth source category (flag, env, config, provider default, or missing), and what setup step is missing.
If the CLI can run without network or auth, make that explicit in doctor --json: report fixture/offline mode, whether fixture data was found, and whether auth is not required for that mode.
For internal web apps sourced from DevTools curls, create sanitized endpoint notes before implementing: resource name, method/path, required headers, auth mechanism, CSRF behavior, request body, response ID fields, pagination, errors, and one redacted sample response. Never commit copied cookies, bearer tokens, customer secrets, or full production payloads.
Use screenshots to infer workflow, UI vocabulary, fields, and confirmation points. Do not treat screenshots as API evidence unless they are paired with a network request, export, docs page, or fixture.
Build Workflow
1. Read the source just enough to inventory resources, auth, pagination, IDs, media/file flows, rate limits, and dangerous write actions. If the docs expose OpenAPI, download or inspect it before naming commands.
2. Sketch the command list in chat. Keep names short and shell-friendly.
3. Scaffold the CLI with a README or equivalent repo-facing instructions.
4. Implement doctor, discovery, resolve, read commands, one narrow draft or dry-run write path if requested, and the raw escape hatch.
5. Install the CLI on PATH so tool-name ... works outside the source folder.
6. Smoke test from another repo or /tmp, not only with cargo run or package-manager wrappers. Run command -v <tool-name>, <tool-name> --help, and <tool-name> --json doctor.
7. Run format, typecheck/build, unit tests for request builders, pagination/request-body builders, no-auth doctor, help output, and at least one fixture, dry-run, or live read-only API call.
If a live write is needed for confidence, ask first and make it reversible or draft-only.
When the source is an existing script or shell history, split the working invocation into real phases: setup, discovery, download/export, transform/index, draft, upload, poll, live write. Preserve the flags, paths, and environment variables the user already relies on, then wrap the repeatable phases with stable IDs, bounded JSON, and file outputs.
For raw escape hatches, support read-only calls first. Do not run raw non-GET/HEAD requests against a live service unless the user asked for that specific write.
For media, artifact, or presigned upload flows, test each phase separately: create upload, transfer bytes, poll/read processing status, then attach or reference the resulting ID.
For fixture-backed prototypes, keep fixtures in a predictable project path and make the CLI locate them after installation. Smoke-test from /tmp to catch binaries that only work inside the source folder.
For log-oriented CLIs, keep deterministic snippet extraction separate from model interpretation. Prefer a command that emits filenames, line numbers or byte ranges, matched rules, and short excerpts.
Rust Defaults
When building in Rust, use established crates instead of custom parsers:
clapfor commands and helpreqwestfor HTTPserde/serde_jsonfor payloadstomlfor small config filesanyhowfor CLI-shaped error context
Add a Makefile target such as make install-local that builds release and installs the binary into ~/.local/bin.
TypeScript/Node Defaults
When building in TypeScript/Node, keep the CLI installable as a normal command:
commanderorcacfor commands and help- native
fetch, the official SDK, or the user's existing HTTP helper for API calls zodonly where external payload validation prevents real breakagepackage.jsonbinentry for the installed commandtsup,tsx, ortscusing the repo's existing convention
Add an install path such as pnpm install, pnpm build, and pnpm link --global, or a Makefile target that installs a small wrapper into ~/.local/bin.
Python Defaults
When building in Python, prefer boring standard-library pieces unless the workflow needs more:
argparsefor commands and help, ortyperwhen subcommands would otherwise get messyurllib.request/urllib.parse,requests, orhttpxfor HTTP, matching what is already installed or already used nearbyjson,csv,sqlite3,pathlib, andsubprocessfor local files, exports, databases, and existing scriptspyproject.tomlconsole script or a small executable wrapper for the installed command
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