cli-creator▌
OWNER/REPO · updated May 7, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Build a composable CLI for Codex from various sources like API docs, OpenAPI specs, and existing scripts.
| name | cli-creator |
| description | 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 companion skill. |
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> || true
If 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 || true
Then 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 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:
- Environment variable using the service's standard name, such as
GITHUB_TOKEN. - User config under
~/.<tool-name>/config.tomlor another simple documented path. --api-keyor 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
- 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.
- Sketch the command list in chat. Keep names short and shell-friendly.
- Scaffold the CLI with a README or equivalent repo-facing instructions.
- Implement
doctor, discovery, resolve, read commands, one narrow draft or dry-run write path if requested, and the raw escape hatch. - Install the CLI on PATH so
tool-name ...works outside the source folder. - Smoke test from another repo or
/tmp, not only withcargo runor package-manager wrappers. Runcommand -v <tool-name>,<tool-name> --help, and<tool-name> --json doctor. - 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 commanduvor a virtualenv only when dependencies are actually needed
Add a Makefile target such as make install-local that installs the command on PATH and document whether it depends on uv, a virtualenv, or only system Python.
Companion Skill
After the CLI works, create or update a small skill for it. Use $skill-creator when it is available. Use $CODEX_HOME/skills/<tool-name>/SKILL.md for a personal companion skill unless the user names a repo-local .codex/skills/... path or another skill repo.
Write the companion skill in the order a future Codex thread should use the CLI, not as a tour of every feature. Explain:
- How to verify the installed command exists.
- Which command to run first.
- How auth is configured.
- Which discovery command finds the common ID.
- The safe read path.
- The intended draft/write path.
- The raw escape hatch.
- What not to do without explicit user approval.
- Three copy-pasteable command examples.
Keep API reference details in the CLI docs or a skill reference file. Keep the skill focused on ordering, safety, and examples future Codex threads should actually run.
How to use cli-creator on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add cli-creator
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches cli-creator from GitHub repository OWNER/REPO and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate cli-creator. Access the skill through slash commands (e.g., /cli-creator) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★66 reviews- ★★★★★Kofi Mehta· Dec 28, 2024
cli-creator reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Arya Patel· Dec 28, 2024
Solid pick for teams standardizing on skills: cli-creator is focused, and the summary matches what you get after install.
- ★★★★★Maya Tandon· Dec 24, 2024
Registry listing for cli-creator matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Anika Huang· Dec 12, 2024
Keeps context tight: cli-creator is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Dhruvi Jain· Dec 8, 2024
I recommend cli-creator for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Sophia Ndlovu· Dec 8, 2024
We added cli-creator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Anika Yang· Dec 4, 2024
We added cli-creator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Oshnikdeep· Nov 27, 2024
Solid pick for teams standardizing on skills: cli-creator is focused, and the summary matches what you get after install.
- ★★★★★Carlos Nasser· Nov 27, 2024
cli-creator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Carlos Sharma· Nov 27, 2024
Useful defaults in cli-creator — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
showing 1-10 of 66