Implementation Kickoff
openai/openai-guardrails-js
Start or resume a requested Guardrails implementation or PR takeover in the selected linked worktree with bounded scope and verification.
Design spec with 98 rules for building CLI tools that AI agents can safely use.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-native-cli --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-native-cli .claude/skills/ai-native-cli && rm -rf skills-srcUse ~/.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/
Install the "ai-native-cli" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-native-cli into .claude/skills/ai-native-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-native-cli", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-native-cliType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-native-cli --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-native-cli .agents/skills/ai-native-cli && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-native-cli" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-native-cli into .agents/skills/ai-native-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-native-cli", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-native-cli --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-native-cli .cursor/skills/ai-native-cli && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-native-cli" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-native-cli into .cursor/skills/ai-native-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-native-cli", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/sickn33/agentic-awesome-skills.git --path skills/ai-native-cli--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-native-cli --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-native-cli .gemini/skills/ai-native-cli && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-native-cli" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-native-cli into .gemini/skills/ai-native-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-native-cli", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install sickn33/agentic-awesome-skills ai-native-cliInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-native-cli .github/skills/ai-native-cli && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-native-cli" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-native-cli into .github/skills/ai-native-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-native-cli", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install sickn33/agentic-awesome-skills ai-native-cli --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/sickn33/agentic-awesome-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-native-cli .opencode/skills/ai-native-cli && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-native-cli" agent skill from https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/ai-native-cli into .opencode/skills/ai-native-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-native-cli", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
ai-native-cliDesign spec with 98 rules for building CLI tools that AI agents can safely use.
AI Native CLI is an agent skill from sickn33/agentic-awesome-skills. Design spec with 98 rules for building CLI tools that AI agents can safely use. Covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, and agent self-description.
Its SKILL.md is about 3.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering LLM guardrails. The repository describes itself as: AAS Core is the local, agent-first control plane for complete catalog discovery, agent-owned selection, stack validation, and planning, backed by 2,400+ agentic skills. Includes… The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 1e53ce2. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
jqFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
github.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AI Native CLI loads about 3.3k tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 1,486 words of instructions outside code blocks.
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.
The automated check found no risky patterns in SKILL.md.
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.
The full file from sickn33/agentic-awesome-skills at commit 1e53ce2, republished under its MIT licence (© sickn33). 1,486 words, ~3,280 tokens.
.claude/skills/ai-native-cli/SKILL.md (or your agent's skills folder).When building or modifying CLI tools, follow these rules to make them safe and reliable for AI agents to use.
A comprehensive design specification for building AI-native CLI tools. It defines 98 rules across three certification levels (Agent-Friendly, Agent-Ready, Agent-Native) with prioritized requirements (P0/P1/P2). The spec covers structured JSON output, error handling, input contracts, safety guardrails, exit codes, self-description, and a feedback loop via a built-in issue system.
--humanThis spec uses two orthogonal axes:
core, recommended, ecosystemP0, P1, P2Use layers for migration and certification:
agent/, skills, issue, inline contextCertification maps to layers:
core rules passcore + recommended rules passDefault is agent mode (JSON). Explicit flags to switch:
$ mycli list # default = JSON output (agent mode)
$ mycli list --human # human-friendly: colored, tables, formatted
$ mycli list --agent # explicit agent mode (override config if needed)Every CLI tool MUST have an agent/ directory at its project root. This is the
tool's identity and behavior contract for AI agents.
agent/
brief.md # One paragraph: who am I, what can I do
rules/ # Behavior constraints (auto-registered)
trigger.md # When should an agent use this tool
workflow.md # Step-by-step usage flow
writeback.md # How to write feedback back
skills/ # Extended capabilities (auto-registered)
getting-started.mdEach level includes all rules from the previous level.
Priority tag [P0]=agent breaks without it, [P1]=agent works but poorly, [P2]=nice to have.
Goal: CLI is a stable, callable API. Agent can invoke, parse, and handle errors.
Output -- default is JSON, stable schema
[P0] O1: Default output is JSON. No --json flag needed[P0] O2: JSON MUST pass jq . validation[P0] O3: JSON schema MUST NOT change within same versionError -- structured, to stderr, never interactive
[P0] E1: Errors -> {"error":true, "code":"...", "message":"...", "suggestion":"..."} to stderr[P0] E4: Error has machine-readable code (e.g. MISSING_REQUIRED)[P0] E5: Error has human-readable message[P0] E7: On error, NEVER enter interactive mode -- exit immediately[P0] E8: Error codes are API contracts -- MUST NOT rename across versionsExit Code -- predictable failure signals
[P0] X3: Parameter/usage errors MUST exit 2[P0] X9: Failures MUST exit non-zero -- never exit 0 then report error in stdoutComposability -- clean pipe semantics
[P0] C1: stdout is for data ONLY[P0] C2: logs, progress, warnings go to stderr ONLYInput -- fail fast on bad input
[P1] I4: Missing required param -> structured error, never interactive prompt[P1] I5: Type mismatch -> exit 2 + structured errorSafety -- protect against agent mistakes
[P1] S1: Destructive ops require --yes confirmation[P1] S4: Reject ../../ path traversal, control charsGuardrails -- runtime input protection
[P1] G1: Unknown flags rejected with exit 2[P1] G2: Detect API key / token patterns in args, reject execution[P1] G3: Reject sensitive file paths (*.env, *.key, *.pem)[P1] G8: Reject shell metacharacters in arguments (; | && $())Goal: CLI is self-describing, well-named, and pipe-friendly. Agent discovers capabilities and chains commands without trial and error.
Self-Description -- agent discovers what CLI can do
[P1] D1: --help outputs structured JSON with commands[][P1] D3: Schema has required fields (help, commands)[P1] D4: All parameters have type declarations[P1] D7: Parameters annotated as required/optional[P1] D9: Every command has a description[P1] D11: --help outputs JSON with help, rules, skills, commands[P1] D15: --brief outputs agent/brief.md content[P1] D16: Default JSON (agent mode), --human for human-friendly[P2] D2/D5/D6/D8/D10: per-command help, enums, defaults, output schema, versionInput -- unambiguous calling convention
[P1] I1: All flags use --long-name format[P1] I2: No positional argument ambiguity[P2] I3/I6/I7: --json-input, boolean --no-X, array paramsError
[P1] E6: Error includes suggestion field[P2] E2/E3: errors to stderr, error JSON validSafety
[P1] S8: --sanitize flag for external input[P2] S2/S3/S5/S6/S7: default deny, --dry-run, no auto-update, destructive markingExit Code
[P1] X1: 0 = success[P2] X2/X4-X8: 1=general, 10=auth, 11=permission, 20=not-found, 30=conflictComposability
[P1] C6: No interactive prompts in pipe mode[P2] C3/C4/C5/C7: pipe-friendly, --quiet, pipe chain, idempotencyNaming -- predictable flag conventions
[P1] N4: Reserved flags (--agent, --human, --brief, --help, --version, --yes, --dry-run, --quiet, --fields)[P2] N1/N2/N3/N5/N6: consistent naming, kebab-case, max 3 levels, --version semverGuardrails
[P1] I8/I9: no implicit state, non-interactive auth[P1] G6/G9: precondition checks, fail-closed[P2] G4/G5/G7: permission levels, PII redaction, batch limits| Flag | Semantics | Notes |
|---|---|---|
--agent | JSON output (default) | Explicit override |
--human | Human-friendly output | Colors, tables, formatted |
--brief | One-paragraph identity | For sync into agent config |
--help | Full self-description JSON | Brief + commands + rules + skills + issue |
--version | Semver version string | |
--yes | Confirm destructive ops | Required for delete/destroy |
--dry-run | Preview without executing | |
--quiet | Suppress stderr output | |
--fields | Filter output fields | Save tokens |
Goal: CLI has identity, behavior contract, skill system, and feedback loop. Agent can learn the tool, extend its use, and report problems -- full closed-loop collaboration.
Agent Directory -- tool identity and behavior contract
[P1] D12: agent/brief.md exists[P1] D13: agent/rules/ has trigger.md, workflow.md, writeback.md[P1] D17: agent/rules/*.md have YAML frontmatter (name, description)[P1] D18: agent/skills/*.md have YAML frontmatter (name, description)[P2] D14: agent/skills/ directory + skills subcommandResponse Structure -- inline context on every call
[P1] R1: Every response includes rules[] (full content from agent/rules/)[P1] R2: Every response includes skills[] (name + description + command)[P1] R3: Every response includes issue (feedback guide)Meta -- project-level integration
[P2] M1: AGENTS.md at project root[P2] M2: Optional MCP tool schema export[P2] M3: CHANGELOG.md marks breaking changesFeedback -- built-in issue system
[P2] F1: issue subcommand (create/list/show)[P2] F2: Structured submission with version/context/exit_code[P2] F3: Categories: bug / requirement / suggestion / bad-output[P2] F4: Issues stored locally, no external service dependency[P2] F5: issue list / issue show <id> queryable[P2] F6: Issues have status tracking (open/in-progress/resolved/closed)[P2] F7: Issue JSON has all required fields (id, type, status, message, created_at, updated_at)[P2] F8: All issues have status field$ mycli list
{"result": [{"id": 1, "title": "Buy milk", "status": "todo"}], "rules": [...], "skills": [...], "issue": "..."}{
"error": true,
"code": "AUTH_EXPIRED",
"message": "Access token expired 2 hours ago",
"suggestion": "Run 'mycli auth refresh' to get a new token"
}0 success 10 auth failed 20 resource not found
1 general error 11 permission denied 30 conflict/precondition
2 param/usage errorImplement by layer -- each phase gets you the next certification level.
Phase 1: Agent-Friendly (core)
--json flag needed{ error, code, message, suggestion } to stderr--yes guard on destructive operationsPhase 2: Agent-Ready (+ recommended)
8. --help returns structured JSON (help, commands[], rules[], skills[])
9. --brief reads and outputs agent/brief.md content
10. --human flag switches to human-friendly format
11. Reserved flags: --agent, --version, --dry-run, --quiet, --fields
12. Exit codes: 20 not found, 30 conflict, 10 auth, 11 permission
Phase 3: Agent-Native (+ ecosystem)
13. Create agent/ directory: brief.md, rules/trigger.md, rules/workflow.md, rules/writeback.md
14. Every command response appends: rules[] + skills[] + issue
15. skills subcommand: list all / show one with full content
16. issue subcommand for feedback (create/list/show/close/transition)
17. AGENTS.md at project root
suggestion field in every error responseagent/brief.md to one paragraph for token efficiencyProblem: CLI outputs human-readable text by default, breaking agent parsing
Solution: Make JSON the default output format; add --human flag for human-friendly mode
Problem: Errors reported in stdout with exit code 0 Solution: Always exit non-zero on failure and write structured error JSON to stderr
Problem: CLI prompts for missing input interactively Solution: Return structured error with suggestion field and exit immediately
@cli-best-practices - General CLI design patterns (this skill focuses specifically on AI agent compatibility)© sickn33, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/ai-native-cli of sickn33/agentic-awesome-skills.
Open the folder on GitHubat commit 1e53ce2
We found 11 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in sickn33/agentic-awesome-skills, which our catalogue first saw on October 7, 2026.
AI Native CLI 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Native CLI this skillsickn33/agentic-awesome-skills | 47k | 2 repos | ~3.3k | Automated safety check: Pass | MIT | |
| Implementation Kickoffopenai/openai-guardrails-js | 104 | — | ~1k | Automated safety check: Pass | MIT | |
| Manor Coding Guardrailsmanor-os/manor-ai | 161 | — | ~816 | Automated safety check: Pass | MIT | |
| Git Guardrails Claude Codefossasia/eventyay-interpretation | 1.6k | 12 repos | ~578 | Automated safety check: Pass | Apache-2.0 | |
| Git Guardrails Claude Codevinvcn/mattpocock-skills-zh-CN | 4.6k | — | ~474 | Automated safety check: Pass | MIT | |
| Wa Guardrailsaws-samples/sample-well-architected-skills-and-steering | 273 | — | ~2.8k | Automated safety check: Pass | MIT-0 |
openai/openai-guardrails-js
Start or resume a requested Guardrails implementation or PR takeover in the selected linked worktree with bounded scope and verification.
manor-os/manor-ai
A skill your agent uses when writing, reviewing, or refactoring Manor code to avoid overcomplication, make surgical changes, surface assumptions, and define verifiable success criteria.
fossasia/eventyay-interpretation
Set up Claude Code hooks to block dangerous git commands (push, reset --hard, clean, branch -D, etc.) before they execute.
vinvcn/mattpocock-skills-zh-CN
设置 Claude Code hooks,在危险 git commands(push、reset --hard、clean、branch -D 等)执行前阻止它们。适用于用户想防止破坏性 git 操作、添加 git safety hooks,或在 Claude Code 中阻止 git push/reset 时。
aws-samples/sample-well-architected-skills-and-steering
Generate preventive Well-Architected guardrails — AWS Config rules, Service Control Policies, permission boundaries, CloudWatch alarms, and IaC policy checks (CDK Aspects, cfn-guard, OPA/Sentinel) —…
yusifeng/formax
A skill your agent uses when we want to turn a just-finished Formax workflow (e.g.
sickn33/agentic-awesome-skills
Implements an interface in one of two named color modes, iridescent white or colorful black, from a parameterized starter that reports measured color intensity.
sickn33/agentic-awesome-skills
Saves a user's project decisions, rules and preferences into a project-local mdbase so later sessions and other agents can recover the intent.
sickn33/agentic-awesome-skills
Keeps project decisions, research and verified results available across coding-agent sessions through LWC memory, a document Wiki graph and a CodeGraph code index.
sickn33/agentic-awesome-skills
Guides an agent through assessing its own owner for cofounder fit, publishing an approved profile, and ranking complementary profiles other agents published for their owners.
sickn33/agentic-awesome-skills
Integracao com WhatsApp Business Cloud API (Meta). An agent skill from sickn33/agentic-awesome-skills.
sickn33/agentic-awesome-skills
Acts as a proxy for the Cline CLI, dispatching coding tasks one at a time, monitoring runs by hard evidence, relaying decisions to you and learning per-project preferences.
Categories
Design spec with 98 rules for building CLI tools that AI agents can safely use. AI Native CLI is an agent skill from sickn33/agentic-awesome-skills. Design spec with 98 rules for building CLI tools that AI agents can safely use.
AI Native CLI fits situations like: tasks that involve LLM guardrails.
Run `npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a claude-code`. Or copy the skill folder (skills/ai-native-cli in sickn33/agentic-awesome-skills) into .claude/skills/ai-native-cli in your project. Claude Code loads it when a task matches its description.
Run `npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a codex`. Or copy the skill folder (skills/ai-native-cli in sickn33/agentic-awesome-skills) into .agents/skills/ai-native-cli in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sickn33/agentic-awesome-skills --skill ai-native-cli -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-native-cli, .gemini/skills/ai-native-cli, .github/skills/ai-native-cli and .opencode/skills/ai-native-cli in your project.
Going by SKILL.md and its folder, AI Native CLI needs the command-line tools its instructions call (jq).
SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
AI Native CLI is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.3k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with AI Native CLI: Implementation Kickoff (openai/openai-guardrails-js, 104 stars), Manor Coding Guardrails (manor-os/manor-ai, 161 stars), Git Guardrails Claude Code (fossasia/eventyay-interpretation, 1.6k stars) and Git Guardrails Claude Code (vinvcn/mattpocock-skills-zh-CN, 4.6k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
sickn33 (a GitHub user) maintains it in sickn33/agentic-awesome-skills, which has 47,304 GitHub stars. The repository holds 1,394 skills in this directory. The repository was last updated on October 6, 2026.
Source: sickn33/agentic-awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.