/ai-native-cli
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.
$ npx -y skills add sickn33/antigravity-awesome-skills --skill ai-native-cli --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/ai-native-cli
Context preview
The summary Claude sees to decide when to auto-load this skill.
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.
SKILL.md
ai-native-cli.SKILL.mdname: ai-native-cli
description: "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."
risk: safe
source: https://github.com/ChaosRealmsAI/agent-cli-spec
date_added: "2026-03-15"
Agent-Friendly CLI Spec v0.1
When building or modifying CLI tools, follow these rules to make them safe and reliable for AI agents to use.
Overview
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.
When to Use This Skill
- Use when building a new CLI tool that AI agents will invoke
- Use when retrofitting an existing CLI to be agent-friendly
- Use when designing command-line interfaces for automation pipelines
- Use when auditing a CLI tool's compliance with agent-safety standards
Core Philosophy
1. **Agent-first** -- default output is JSON; human-friendly is opt-in via `--human` 2. **Agent is untrusted** -- validate all input at the same level as a public API 3. **Fail-Closed** -- when validation logic itself errors, deny by default 4. **Verifiable** -- every rule is written so it can be automatically checked
Layer Model
This spec uses two orthogonal axes:
- **Layer** answers rollout scope: `core`, `recommended`, `ecosystem`
- **Priority** answers severity: `P0`, `P1`, `P2`
Use layers for migration and certification:
- **core** -- execution contract: JSON, errors, exit codes, stdout/stderr, safety
- **recommended** -- better machine UX: self-description, explicit modes, richer schemas
- **ecosystem** -- agent-native integration: `agent/`, `skills`, `issue`, inline context
Certification maps to layers:
- **Agent-Friendly** -- all `core` rules pass
- **Agent-Ready** -- all `core` + `recommended` rules pass
- **Agent-Native** -- all layers pass
How It Works
Step 1: Output Mode
Default 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)
- **Default (no flag)** -- JSON to stdout. Agent never needs to add a flag.
- **--human** -- human-friendly format (colors, tables, progress bars)
- **--agent** -- explicit JSON mode (useful when env/config overrides default)
Step 2: agent/ Directory Convention
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.mdStep 3: Four Levels of Self-Description
1. **--brief** (business card, injected into agent config) 2. **Every Command Response** (always-on context: data + rules + skills + issue) 3. **--help** (full self-description: brief + commands + rules + skills + issue) 4. **skills \<name\>** (on-demand deep dive into a specific skill)
Certification Requirements
Each level includes all rules from the previous level. Priority tag `[P0]`=agent breaks without it, `[P1]`=agent works but poorly, `[P2]`=nice to have.
Level 1: Agent-Friendly (core -- 20 rules)
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 version
**Error** -- 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 versions
**Exit 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 stdout
**Composability** -- clean pipe semantics
- `[P0]` C1: stdout is for data ONLY
- `[P0]` C2: logs, progress, warnings go to stderr ONLY
**Input** -- fail fast on bad input
- `[P1]` I4: Missing required param -> structured error, never interactive prompt
- `[P1]` I5: Type mismatch -> exit 2 + structured error
**Safety** -- protect against agent mistakes
- `[P1]` S1: Destructive ops require `--yes` confirmation
- `[P1]` S4: Reject `../../` path traversal, control chars
**Guardrails** -- 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 (; | && $())
Level 2: Agent-Ready (+ recommended -- 59 rules)
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
Read more
name: ai-native-cli description: "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." risk: safe source: https://github.com/ChaosRealmsAI/agent-cli-spec date_added: "2026-03-15"
Agent-Friendly CLI Spec v0.1
When building or modifying CLI tools, follow these rules to make them safe and reliable for AI agents to use.
Overview
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.
When to Use This Skill
- Use when building a new CLI tool that AI agents will invoke
- Use when retrofitting an existing CLI to be agent-friendly
- Use when designing command-line interfaces for automation pipelines
- Use when auditing a CLI tool's compliance with agent-safety standards
Core Philosophy
1. **Agent-first** -- default output is JSON; human-friendly is opt-in via `--human` 2. **Agent is untrusted** -- validate all input at the same level as a public API 3. **Fail-Closed** -- when validation logic itself errors, deny by default 4. **Verifiable** -- every rule is written so it can be automatically checked
Layer Model
This spec uses two orthogonal axes:
- **Layer** answers rollout scope: `core`, `recommended`, `ecosystem`
- **Priority** answers severity: `P0`, `P1`, `P2`
Use layers for migration and certification:
- **core** -- execution contract: JSON, errors, exit codes, stdout/stderr, safety
- **recommended** -- better machine UX: self-description, explicit modes, richer schemas
- **ecosystem** -- agent-native integration: `agent/`, `skills`, `issue`, inline context
Certification maps to layers:
- **Agent-Friendly** -- all `core` rules pass
- **Agent-Ready** -- all `core` + `recommended` rules pass
- **Agent-Native** -- all layers pass
How It Works
Step 1: Output Mode
Default 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)
- **Default (no flag)** -- JSON to stdout. Agent never needs to add a flag.
- **--human** -- human-friendly format (colors, tables, progress bars)
- **--agent** -- explicit JSON mode (useful when env/config overrides default)
Step 2: agent/ Directory Convention
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.mdStep 3: Four Levels of Self-Description
1. **--brief** (business card, injected into agent config) 2. **Every Command Response** (always-on context: data + rules + skills + issue) 3. **--help** (full self-description: brief + commands + rules + skills + issue) 4. **skills \<name\>** (on-demand deep dive into a specific skill)
Certification Requirements
Each level includes all rules from the previous level. Priority tag `[P0]`=agent breaks without it, `[P1]`=agent works but poorly, `[P2]`=nice to have.
Level 1: Agent-Friendly (core -- 20 rules)
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 version
**Error** -- 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 versions
**Exit 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 stdout
**Composability** -- clean pipe semantics
- `[P0]` C1: stdout is for data ONLY
- `[P0]` C2: logs, progress, warnings go to stderr ONLY
**Input** -- fail fast on bad input
- `[P1]` I4: Missing required param -> structured error, never interactive prompt
- `[P1]` I5: Type mismatch -> exit 2 + structured error
**Safety** -- protect against agent mistakes
- `[P1]` S1: Destructive ops require `--yes` confirmation
- `[P1]` S4: Reject `../../` path traversal, control chars
**Guardrails** -- 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 (; | && $())
Level 2: Agent-Ready (+ recommended -- 59 rules)
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
Local, agent-owned skill stacks for coding agents—from complete catalog access to a reproducible, reviewable plan. Codex or Claude inspects your project and chooses exact skills from the complete local AAS catalog.
Other skills on agentic-awesome-skills.
- /00-andruia-consultant
Arquitecto de Soluciones Principal y Consultor Tecnológico de Andru.ia. Diagnostica y traza la hoja de ruta óptima para proyectos de IA en español.
Open skill - /007
Security audit, hardening, threat modeling (STRIDE/PASTA), Red/Blue Team, OWASP checks, code review, incident response, and infrastructure security for any project.
Open skill - /10-andruia-skill-smith
Ingeniero de Sistemas de Andru.ia. Diseña, redacta y despliega nuevas habilidades (skills) dentro del repositorio siguiendo el Estándar de Diamante.
Open skill - /20-andruia-niche-intelligence
Estratega de Inteligencia de Dominio de Andru.ia. Analiza el nicho específico de un proyecto para inyectar conocimientos, regulaciones y estándares únicos del sector. Actívalo tras definir el nicho.
Open skill - /2slides-ppt-generator
AI-powered presentation generation via the 2slides API — create slides from text, match a reference image style, summarize documents into decks, add AI voice narration, and export pages/audio. Use for any \"make slides\", \"create a deck\", or \"slides from this document\"
Open skill - /3d-web-experience
Expert in building 3D experiences for the web - Three.js, React
Open skill

