Ai Native Cli

---
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:

```bash
$ 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.md
```

### Step 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 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, version

**Input** -- 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 params

**Error**
- `[P1]` E6: Error includes `suggestion` field
- `[P2]` E2/E3: errors to stderr, error JSON valid

**Safety**
- `[P1]` S8: `--sanitize` flag for external input
- `[P2]` S2/S3/S5/S6/S7: default deny, --dry-run, no auto-update, destructive marking

**Exit Code**
- `[P1]` X1: 0 = success
- `[P2]` X2/X4-X8: 1=general, 10=auth, 11=permission, 20=not-found, 30=conflict

**Composability**
- `[P1]` C6: No interactive prompts in pipe mode
- `[P2]` C3/C4/C5/C7: pipe-friendly, --quiet, pipe chain, idempotency

**Naming** -- 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 semver

**Guardrails**
- `[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

#### Reserved Flags

| 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 |

### Level 3: Agent-Native (+ ecosystem -- 19 rules)

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` subcommand

**Response 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 changes

**Feedback** -- 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

## Examples

### Example 1: JSON Output (Agent Mode)

```bash
$ mycli list
{"result": [{"id": 1, "title": "Buy milk", "status": "todo"}], "rules": [...], "skills": [...], "issue": "..."}
```

### Example 2: Structured Error

```json
{
  "error": true,
  "code": "AUTH_EXPIRED",
  "message": "Access token expired 2 hours ago",
  "suggestion": "Run 'mycli auth refresh' to get a new token"
}
```

### Example 3: Exit Code Table

```
0   success         10  auth failed       20  resource not found
1   general error   11  permission denied 30  conflict/precondition
2   param/usage error
```

## Quick Implementation Checklist

Implement by layer -- each phase gets you the next certification level.

**Phase 1: Agent-Friendly (core)**
1. Default output is JSON -- no `--json` flag needed
2. Error handler: `{ error, code, message, suggestion }` to stderr
3. Exit codes: 0 success, 2 param error, 1 general
4. stdout = data only, stderr = logs only
5. Missing param -> structured error (never interactive)
6. `--yes` guard on destructive operations
7. Guardrails: reject secrets, path traversal, shell metacharacters

**Phase 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

## Best Practices

- Do: Default to JSON output so agents never need to add flags
- Do: Include `suggestion` field in every error response
- Do: Use the three-level certification model for incremental adoption
- Do: Keep `agent/brief.md` to one paragraph for token efficiency
- Don't: Enter interactive mode on errors -- always exit immediately
- Don't: Change JSON schema or error codes within the same version
- Don't: Put logs or progress info on stdout -- use stderr only
- Don't: Accept unknown flags silently -- reject with exit code 2

## Common Pitfalls

- **Problem:** 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

## Related Skills

- `@cli-best-practices` - General CLI design patterns (this skill focuses specifically on AI agent compatibility)

## Additional Resources

- [Agent CLI Spec Repository](https://github.com/ChaosRealmsAI/agent-cli-spec)

## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.