ai-native-cli — Стандартизированные CLI для безопасного взаимодействия с ИИ

--- 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)