Install
$ agentstack add skill-chaosrealmsai-agent-cli-spec-ai-native-cli ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ● Environment & secrets Used
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
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.
Core Philosophy
- Agent-only -- output is always JSON, no human-friendly mode
- Agent is untrusted -- validate all input at the same level as a public API
- Fail-Closed -- when validation logic itself errors, deny by default
- Verifiable -- every rule is written so it can be automatically checked
Layer Model
This spec now 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,feedback, inline context
Certification maps to layers:
- Agent-Friendly -- all
corerules pass - Agent-Ready -- all
core+recommendedrules pass - Agent-Native -- all layers pass
Output Mode
Output is always JSON. No human-friendly mode. No flags needed.
$ mycli list # JSON output, always
- All output is JSON to stdout. Period.
- No
--human, no--agent, no mode switching. - If a human needs to read it, pipe through
jq.
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 # MANDATORY auto-feedback behavior
└── skills/ # Extended capabilities (auto-registered)
└── getting-started.md
File Format
agent/brief.md — plain text, one paragraph. No frontmatter needed.
**agent/rules/.md* — each file MUST have YAML frontmatter:
---
name: trigger
description: When should an agent use this tool
---
(content here)
**agent/skills/.md* — each file MUST have YAML frontmatter:
---
name: getting-started
description: Quick start guide for new users
---
(content here)
The name field is the canonical identifier. The description field tells agents when/why to read this rule or skill.
writeback.md — The Feedback Reflex
The writeback.md rule is special. It MUST be written as a mandatory instruction, not a suggestion. The goal is to program a feedback reflex into every agent that reads it. Key requirements:
- Use imperative language: "You MUST file feedback", not "You can report issues"
- List explicit trigger conditions: when exactly should the agent file feedback
- Provide the exact command: copy-paste ready, with placeholders
- Rule: file first, explain second: agent files feedback before telling the user
- One issue per feedback: don't batch problems
- Include context: command, input, expected vs actual behavior
The description field should include "MANDATORY" to signal urgency:
description: MANDATORY — auto-report problems via feedback. Do not ask the user, just file it.
Auto-Registration
Drop a .md file into agent/rules/ or agent/skills/ and it is automatically registered. The CLI reads these directories at runtime. No code changes needed.
Progressive Disclosure — Agent Self-Learns by Using
The core design principle: an agent learns the tool by calling it. No external docs, no pre-configuration, no training data. One call → full understanding.
This works because every JSON response carries the tool's complete behavior contract inline. The agent reads rules[] once and knows how to use the tool. It sees skills[] and knows what deeper capabilities exist. It sees feedback and knows how to report problems. Zero setup, zero prior knowledge required.
Level 1: --brief (business card)
The smallest context. One paragraph. Gets injected into agent system prompts.
$ mycli --brief
mycli — task manager, add/list/show/done for local tasks
Source: agent/brief.md. Enough to know the tool exists and what it does.
Level 2: Every Command Response (self-teaching on first use)
EVERY command's JSON output MUST include three fixed fields. This is the key mechanism: the first time an agent calls ANY command, it receives the complete usage contract in the response. No separate learning step needed.
{
"result": { "id": 1, "title": "Buy milk", "status": "todo" },
"rules": [
{"name": "trigger", "content": "full content of trigger.md"},
{"name": "workflow", "content": "full content of workflow.md"},
{"name": "writeback", "content": "full content of writeback.md"}
],
"skills": [
{"name": "getting-started", "description": "Quick start guide", "command": "mycli skills getting-started"},
{"name": "batch-import", "description": "Import from CSV", "command": "mycli skills batch-import"}
],
"feedback": "Any problem, bad output, or confusion — run: mycli feedback create --type --message '...'"
}
- rules — full
.mdcontent inline, pushed on every call. Agent absorbs them
automatically. Contains: when to use this tool (trigger), how to use it step by step (workflow), how to report problems (writeback). After one call, the agent knows everything it needs.
- skills — name + description + command. Agent sees what's available and pulls
on demand when needed. Progressive: learns basics from rules first, goes deeper via skills only when the task requires it.
- feedback — one-line instruction, always present. Not optional, not an
escape hatch — it is the default error-handling behavior. When an agent encounters unexpected output, a confusing response, a bug, or has a feature need, it SHOULD immediately call feedback create without being asked. The feedback field teaches this reflex on every single response.
This forms a closed self-learning + self-healing loop: rules teach how → skills teach more → feedback auto-reports problems
Feedback is automatic, not manual. The agent sees the feedback instruction on every call. When something goes wrong, it doesn't ask the user what to do — it files feedback, stored in {PROJECT}/feedback/ as a git-tracked artifact. This means: problems get captured the moment they happen, in code, reviewable, never lost.
No external CLAUDE.md rules. No AGENTS.md configuration. No README reading. The tool teaches itself to every agent that calls it, and the agent teaches the tool what's broken.
Level 3: --help (full self-description)
Complete identity + capabilities. Only called for deep exploration.
{
"help": "mycli — full description from agent/brief.md",
"commands": [
{"name": "add", "description": "Create a new task"},
{"name": "list", "description": "List all tasks"},
{"name": "done", "description": "Mark task as done (destructive)"}
],
"rules": [
{"name": "trigger", "content": "..."},
{"name": "workflow", "content": "..."},
{"name": "writeback", "content": "..."}
],
"skills": [
{"name": "getting-started", "description": "Quick start guide", "command": "mycli skills getting-started"}
],
"feedback": "Any problem — run: mycli feedback create ..."
}
Level 4: skills (on-demand deep dive)
$ mycli skills getting-started
{
"name": "getting-started",
"content": "full content of getting-started.md",
"rules": [ ... same rules for context ... ]
}
Summary: Information Architecture
--brief → always in agent's prompt (via sync-agent)
every command → data + rules + skills list + feedback (always attached)
--help → brief + commands + rules + skills + feedback (first contact)
skills → full skill content + rules (on demand)
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--jsonflag needed[P0]O2: JSON MUST passjq .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-readablecode(e.g.MISSING_REQUIRED)[P0]E5: Error has human-readablemessage[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 (JSON result, buffered until complete)[P0]C2: logs, progress, warnings go to stderr ONLY[P1]C8: Progress MUST stream to stderr in real-time, not buffer until exit. For long-running operations, agent must see what's happening during execution, not just the final result.
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--yesconfirmation[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:--helpoutputs structured JSON withcommands[][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:--helpoutputs JSON with help, rules, skills, feedback, commands[P1]D15:--briefoutputsagent/brief.mdcontent[P1]D16: Output is always JSON, no human mode[P2]D2/D5/D6/D8/D10: per-command help, enums, defaults, output schema, version
Input — unambiguous calling convention
[P1]I1: All flags use--long-nameformat[P1]I2: No positional argument ambiguity[P2]I3/I6/I7: --json-input, boolean --no-X, array params
Error
[P1]E6: Error includessuggestionfield[P2]E2/E3: errors to stderr, error JSON valid
Safety
[P1]S8:--sanitizeflag 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 (--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 | |------|-----------|-------| | --brief | One-paragraph identity | For sync into agent config | | --help | Full self-description JSON | Brief + commands + rules + skills + feedback | | --version | Semver version string | | | --yes | Confirm destructive ops | Required for delete/destroy | | --dry-run | Preview without executing | | | --quiet | Suppress rules/skills/feedback from response, return result only. Saves tokens for agents that already learned the tool. | | | --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.mdexists[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 +skillssubcommand
Response Structure — inline context on every call
[P1]R1: Every response includesrules[](full content from agent/rules/)[P1]R2: Every response includesskills[](name + description + command)[P1]R3: Every response includesfeedback(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 feedback system, stored in project code
[P1]F1:feedbacksubcommand (create/list/show)[P1]F2: Structured submission with version/context/exit_code[P1]F3: Categories: bug / requirement / suggestion / bad-output[P1]F4: Feedback stored in project source ({PROJECT}/feedback/), committed to git[P1]F5:feedback list/feedback showqueryable[P2]F6: Feedback has status tracking (open/in-progress/resolved/closed)[P2]F7: Feedback JSON has all required fields (id, type, status, message, createdat, updatedat)[P2]F8: All feedback entries have status field
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
Error Format
{
"error": true,
"code": "AUTH_EXPIRED",
"message": "Access token expired 2 hours ago",
"suggestion": "Run 'mycli auth refresh' to get a new token"
}
Quick Implementation Checklist
Implement by layer — each phase gets you the next certification level.
Phase 1: Agent-Friendly (core)
- Default output is JSON — no
--jsonflag needed - Error handler:
{ error, code, message, suggestion }to stderr - Exit codes: 0 success, 2 param error, 1 general
- stdout = data only (buffered), stderr = logs/progress (real-time streamed)
- Missing param → structured error (never interactive)
--yesguard on destructive operations- Guardrails: reject secrets, path traversal, shell metacharacters
Phase 2: Agent-Ready (+ recommended)
--helpreturns structured JSON (help, commands[], rules[], skills[])--briefreads and outputsagent/brief.mdcontent- Reserved flags: --version, --dry-run, --quiet, --fields
- Exit codes: 20 not found, 30 conflict, 10 auth, 11 permission
Phase 3: Agent-Native (+ ecosystem)
- Create
agent/directory:brief.md,rules/trigger.md,rules/workflow.md,rules/writeback.md - Every command response appends: rules[] + skills[] + feedback
skillssubcommand: list all / show one with full contentfeedbacksubcommand (create/list/show/close/transition), stored in project source- AGENTS.md at project r
…
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: ChaosRealmsAI
- Source: ChaosRealmsAI/agent-cli-spec
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.