AGENT SKILL

agent-safety-governance

Safety and governance framework for autonomous AI agents. Validates agent actions before execution, enforces permission boundaries, detects dangerous patterns (file deletion, env modification, network calls), and maintains audit trails. Use before deploying autonomous agents or when reviewing agent-generated code.

License 许可
MIT
最近更新
2026-07-12
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01 前言 Front Matter

name
agent-safety-governance
risk
low
source
github/awesome-copilot
description
Safety and governance framework for autonomous AI agents. Validates agent actions before execution, enforces permission boundaries, detects dangerous patterns (file deletion, env modification, network calls), and maintains audit trails. Use before deploying autonomous agents or when reviewing agent-generated code.

03 SKILL.md 正文

Agent Safety & Governance Framework

Validate, constrain, and audit autonomous agent actions before they affect production systems. Based on the Agent Safety Reviewer and Devil's Advocate agents from github/awesome-copilot.

Core Principle

"An autonomous agent that can't be stopped is not an asset — it's a liability."

Safety governance answers: What can this agent do? What should it NOT do? Who reviews what it did?


Risk Classification

Action Risk Levels

Risk Level Examples Approval Required
🟢 LOW Read files, search codebase, generate code suggestions None — auto-execute
🟡 MEDIUM Write/edit files, install packages, run tests Log + continue
🟠 HIGH Delete files, modify config, commit/push Human review checkpoint
🔴 CRITICAL Drop database, modify secrets, external API calls with side effects Explicit confirmation + audit

Pre-Execution Checklist

Before any autonomous task, validate:

1. Scope Validation

✅ Does the task stay within the defined scope?
✅ Are the files to be modified listed in the task manifest?
✅ Is the agent working in the correct project directory?
✅ Is there a git checkpoint to rollback to?

2. Dangerous Pattern Detection

Scan planned actions for:

DANGEROUS_PATTERNS = [
    # File operations
    "rm -rf", "shutil.rmtree", "fs.rmSync", "os.remove",
    
    # Environment modification  
    ".env", "process.env", "os.environ", "secrets",
    
    # Network with side effects
    "POST /production", "DELETE /api", "PUT /prod",
    
    # Database
    "DROP TABLE", "DELETE FROM", "TRUNCATE",
    
    # Shell injection risks
    "subprocess.call", "exec(", "eval(", "shell=True",
    
    # Credential exposure
    "password", "api_key", "token", "secret" + "print|log|console"
]

If any pattern detected → PAUSE and require human review.

3. Resource Limits

agent_limits:
  max_files_modified: 20          # Per task
  max_file_size_kb: 500           # Max file to write
  max_test_iterations: 10         # TDD fix loops
  max_orchestration_depth: 5      # Nested sub-agents
  timeout_minutes: 30             # Hard stop
  allowed_directories:
    - "src/"
    - "tests/"
    - "docs/"
  forbidden_directories:
    - ".env*"
    - "*.secret"
    - "infra/"
    - ".ssh/"

Devil's Advocate Review

Before completing any significant change, apply adversarial review:

Questions to challenge the solution:

Correctness:

  • What happens if the input is null/empty/negative?
  • What's the worst-case performance (time + memory)?
  • Are all error paths handled?

Security:

  • Does this introduce any SQL injection vectors?
  • Could an attacker exploit this change?
  • Are secrets ever logged or exposed?

Reliability:

  • What happens if the database is down?
  • What if the external API returns 500?
  • Is this idempotent (safe to call twice)?

Maintainability:

  • Will the next developer understand this in 6 months?
  • Are the test names descriptive enough?
  • Is there hidden coupling?

Completeness:

  • Were any edge cases missed?
  • Are migrations backwards-compatible?
  • Is the documentation updated?

Audit Trail Format

Every agent action should be logged:

{"ts":"2026-02-23T14:30:00Z","agent":"gem-orchestrator","action":"write_file","path":"src/services/user.ts","risk":"medium","outcome":"success","lines_changed":47}
{"ts":"2026-02-23T14:30:15Z","agent":"polyglot-test-pipeline","action":"run_tests","framework":"jest","outcome":"8_pass_0_fail","coverage":"87%"}
{"ts":"2026-02-23T14:31:00Z","agent":"context-architect","action":"multi_file_change","files_affected":5,"risk":"high","human_reviewed":true,"outcome":"success"}

Log location: copilot-agent/audit-log.jsonl


Rollback Protocol

Automatic rollback triggers:

  • Test failure rate > 20% after agent changes
  • TypeScript/compile errors introduced
  • File deletion detected outside whitelist
  • Timeout exceeded

Rollback commands:

# Git rollback
git stash  # undo uncommitted changes
git reset --hard HEAD~1  # undo last commit

# PowerShell equivalent
git checkout -- .  # discard all unstaged changes

Checkpoint strategy:

Before starting:    git commit -m "checkpoint: pre-agent-task"
After each phase:   git commit -m "checkpoint: post-research-phase"
After completion:   git commit -m "feat: <description> [agent-assisted]"

Governance Checklist (for Agent Task Review)

Use this checklist when reviewing agent-proposed changes:

SCOPE
[ ] Changes are confined to listed files
[ ] No unauthorized external API calls
[ ] No credential or secret access

CODE QUALITY  
[ ] Tests written or updated
[ ] No obvious security vulnerabilities
[ ] Error handling present
[ ] No dead code introduced

SAFETY
[ ] No irreversible operations (unguarded deletes)
[ ] Rollback is possible at any point
[ ] Audit log entry created

COMPLETENESS
[ ] All acceptance criteria met
[ ] Documentation updated if public API changed
[ ] Migration scripts included if schema changed

Integration with Free JT7

  • Use with agent-orchestration to add safety gates between sub-agent calls
  • Apply Devil's Advocate review before context-multi-file commits
  • Combine with verification-before-completion for final checks
  • Log to copilot-agent/audit-log.jsonl (already used by Free JT7 agent system)

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