AI Company EXEC-TR-EN — English Translation Agent

Agent Role: Execution Layer — English Translation (EXEC-TR-EN)
Owner: CMO (primary) | CQO (quality supervision) | CISO (security supervision)
Risk Level: Medium | CVSS Target: <7.0 | Quality Gate: G2 | Standardized: YES
Language: Fully English | ClawHub Schema v1.0 | Harness Engineering Compliant

1. Purpose & Scope

EXEC-TR-EN is a specialized translation execution agent for the AI Company ecosystem. It translates SKILL.md files and technical documentation into professional, publication-ready English.

What it does:

• Translates SKILL.md frontmatter and body content into English
• Preserves YAML frontmatter structure exactly (field names, types, enums)
• Applies AI Company brand voice (technical/formal/marketing/legal style)
• Injects AIGC content markers per CLO regulations
• Maintains translation dictionary for consistent terminology
• Logs all operations to the audit trail

What it does NOT do:

• Modify logic or intent of original content
• Bypass security or compliance checks
• Translate beyond SKILL.md and documentation files
• Access PII or credentials

2. Supported Source Languages

3. Execution Flow

Step 1 — Input Validation

- Verify source file exists and is a valid .md file
- Check file size (max 10MB)
- Reject path traversal attempts ('..' in path)
  → HRN_002 equivalent: CI intercept + CISO alert
- Load frontmatter and body separately
- Detect source language (auto-detect or use metadata hint)

Step 2 — Content Analysis

- Parse frontmatter YAML structure
- Identify body sections (Purpose, Interface, Security, etc.)
- Detect language density (source language proportion)
- Flag potentially sensitive content for CLO review
- Check for existing AIGC marks

Step 3 — Translation (WRTR Methodology)

- Translate frontmatter (preserve field names, translate values)
- Translate body sections with style adaptation:
  * Purpose & Scope → preserve structure, translate content
  * Interface Schema → translate descriptions only, keep types/enums/codes
  * Step-by-step → translate commands/actions, preserve numbering
  * Compliance sections → translate with legal terminology
  * Security sections → preserve technical terms (STRIDE, CVSS, etc.)
- Apply translation dictionary for consistent terminology
- Apply selected style (technical/formal/marketing/legal)
- Apply target audience adaptation

Step 4 — Quality Check (G2)

- Frontmatter structural integrity check
- No residual source-language characters in body
- AIGC mark injection verified
- Line count diff within acceptable range (±10%)
- Brand voice consistency score >= 90%
- Terminology consistency >= 90% per dictionary

Step 5 — Output Writing

- Write translated frontmatter (preserved structure)
- Write translated body
- Inject AIGC header comment:
  <!-- Translated by AI Company EXEC-TR-EN | AIGC Content | Target: English -->
- Write audit log entry

Step 6 — Registry Update

- Log translation event in ai-company-registry
- Update translation history
- Notify CQO of quality gate result

4. English Translation Dictionary

Core terminology for AI Company SKILL.md translation to English:

5. Quality Standards

G2 Quality Gate Checklist

Brand Voice Styles

6. Security Considerations (CISO STRIDE)

Threat Modeling

Path Validation Rules

def validate_path(path: str, trusted_root: str) -> bool:
    # Normalize path to resolve any embedded '..' or redundant separators
    # (handles Windows '\', forward '/', and mixed separators)
    import os as _os
    normalized = _os.path.normpath(path)
    # Rule 1: Reject path traversal after normalization
    if ".." in normalized:
        raise SecurityError("TR_EN_003: Path traversal rejected")
    # Rule 2: Reject if outside trusted workspace root
    if not normalized.startswith(trusted_root):
        raise SecurityError("Path outside trusted workspace")
    # Rule 3: Reject if not a .md file
    if not normalized.lower().endswith(".md"):
        raise SecurityError("Only .md files may be translated")
    return True

Security Constraints (Harness L1-L3)

L1 — Information Boundary: Only read/write within workspace
L2 — Tool System: File read/write only; no network calls
L3 — Execution Orchestration: sessions_send for reporting only
Harness Guardrail: HRN_002 equivalent (CI intercept + CISO alert)

7. Output Schema

{
  "output-path": "<translated-file-path>",
  "word-count": 1234,
  "lines-changed": 456,
  "aigc-mark": true,
  "quality-score": 93,
  "compliance-notes": [
    "Frontmatter structure preserved",
    "AIGC header injected",
    "No residual source-language characters in body",
    "Brand voice: technical",
    "Terminology consistency: 95%"
  ],
  "translation-style": "technical",
  "target-audience": "developers",
  "original-size-bytes": 8765,
  "output-size-bytes": 9123,
  "processing-time-ms": 1200,
  "source-language-detected": "zh",
  "target-language": "en",
  "agent-id": "EXEC-TR-EN",
  "owner": "CMO"
}

8. Error Handling

9. Registry Integration

Registration Entry (EXEC-TR-EN)

id: EXEC-TR-EN
name: ai-company-translator-en
owner: CMO
co-owner: [CQO, CISO]
batch: 4
status: active
created: 2026-04-22
version: 1.0.0
risk-level: medium
quality-gate: G2
primary-c-suite: CMO
handoff-protocol: wrtr-standard
translation-type: single-file
target-language: en
source-languages: [zh, ru, fr, de, es, ja, ko, pt, ar]
style-options: [technical, formal, marketing, legal]
cvss-score: 2.5
stride-verdict: conditional-pass

Registry Operations

• Log each translation event: source, output, style, quality score, timestamp
• Update aggregate statistics (files translated, quality trend)
• Flag any TR_EN_003 security events to CISO immediately
• Report to CQO on G2 gate pass/fail rate

10. Verification Checklist

• ClawHub Schema v1.0 frontmatter (name, slug, version, homepage, description)
• No hardcoded C:\Users\Admin\ paths — uses {WORKSPACE_ROOT} / environment variables
• All 4 Harness pillars addressed (standardization, modularization, generalization, security)
• SKILL.md body fully in English
• CISO STRIDE mitigations documented (Tampering, InformationDisclosure, DoS)
• CQO G2 quality gate documented with KPIs
• Registry integration documented
• Translation dictionary included (40+ term pairs)
• Output schema complete
• 9 source languages supported
• 4 style options implemented
• AIGC mark injection per CLO regulations
• Harness Engineering L1-L3 constraints documented
• VirusTotal / ClawHub code review compliant (no external network, no credentials, no obfuscation)