Adversarial Workflow Audit

SkillFiles & storage

Multi-pass adversarial quality audit for flat markdown workflow files. Combines structured evaluation (Agent A) with adversarial stress-testing (Agent B) to assess sequential clarity, prerequisite validation, HITL (Human-in-the-loop) safety gates, loop prevention, and formatting. Use when auditing workflow scripts (e.g., slash-commands like /bump-deploy), or when the user asks to review or improve operational playbooks.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Adversarial Workflow Audit skill

What this skill tells your AI

The instructions your AI receives, as published by neverinfamous/memory-journal-mcp in skills/adversarial-workflow-audit/SKILL.md and read by ahel’s review.

A multi-pass quality auditing system adapted specifically for manual markdown workflows. Unlike agent skills (which trigger automatically), workflows are manually invoked by users and execute sequentially. This audit ensures they are deterministic, safe, and robust.

When to Load

Load this skill when any of these apply:

  • Auditing an entire workflows directory for quality and safety.
  • Reviewing a new workflow before finalizing it.
  • The user asks for a workflow quality check or playbook review.
  • The user says "audit this workflow", "review this runbook", "check my playbook", or "review this slash command".

Adversarial Protocol

This skill follows the standard dual-agent adversarial pattern (Agent A: The Evaluator, Agent B: The Adversarial Tester). For the core pipeline rules, phase definitions, and agent switching protocols, read: ../adversarial-security/references/adversarial-base-protocol.md

Deep References

For the specific audit categories and rubric, read:

External Validation (Phase 4)

Phase 4 triggers an independent validation pass using the GitHub CLI (gh copilot). The copilot subcommand is built into modern gh CLI — no separate extension is needed. This provides a fundamentally different model's perspective on workflow quality, catching ambiguous steps and missing safety gates that internal review normalizes.

Prerequisites: gh CLI v2.x+ with gh auth status passing. If gh copilot is not available, skip Phase 4 gracefully and note the skip in the journal entry.

Read references/copilot-usage.md for critical non-interactive execution requirements.

Feedback Loop

Every phase creates a journal entry for future retrieval. Ensure the entry_type and tags map to the protocol table above.

Journal Opt-Out

See ../adversarial-security/references/journal-opt-out.md for instructions on how to handle explicit opt-outs from journaling.

Scripts

  • scripts/check-workflows.ps1: Gathers baseline structural metrics across a workflows directory.

Configuration

VariableDefaultDescription
MAX_AUDIT_PASSES2Maximum stress-test cycles (phases 2–3 repeat)
AUDIT_DEPTHstandardDepth: surface, standard, or thorough
COPILOT_VALIDATIONtrueEnable/disable Copilot extension validation phase

Audit Depth Profiles

  • Surface: Review structure, linear step numbering, and obvious prerequisites. Quick scan for workflow injection vectors.
  • Standard: Full audit with all review dimensions and Phase 2 stress testing. Default for most workflows.
  • Thorough: Full audit plus cross-workflow impact analysis, ecosystem comparisons, and rigorous infinite loop boundary testing.

Synergies

Skill/WorkflowRelationship
adversarial-plannerParent pattern; this skill adapts it for manual execution workflows.
/doc-auditAudits documentation repositories, but not specifically executable workflow steps.

Signals

GitHub stars
20
Forks
5
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
adversarial-workflow-audit
Source
github.com/neverinfamous/memory-journal-mcp