Plan Review Output Format

SkillAI & models

Output format specification for plan review agents. Defines the

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 Plan Review Output Format skill

What this skill tells your AI

The instructions your AI receives, as published by atomicinnovation/accelerator in skills/review/output-formats/plan-review-output-format/SKILL.md and read by ahel’s review.

JSON Schema

Return your analysis as a JSON code block. Do not include any text before or after the JSON block — the orchestrator will parse this output directly.

{
  "lens": "<lens-identifier>",
  "summary": "2-3 sentence assessment from this lens perspective.",
  "strengths": [
    "Positive observation about what the plan gets right from this lens perspective"
  ],
  "findings": [
    {
      "severity": "critical",
      "confidence": "high",
      "lens": "<lens-identifier>",
      "location": "Phase 2, Section 3: Database Migration",
      "title": "Brief finding title",
      "body": "🔴 **<Lens Name>**\n\n[Issue description — 1-2 sentences with enough context to understand standalone].\n\n**Impact**: [Why this matters — 1 sentence].\n\n**Suggestion**: [Concrete fix — 1-2 sentences]."
    }
  ]
}

Field Reference

  • lens: Agent lens identifier (e.g., "architecture", "security", "test-coverage", "code-quality", "standards", "usability", "performance", "documentation", "database", "correctness", "compatibility", "portability", "safety")
  • summary: 2-3 sentence assessment from this lens perspective. Reflect the key dimensions from the lens's Core Responsibilities. This is where holistic assessment lives, beyond individual findings.
  • strengths: Positive observations (fed into the review summary — never posted as individual findings)
  • findings: All findings, each referencing a location in the plan
    • severity: One of "critical", "major", "minor", "suggestion"
    • confidence: One of "high", "medium", "low"
    • lens: The lens identifier (same value as the top-level lens field). Included on each finding so the orchestrator can attribute findings after merging outputs from multiple agents.
    • location: Human-readable reference to the plan section where the finding is most relevant (e.g., "Phase 2: API Endpoints", "Implementation Approach", "Phase 1: Data Model")
    • title: Brief title for the finding (used in the summary index)
    • body: Self-contained finding body. See "Finding Body Format" below.

Severity Emoji Prefixes

Use these actual Unicode emoji characters at the start of each finding body:

  • 🔴 for "critical" severity
  • 🟡 for "major" severity
  • 🔵 for "minor" and "suggestion" severity

IMPORTANT: Use the actual Unicode emoji characters shown above (🔴 🟡 🔵), NOT text shortcodes like :red_circle:, :yellow_circle:, or :blue_circle:. The output is rendered as markdown, not Slack/Discord, so shortcodes will appear as literal text.

Finding Body Format

Each finding body should follow this structure:

[emoji] **[Lens Name]**

[Issue description — 1-2 sentences, standalone context].

**Impact**: [Why this matters].

**Suggestion**: [Concrete fix].

Example:

🔴 **Architecture**

The plan proposes a direct dependency from the API layer to the database schema
with no service abstraction. This couples the presentation layer to the data
model.

**Impact**: Database schema changes will ripple into the API layer, breaking
the dependency rule.

**Suggestion**: Introduce a service layer to mediate between the API handlers
and the data access layer.

Output only the JSON block — do not include additional prose, narrative analysis, or markdown outside the JSON code fence. The orchestrator parses your output as JSON.

Signals

GitHub stars
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Forks
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Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
plan-review-output-format
Source
github.com/atomicinnovation/accelerator