Draft Reviewer

SKILL: draft-reviewer

Purpose

Build and maintain the review node (Stage 4). Review validates draft quality and optionally applies inline fixes. Uses slim payload — only draft text + gate errors + user request.

When to Use

• Building or modifying the review node
• Tuning the review prompt or skip conditions
• Debugging review output quality
• Changing review model assignment

Architecture Context (v5.1 — what's running)

Review runs after 4 deterministic gates. It receives a slim payload (~3.5K tokens) and performs structured validation + optional inline fix.

Stage 3 gates (evidence_anchoring -> lkb_compliance -> postprocess -> citation_validator)
  -> REVIEW (slim payload: draft text + gate errors + user request)
  -> Phase 1: 7 conditional checks
  -> Phase 2: inline fix (if blocking issues found)
  -> END

Skip Review

Set DRAFTING_SKIP_REVIEW=True in .env to bypass review entirely (for speed testing).

Model

• glm-5:cloud with reasoning=ON, temperature=0.3
• ~40-70s when triggered
• Fallback: glm-4.6:cloud -> OpenAI (REVIEW_LLM_MODEL)

Slim Payload (what review receives)

Review receives ONLY:

• Draft text (~3K tokens) — plain text extracted from draft.draft_artifacts[0].text
• Gate errors summary (~200 tokens) — compact, from _build_gate_errors_summary()
• User request (~200 tokens) — for fact fabrication check
• doc_type + law_domain (~10 tokens)

Total: ~3.5K tokens (was ~15K before pruning)

NOT sent: RAG chunks, court fee context, legal research context, cited chunk IDs. Gates already verified all of that deterministically.

Review User Prompt

Review the generated draft for legal correctness and filing readiness.

USER_REQUEST:
{user_request}

DOC_TYPE: {doc_type}
LAW_DOMAIN: {law_domain}

GATE ERRORS (from deterministic validation gates — already verified):
{gate_errors}

DRAFT TEXT:
{draft_text}

Gate Errors Summary Builder

_build_gate_errors_summary(state) collects errors from 3 sources:

1. evidence_anchoring_issues — fact tracing issues
2. postprocess_issues — formatting + LKB compliance issues
3. citation_issues — provision verification issues

If no issues: returns "No gate errors — all deterministic checks passed."

Review System Prompt (7 conditional checks)

The review system prompt (prompts/review.py) includes:

1. Factual accuracy (every claim traces to intake)
2. Legal theory validity
3. Citation correctness
4. Procedural compliance
5. Section completeness
6. Relief completeness
7. Cross-section consistency

Output: structured JSON with review_pass, blocking_issues, non_blocking_issues, final_artifacts

Inline Fix (Phase 2)

When DRAFTING_REVIEW_INLINE_FIX=True (default), review generates a corrected final_artifacts[] alongside blocking_issues[]. This eliminates the separate pass-2 LLM call.

After inline fix, _fix_and_or() is applied (deterministic cleanup since LLM may reintroduce anti-patterns).

Routing After Review

def _route_after_review(result, review_count, state, elapsed, inline_fix_enabled):
    # Priority:
    # 1. No legal blocking issues -> END (promote pass-1)
    # 2. Legal issues + inline fix -> END (use corrected artifacts)
    # 3. Legal issues + no fix + within cycles -> draft_freetext (pass-2)
    # 4. Max cycles exceeded -> END regardless

• severity="legal" — wrong citation, missing section, wrong limitation
• severity="formatting" — numbering, heading style, annexure labels
• Formatting-only issues -> END (no pass-2 needed)

Key Files

Settings

DRAFTING_MAX_REVIEW_CYCLES: int = 1
DRAFTING_REVIEW_INLINE_FIX: bool = True
DRAFTING_SKIP_REVIEW: bool = False
OLLAMA_REVIEW_MODEL: str = "glm-5:cloud"
OLLAMA_REVIEW_TEMPERATURE: float = 0.3
OLLAMA_REVIEW_REASONING: bool = True
REVIEW_LLM_MODEL: Optional[str] = None  # OpenAI fallback
REVIEW_REASONING_EFFORT: Optional[str] = "medium"

Retry Strategy (3 attempts)

1. Attempt 1 — structured output via with_structured_output(ReviewNode)
2. Attempt 2 — structured output with retry suffix prompt
3. Attempt 3 — raw model call + extract_json_from_text() parsing

All 3 fail -> fallback result with review_pass=False + error logged, pipeline continues.

Rules

• Review receives ONLY slim payload — never full RAG/court_fee/legal_research
• Max 1 review cycle (setting: DRAFTING_MAX_REVIEW_CYCLES)
• Inline fix preferred over pass-2 re-draft (saves 1 LLM call)
• Gate errors provided to review to avoid duplicate flagging
• Token usage logged for cost tracking

Anti-Patterns

• Do NOT dump RAG chunks, court fee, or legal research into review prompt
• Do NOT send full JSON artifacts — extract plain text only
• Do NOT let review duplicate gate findings (gate report provided)
• Do NOT accept vague issues like "improve the facts section"
• Do NOT flag placeholder usage as an issue
• Do NOT block pipeline if review fails — deliver with gates-only quality