semantic-draft-writer

name

semantic-draft-writer

description

Write a full article draft from a semantic-SEO brief, following the micro-semantics writing rules and the brand's locked facts, then validate-and-repair it against the fabrication guard. Use whenever the user says "write the article", "draft from this brief", "turn this node into content", or asks to produce the actual copy for a topical-map node. Always runs scripts/validate_draft.py and repairs violations before returning. Triggers on drafting/writing intent for mapped content.

semantic-draft-writer

Turn a brief into publishable copy that is deep, specific, extractive, and — the part other tools skip — factually honest. "Passes the validator" is the floor, not the goal: the goal is a piece genuinely worth reading. The draft is done when it is fabrication-clean AND clears the quality bar (or its remaining gaps are explicitly surfaced).

Read first: ../../framework/semantic-writing-rules.md (especially the Craft & depth rules 22–28), ../../framework/macro-micro-semantics.md. Load the brief, the node, brands/<slug>/locked-facts.json, and entity-profile.json (for voice/audience).

Workflow

0. Scope depth and surface fact gaps FIRST. Before writing, list the concrete specifics a strong piece needs — real examples, named entities, figures, a point of view — and check them against locked-facts.json + the brief. If the piece can only be written generically because the facts aren't there, that is a signal to ask the user for the missing specifics (real customer result, actual feature names, a workflow detail) rather than writing vague filler. Thin facts are the #1 cause of thin drafts.

1. Front-matter first. Emit the required block (semantic-writing-rules.md): node_id, target_query, intent, entities_covered, internal_links, schema_type, locked_facts_used (start empty), sources (start empty).

2. Draft for a reader, section by section along the brief's contextual vector. Lead a section with the extractive answer (rules 3–4) THEN go deep: mechanism, a concrete example (rule 23), a trade-off, a real point of view (rule 26). Do not turn every H2 into a tiny Q&A (rule 27) — vary the shape. Declarative, specific, filler-free.

3. Honour the locks while writing:

   • State a brand fact ONLY if it exists in locked-facts.json; when you use one, add its key to locked_facts_used.
   • State an external factual number ONLY with a citation; add the URL to sources.
   • Where a figure would help but isn't grounded, write the honest version (mechanism/ range/"depends on…") — never invent one. Pull from the brief's do_not_fabricate.

4. Insert internal links from the brief with varied, descriptive anchors (internal-linking-rules.md).

5. Editorial self-critique pass (before the gates). Re-read the draft as a skeptical editor: Which section is thin? Where is there no example? What's the non-obvious point, and is it actually there? Cut every filler sentence. Rewrite the weakest section. Do this once before running the scorers — the gates confirm quality, they don't create it.

6. Three-gate loop — fabrication is a hard gate; quality is the target; AEO is a floor:

   # (a) HARD GATE — must be 0 high, or surface remaining violations
   python ../../scripts/validate_draft.py --draft <draft.md> \
     --locked brands/<slug>/locked-facts.json --brief brands/<slug>/briefs/<slug>.json \
     --brand-terms "<Brand>" --json
   # (b) QUALITY — the number to optimize (target >= 80)
   python ../../scripts/draft_quality.py --draft <draft.md> --floor <800+ per node type> --json
   # (c) AEO — a FLOOR to clear (target >= 80), NOT a number to maximize
   python ../../scripts/aeo_score.py --draft <draft.md> --schema-dir brands/<slug>/data/schema --json
   

   Repair in priority order: fabrication first (never fix a fabrication by inventing a source — tell the truth or cut the claim); then work the draft_quality.py fixes (deepen shallow sections, add the missing examples, cut filler, reach length through depth); then confirm AEO ≥ ~80. Do not sacrifice depth to push AEO past ~85 — a formulaic all-Q&A page is the failure mode this loop exists to prevent. Repeat ~2–4×.

7. Surface, don't hide. If violations or an unavoidable quality gap remain (e.g. the piece stays generic because a brand fact the user hasn't confirmed is missing), STOP and list them with the exact sentences and the specific facts you need — rather than shipping filler or faking a source. These usually map to _pending_owner_confirmation.

8. Emit brands/<slug>/drafts/<node-slug>.md; set node status: drafted.

Definition of done

• validate_draft.py: 0 high-severity violations (or remaining ones surfaced with rationale).
• draft_quality.py: >= 80 — every section has depth and a concrete example; filler is gone; length reached through substance. This is the bar the writer is judged on.
• aeo_score.py: >= 80 (floor cleared; not maximized at the cost of depth).
• Front-matter accurate; reads as a genuine expert with a point of view, not a padded FAQ.

Grounding ladder

• T0: research external facts via web_search (cite them); brand facts from locked ledger only.
• T1+: same rules; richer sourcing. Grounding tier never relaxes the fabrication guard — it only changes where legitimate numbers come from.