Done-for-you offer · Fractional CMO with AI Swarm · voice-attribute-extraction skill · Brand-consistency 8-skill cross-swarm
Completions builds voice-attribute extraction — 🎯 15th 5 -skill bundle on brand-spec + 🎯 Brand-consistency 8 -skill cross-swarm + 🎯 LLM-extract-from-corpus signature
You operate 50-1,500 locations × per-corpus per-attribute brand-voice corpus dependency. Per-corpus per-attribute voice extraction without governance fragments per-corpus per-attribute extraction + normalization + spec-emission. Completions builds the voice-attribute-extraction 5 -skill bundle on the brand-spec agent end-to-end. 🎯 15th 5-skill bundle on brand-spec (corpus-ingestion + LLM -attribute-extraction + attribute-normalization + spec -emission + attestation — brand-spec + governance-router co-lead 5-skill bundle host density at 15 each). 🎯 Brand -consistency 8-skill cross-swarm mechanic (densest cross -swarm coordination mechanic in catalog, exceeding 7 -skill cross-swarm density at #528). 🎯 LLM-extract-from -corpus signature (10th canonical 5-skill bundle topology — FIRST LLM-extract-from-corpus signature in catalog). You keep every artifact.
Published September 24, 2026
Frequently asked
What does "Completions builds voice-attribute extraction — 15th 5-skill bundle on brand-spec + Brand-consistency 8-skill cross-swarm + LLM-extract-from-corpus signature" actually deliver?
Completions builds and operates per-corpus per-attribute corpus-ingestion + LLM-attribute-extraction + attribute-normalization + spec-emission + attestation across the brand-spec agent. Per-corpus per-attribute corpus-ingestion (skill 1) ingests per-corpus per-attribute brand-voice corpus across 50-1,500 locations × per-corpus per-attribute 12+ corpus-types (per-corpus per-attribute existing-website-copy + per-corpus per-attribute existing-email-copy + per-corpus per-attribute existing-social-copy + per-corpus per-attribute existing-ad-copy + per-corpus per-attribute existing-blog-copy + per-corpus per-attribute existing-podcast-transcript + per-corpus per-attribute existing-video-transcript + per-corpus per-attribute customer-interview-transcript + per-corpus per-attribute founder-interview-transcript + per-corpus per-attribute executive-keynote-transcript + per-corpus per-attribute customer-review-text + per-corpus per-attribute press-release-text). Per-corpus per-attribute LLM-attribute-extraction (skill 2 — LLM-EXTRACT-FROM-CORPUS SIGNATURE) uses per-corpus per-attribute LLM-prompt-chain to extract per-corpus per-attribute voice-attribute (per-corpus per-attribute tone-attribute + per-corpus per-attribute formality-attribute + per-corpus per-attribute energy-attribute + per-corpus per-attribute sentence-cadence-attribute + per-corpus per-attribute vocabulary-density-attribute + per-corpus per-attribute jargon-density-attribute + per-corpus per-attribute emoji-density-attribute + per-corpus per-attribute em-dash-density-attribute + per-corpus per-attribute contraction-density-attribute + per-corpus per-attribute second-person-density-attribute + per-corpus per-attribute imperative-mood-density-attribute + per-corpus per-attribute question-density-attribute + per-corpus per-attribute negation-density-attribute + per-corpus per-attribute hedging-density-attribute + per-corpus per-attribute repetition-pattern-attribute). Per-corpus per-attribute attribute-normalization (skill 3) normalizes per-corpus per-attribute raw-extraction-output into per-corpus per-attribute canonical-spec-format with per-corpus per-attribute attribute-weight + per-corpus per-attribute attribute-variance + per-corpus per-attribute attribute-evidence-citation + per-corpus per-attribute attribute-confidence-score. Per-corpus per-attribute spec-emission (skill 4) emits per-corpus per-attribute brand-voice-spec to the brand-spec master-record (synced with [[brand-spec-master-record]] from prior pillar arc). Per-corpus per-attribute attestation (skill 5) emits per-corpus per-attribute attestation-record with attestor-identity + attestation-timestamp + WORM-storage-attestation + chain-of-custody-record + per-vertical compliance overlay. 🎯 15th 5-skill bundle on brand-spec — extends prior 14 5-skill bundles on brand-spec by adding the 15th 5-skill bundle (corpus-ingestion + LLM-attribute-extraction + attribute-normalization + spec-emission + attestation) on the brand-spec agent; cumulative 5-skill bundle count on brand-spec reaches 15 with this skill; 15th 5-skill bundle on brand-spec ties brand-spec with governance-router at 15 5-skill bundles each (both behind creative-swarm at 14 actually — wait — creative-swarm is at 14, governance-router and brand-spec now tied at 15); brand-spec + governance-router co-lead 5-skill bundle host density at 15 each. 🎯 Brand-consistency 8-skill cross-swarm mechanic — extends prior Brand-consistency 7-skill cross-swarm mechanic (at #528) by adding 8-skill brand-consistency cross-swarm mechanic where 8 brand-consistency-bearing skills now coordinate across the brand-spec swarm (voice-attribute-extraction + brand-spec-master-record + brand-voice-gate + brand-consistency-feedback-loop + pre-publish-QC-loop + claims-allowlist + brand-spec-version-control + this skill consolidation); cumulative brand-consistency cross-swarm coordination at 8 skills with this addition; Brand-consistency 8-skill cross-swarm mechanic marks brand-consistency as the densest cross-swarm coordination mechanic in the catalog (exceeding 7-skill cross-swarm density at #528). 🎯 LLM-extract-from-corpus signature — extends prior 5-skill bundle topology signatures by adding the LLM-extract-from-corpus signature where 5-skill bundle composes as 1 corpus-ingestion stage feeding 1 LLM-prompt-chain extraction stage feeding 1 normalization stage feeding 1 spec-emission stage feeding 1 attestation stage; the FIRST LLM-extract-from-corpus signature in the catalog; marks LLM-extract-from-corpus signature as the 10th canonical 5-skill bundle topology in the catalog (after #527 + #529 established 8th + 9th). Per-corpus per-attribute compliance overlay (per-vertical CCPA + per-vertical GDPR + per-vertical LGPD + per-vertical FTC-endorsement + per-vertical CARU + per-vertical SEC-Reg-FD + per-vertical PII-redaction + per-vertical attorney-client-privileged-redaction). Operator team owns the per-corpus per-attribute corpus-ingestion + LLM-attribute-extraction + attribute-normalization + spec-emission + attestation registries + audit trail. Completions owns the swarm orchestration on the brand-spec agent.
Why does in-house voice-attribute extraction break at multi-corpus multi-attribute scale?
In-house operation fails on five axes: (1) per-corpus per-attribute corpus-ingestion across 12+ corpus-types requires data-engineering capacity unstaffable by internal teams; (2) per-corpus per-attribute LLM-attribute-extraction across 15 voice-attributes requires LLM-prompt-engineering capacity; (3) per-corpus per-attribute attribute-normalization with attribute-weight + variance + evidence-citation + confidence-score requires NLP-engineering capacity; (4) per-corpus per-attribute spec-emission into brand-spec master-record requires brand-spec-engineering capacity; (5) per-corpus per-attribute attestation with WORM-storage + chain-of-custody + 8-vertical compliance overlay requires audit-engineering capacity. 15th 5-skill bundle + Brand-consistency 8-skill cross-swarm + LLM-extract-from-corpus signature architecture coordination requires orchestration capacity at the cross-swarm tier. Completions absorbs all five axes under one Tier 3 Fractional CMO with AI Swarm engagement.
What does the engagement look like across Tier 1 to Tier 2 to Tier 3?
Tier 1 AI Readiness Assessment ($10k, 2-3 weeks, diagnostic): audits five axes. Tier 2 AI Swarm Setup Sprint ($25-50k, 4-8 weeks): builds 5-skill bundle on brand-spec agent — completing the 15th 5-skill bundle + Brand-consistency 8-skill cross-swarm + LLM-extract-from-corpus signature architecture. Tier 3 Fractional CMO with AI Swarm ($15-25k/month, 6-month minimum, 1-2 days/wk embedded): continues operating end-to-end + cross-agent swarm coordination.
Who owns the registries?
Operator owns 100% of every artifact: 5 registries (in operator data infrastructure), 5-skill bundle model code (operator-owned + operator-brand-engineering-team-aligned), per-vertical compliance overlay (rule library in operator repo with attorney-approved updates), brand-voice corpus library, LLM prompt chains, audit trail. Completions owns the orchestration knowledge.
What KPIs will Completions commit to on Tier 3 engagement?
Typical Tier 3 commitments: (1) per-corpus per-attribute corpus-ingestion coverage at 99-percent target across 12+ corpus-types; (2) per-corpus per-attribute LLM-attribute-extraction precision at 90-percent target across 15 voice-attributes; (3) per-corpus per-attribute attribute-normalization completeness at 99-percent target with attribute-weight + variance + evidence-citation + confidence-score; (4) per-corpus per-attribute spec-emission persistence at 100-percent target into brand-spec master-record; (5) per-corpus per-attribute attestation persistence at 100-percent target with WORM-storage; (6) Brand-consistency 8-skill cross-swarm coordination uptime at 99.5-percent target.
How does engagement end and what is the operator transition path?
Tier 3 engagements are 6-month minimum with 90-day notice. At engagement end, Completions transitions back to operator in-house in 30-60 days: operating-playbook hand-off + in-house staff training + 5 registries hand-off + 5-skill bundle model code hand-off + per-vertical compliance overlay rule library hand-off + brand-voice corpus library hand-off + LLM prompt chains hand-off + audit trail hand-off; Completions credentials revoke immediately.
Engage Completions
Start with the AI Readiness Assessment (Tier 1, 2-3 weeks, $10k). Hand off to Tier 2 ($25-50k, 4-8 weeks). Continue under Tier 3 Fractional CMO with AI Swarm ($15-25k/month, 6-month minimum, 1-2 days/wk embedded).