/digital-marketing-pro:client-validation-document — Part 5: The One True Stop

This skill produces the Part 5 deliverable: the Client Validation Document. It is the only point in the engagement where unbiased v1 findings are formally presented to the client for accept/reject/edit decisions.

Context efficiency

Heavy skill. Grep before Read any referenced file, then Read only matched ranges with offset + limit. List ${CLAUDE_PLUGIN_DATA}/<brand>/ before opening files. On re-invocation mid-session, skip files already in context.

This is the one true stop in the 12-Part flow. Nothing in Parts 6+ proceeds until this is signed off.

What this document is

The Client Validation Document compiles the most strategically consequential findings from Parts 2, 3, and 4 (the unbiased research and the four core documents) into a structured review document. For each finding:

• The finding itself
• Evidence / sources
• Proposed implication if accepted
• Three response options for the client: ACCEPT / REJECT / EDIT / DEFER
• (For REJECT or EDIT) — the client provides their corrected version and the rationale

The client's responses then feed the Decision Matrix in Part 6 to determine which v2 re-runs are needed.

What this document is NOT

• Not a Growth Plan. This is research findings, not strategic recommendations dressed up. The Growth Plan is Part 8.
• Not exhaustive. It includes only findings that have material strategic implications. Detail belongs in the source documents.
• Not a slide deck. It is a written document the client reads carefully and responds to. Slides do not capture the rigor required.
• Not optional. Every engagement runs Part 5. No shortcut to Part 6 without it.

Pre-conditions

Before running this skill:

1. Parts 2, 3, 4 must be completed (or substantially complete with explicit acknowledgment that some research continues)
2. The engagement state file _engagement.json must show Parts 3 and 4 as completed
3. The Living Project Instruction File should be up to date with the v1 strategic facts

If pre-conditions fail, do NOT produce output. Instruct the user on what is missing.

Document Structure

The Client Validation Document is organised by category of finding. Each category has 3–8 findings; total document is typically 12–25 findings across categories.

Section 1: Executive Briefing

Length: 1 page.

Content:

• Purpose of this document
• How to read it (the ACCEPT / REJECT / EDIT / DEFER framework)
• What happens after the client responds (Part 6 v2 re-runs governed by the Decision Matrix)
• Decision deadline (typically 7–14 days)

Section 2: Findings — by category

Each category contains its findings as structured blocks. Categories:

#### A. Business & SBU Findings (from 3.1)

Findings about the business reality — SBU separation, unit economics, value chain, growth levers, constraints, risks. Typically 3–5 findings.

#### B. Audience & Segmentation Findings (from 3.2 + 4.3)

Findings about target groups, persona priority, decision-making units, MQL/SQL definitions. Typically 3–5 findings.

#### C. Positioning & Communications Findings (from 3.3)

The chosen positioning, messaging pillars, tone-of-voice, don't-say rules, sensitive-topic handling. Typically 3–5 findings.

#### D. Channel & Budget Findings (from 3.4)

Channel selections, in-market vs out-market split, budget allocation, channel sequencing. Typically 2–4 findings.

#### E. Competitive Findings (from 4.1 + 4.2)

Competitor list, competitive positioning, Three-Question outputs (do well / do poorly / not doing). Typically 2–4 findings.

#### F. Market & Customer Findings (from 4.3 + 4.4)

Market sizing, customer behaviour patterns, demand signals. Typically 2–4 findings.

Section 3: Open Questions

Questions that the unbiased research could not resolve and need client input. The client provides answers here.

Section 4: Response Mechanism

How the client returns their responses (typically a structured response file or a meeting walkthrough).

Finding Block Format

Each finding follows this exact structure:

### Finding {ID}: {Short title}

**Category:** {A/B/C/D/E/F}
**Source:** {Document and step references — e.g., "3.1 Step 4, 4.1 Three-Question Output"}
**Materiality:** {High / Medium / Low}

**Finding:**
{2–4 sentences stating the finding from the unbiased research}

**Evidence:**
- {Cited source 1 with specific data point}
- {Cited source 2}
- {Cited source 3}

**Proposed implication if accepted:**
{1–3 sentences on what this means for the strategy if the client accepts}

**Client response:**

- [ ] ACCEPT — finding is correct as stated
- [ ] REJECT — finding is wrong; correction below
- [ ] EDIT — finding is partially correct; amended version below
- [ ] DEFER — needs further investigation; reason below

**If REJECT or EDIT, client correction:**
{Client fills in: what the correct finding is, with their evidence}

**If DEFER, reason and follow-up plan:**
{Client fills in: what additional research / data is needed, who is accountable, deadline}

Materiality Classification

Each finding gets a Materiality rating that indicates how consequential the response is:

• High — accepting vs rejecting would meaningfully change the channel mix, budget, positioning, or audience priority. Triggers v2 re-runs per Decision Matrix.
• Medium — accepting vs rejecting would change tactical execution but not strategic direction. May or may not trigger re-runs.
• Low — accepting vs rejecting changes phrasing or examples but not substance. No re-run triggered.

The client should focus most attention on High materiality findings; Medium and Low are still presented for completeness.

Response Categorisation for the Decision Matrix

After the client provides responses, the responses are categorised into Decision Matrix triggers:

The skill compiles the trigger list and runs:

python ${CLAUDE_PLUGIN_ROOT}/scripts/engagement-state.py decision-matrix \
  --brand {slug} --id {id} \
  --triggers "{comma-separated-trigger-list}"

The output then feeds the Part 6 v2 re-run plan.

Production Steps

1. Verify pre-conditions — Parts 2, 3, 4 completed.

1. Read the v1 source documents:

• part-03-four-core-documents/v1/3.1-business-and-sbu-analysis.md
• part-03-four-core-documents/v1/3.2-segmentation-framework.md
• part-03-four-core-documents/v1/3.3-brand-positioning-and-communications.md
• part-03-four-core-documents/v1/3.4-dmflow.md
• part-04-competitive-customer-market/v1/4.1-competitor-ad-analysis.md
• part-04-competitive-customer-market/v1/4.2-competitor-positioning.md
• part-04-competitive-customer-market/v1/4.3-customer-analysis.md
• part-04-competitive-customer-market/v1/4.4-market-analysis.md

1. Extract material findings. For each source document, identify the 2–5 most strategically consequential findings. Materiality rating: prefer High and Medium; include Low only if the client specifically benefits from confirming.

1. Synthesise findings into the structured format. Use plain client-facing language, not internal jargon. Each finding stands alone — do not require the client to read the source documents.

1. Add Open Questions section drawn from the "Open questions" sections of each source document.

1. Add response mechanism section — instruct the client how to return responses (recommended: produce a paired client-validation-responses.json file alongside the document).

1. Save the document to:

   engagements/{id}/part-05-client-validation/client-validation-document.md

1. Generate the response template:

   engagements/{id}/part-05-client-validation/client-validation-responses.template.json

Containing one entry per finding with empty decision/correction fields.

1. Mark Part 5 as `awaiting_input` in _engagement.json (not completed — Part 5 is only complete when the client responses are recorded).

1. Brief the user on the document, the response mechanism, and the typical 7–14 day decision window.

Recording Client Responses

When the client returns responses (filled-in JSON file or verbal walkthrough captured in a meeting):

1. Save the populated response file to:

   engagements/{id}/part-05-client-validation/client-validation-responses.json

1. Run engagement-state.py decision-matrix --validation-file <path> to determine the v2 re-run plan.

1. Mark Part 5 as completed.

1. Advance to Part 6 (v2 re-runs).

Quality Discipline

1. Plain client language. No "MQL/SQL pipeline funnel architecture" jargon. Translate to "the way leads move from interested to ready-to-buy."
2. Each finding stands alone. Client should not need to consult the source docs to understand the finding.
3. Evidence is cited explicitly. Vague claims ("market data shows...") are unacceptable. Cite the specific source with the data point.
4. Materiality is honest. Don't downgrade an uncomfortable finding to "Low" to make it easier to accept.
5. Open Questions are real questions. Don't fabricate questions for the sake of having an Open Questions section.
6. The response mechanism is structured. Free-form client emails are hard to translate into Decision Matrix triggers; the JSON response template makes the pattern unambiguous.

Examples

Example 1: Producing the document

User: We've completed Parts 2, 3, 4 for Acme. Time to prepare the Client Validation Document.

Skill response:
1. Verify pre-conditions ✓
2. Pull findings from the 8 source documents (4 from Part 3 + 4 from Part 4) using grep first to locate each category's section, then targeted Read with offset+limit — avoid bulk-Read on all 8 files up front or you'll blow the per-skill 5K-token budget
3. Extract 18 material findings across categories A–F:
   - 4 in Business & SBU
   - 3 in Audience & Segmentation
   - 4 in Positioning & Communications
   - 3 in Channel & Budget
   - 2 in Competitive
   - 2 in Market & Customer
4. 12 are High materiality, 5 Medium, 1 Low
5. 4 Open Questions identified from source docs
6. Save document at engagements/2026-q2/part-05-client-validation/client-validation-document.md (~22 pages)
7. Save response template at engagements/2026-q2/part-05-client-validation/client-validation-responses.template.json
8. Mark Part 5 as awaiting_input
9. Brief: "Document ready. 18 findings, 4 open questions. Recommend client meeting in 5–7 days for live walk-through, with responses returned within 2 weeks."

Example 2: Recording client responses

User: Acme client returned responses. They accepted most but rejected the positioning finding (they want to keep their existing positioning) and added 2 new competitors we missed.

Skill response:
1. Read the populated client-validation-responses.json
2. Categorise responses: 16 ACCEPT, 1 REJECT (positioning), 1 EDIT (competitor list)
3. Determine triggers: positioning_changed + competitors_changed
4. Run engagement-state.py decision-matrix --triggers "positioning_changed,competitors_changed"
5. Output: triggered re-runs = 3.1, 3.2, 3.3, 3.4, 4.1, 4.2 (the union of both triggers' re-run sets)
6. Estimate cost: ~85K tokens
7. Mark Part 5 completed
8. Brief: "Part 5 closed. 6 v2 re-runs triggered. Recommend reviewing the re-run plan and approving before invoking four-core-documents and competitor-analysis with view=v2."

Related skills

• engagement-workflow — orchestrates the 12-Part flow
• four-core-documents — produced the v1 docs being validated; will produce v2 re-runs after Part 5
• Existing competitor-analysis, audience-intelligence, market-intelligence skills produced the Part 4 docs

Related references

• engagement-flow-methodology.md — Part 5 in context
• decision-matrix-rerun.md — how responses translate to re-runs
• two-views-model.md — v1 + v2 architecture
• stone-vs-opinion.md — confidence tagging context