product-messaging

name	product-messaging
version	2.1
last_updated	"2026-01-21T00:00:00.000Z"
author	marketing-team
description	Builds a 10-component messaging library from website and product research. Produces value propositions, key differentiators, taglines, CTA variants, and proof points organized into a messaging hierarchy. Triggers on "product messaging", "messaging library", "capabilities and benefits", "value props", or "messaging framework". Requires positioning as upstream input. Feeds into landing-page-copy, outreach-emails, sales-enablement, and linkedin-content. NOT for positioning strategy — use positioning instead.
goal	Builds a 10-component messaging library from website and product research.
outcome	Builds a 10-component messaging library from website and product research. Produces value propositions, key differentiators, taglines, CTA variants, and proof points organized into a messaging hierarchy. Triggers on "product messaging", "messaging library", "capabilities and benefits", "value...
primitive	product-marketing
sub_primitive	strategy
ontology_type	messaging
review_gate	2
inputs	{"required":[],"recommended":["positioning","icp-behavioural","competitor-research"]}
outputs	[{"type":"product-messaging-library","feeds_into":["website-copy","sales-enablement","linkedin-weekly-content","outreach-emails","product-launch"]}]
depends_on	[]
feeds_into	["website-copy","linkedin-weekly-content","outreach-emails","product-launch","sales-enablement"]
owned_by_agent	pmm
mcps_used	["gdrive","notion"]
push_targets	["gdrive","notion"]
triggers	{"slash_commands":[],"natural_language":[]}
status	draft
locked_by	null
locked_date	null
lock_version	null
sources_count	0
context	fork
effort	high

Product messaging

Builds a 10-component messaging library from website and product research. Output ships as the source of truth for all downstream marketing assets — landing pages, sales enablement, LinkedIn content, outreach. Knowledge type: messaging (per .claude/rules/ontology.md); maturity: emergent → validated after team review → canonical when locked. Visual phase map → references/process-flowchart.md.

When to run

Invoke when the user asks for: product messaging for [URL/company], messaging library for [product], extract messaging from [website], product messaging framework, capabilities and benefits for [company], what are [product]'s differentiators?, pain points and capabilities for [URL]. Do NOT invoke for: competitor analysis only (use /competitor-research), landing page copy directly (use /landing-page-copy — run this first), ICP research only (use /icp-behavioural), or single-feature questions (answer directly without full framework).

The Iron Law: no messaging output without source verification. Every claim cites URL + access date or is marked [Not available]. Every quote is verbatim. Every consequence chain traces 1st→2nd→3rd order. Full guardrails + red flags + anti-hallucination rules → references/quality-gates.md.

Inputs

Required:

• website URL — primary product website (verify it loads).
• product name — exact product/company name (confirm if ambiguous, e.g., "Bolt" could be ride-share, fintech, or bolt.new).

Recommended (improve quality):

• target ICP context — focuses messaging on relevant segments.
• competitor context — sharpens differentiators (use /competitor-research output if available).
• internal docs — provides claims not on website.
• customer quotes — fills gaps in testimonial coverage.

Upstream skill outputs (if available, read first):

• positioning (primary) — frames Description and core messaging blocks.
• icp-behavioural — enriches pain points and benefits with VoC data.
• competitor-research — sharpens status quo and differentiators.
• tov-guidelines — applies tone to messaging.

If website URL is missing, ask. If product name is ambiguous, confirm before starting.

Steps

1. Validate inputs → verify URL accessible, product name confirmed, ICP context confirmed if not obvious. Pull upstream skill outputs (positioning, icp-behavioural, competitor-research) into context if available.
2. Phase 1 — Discovery research → references/steps/phase-1-discovery.md. Fetch core pages (homepage, features, pricing, customers, about — 5+ pages with URLs + access dates). Search external data (G2, testimonials, vs-pages) per Exa protocol (.claude/rules/exa-protocol.md). Extract branded feature names verbatim before structured extraction begins. Detailed search/scraping patterns → references/extraction-patterns.md.
3. Phase 2 — Structured extraction → references/steps/phase-2-extraction.md. Extract all 10 components in order: Description → Status quo & alternatives → Pain points (with consequence chains) → Capabilities → Functional benefits → Emotional & social benefits → Features (branded names) → Cost of inaction → Common objections → Core messaging blocks. Frameworks + descriptor counts + link graph → references/frameworks.md.
4. Phase 3 — Verification & gaps → references/steps/phase-3-verification.md. Source-verify every claim (URL + access date), confirm verbatim quotes, assign confidence levels (High/Medium/Low → [VERIFIED]/[INFERRED]/[ESTIMATED]), document data gaps + recommendations as Component 10.
5. Apply attribution standards → per .claude/rules/ontology.md: [VERIFIED: source_type, reference], [INFERRED: from X + Y], [ESTIMATED: reasoning], [UNAVAILABLE]. Quality threshold for client-deliverable strategy outputs: ≥60% verified, ≤10% estimated.
6. Self-evaluate against quality gates → references/quality-gates.md. Run completeness, evidence-quality, and guardrail checks. Answer self-roast questions honestly.
7. Write to client folder per output template → references/output-template.md. File path: messaging/MMYY-messaging.md (or per client CLAUDE.md folder map). Header includes skill name, generated date, font (Inter), version.
8. Push to Notion (Product Messaging Database) and Google Docs (client_folder/strategy/) per push targets in frontmatter. For refresh runs, UPDATE existing pages rather than duplicating.
9. Offer iteration prompts post-delivery → references/iteration-prompts.md. If user signals approval ("great messaging" / quick approval), offer to save as a reference example under references/examples/{date}-{product-slug}.md.

What good looks like

References

• Output template → references/output-template.md — full markdown template covering all 10 components with source/confidence formatting, source appendix, and skill improvement notes.
• Frameworks + scoring rubric → references/frameworks.md — 10-component table, JTBD framing (optional Component 0), consequence chain framework with worked example, confidence scoring rubric, descriptor-count caps, component link graph (status quo → pain → capability → feature → benefit → quote).
• Quality gates → references/quality-gates.md — Iron Law, red flags, anti-hallucination guardrails (6 rules), anti-examples table, pre-delivery checklist, self-evaluation protocol with self-roast questions, gotchas (generic copy, missing hierarchy, tagline-first, unsourced proof, ignored status quo).
• Process flowchart (visual) → references/process-flowchart.md — ASCII flowchart of full execution path (input validation → discovery → extraction → verification → self-eval → review gate → chain suggestions).
• Per-phase walkthroughs → references/steps/phase-1-discovery.md, phase-2-extraction.md, phase-3-verification.md — full step-by-step for each phase including search patterns, extraction order, and checkpoints.
• Extraction patterns → references/extraction-patterns.md — search and scraping patterns per messaging component (homepage, features, pricing, testimonials, G2, comparison pages).
• Iteration prompts + skill auto-update + MCP integration → references/iteration-prompts.md — post-delivery refinement/expansion/quality offers, integration tables (feeds-into, receives-from), recommended workflow sequences, feedback signal table, reference-example capture format, pattern-detection rules, MCP data integration (Slack/Granola conditional pulls), changelog.

Examples

• Archive (social listening platform) → references/example-archive.md — full 10-component dossier; demonstrates consequence chain discipline (manual influencer discovery → missed UGC → competitive market-share loss).
• Linear (issue-tracking platform) → references/example-linear.md — demonstrates branded-feature-name discipline and pricing-page extraction.
• Notion (productivity platform) → references/example-notion.md — demonstrates emotional + social benefits extraction and audience-segmented core messaging blocks.

Evaluations (binary pass/fail before declaring "done")

• All 10 components present in correct order (or explicit [Not available] per component with reason).
• Status quo includes Manual/DIY + at least one named competitive alternative.
• Every pain point has a complete 1st→2nd→3rd order consequence chain (not cut short).
• Every pain point links forward to a capability; every capability links to a branded feature name.
• Every functional benefit includes a verbatim customer quote or explicit "Not available" with reason.
• Emotional + social benefits section complete: 2 emotional + 2 social.
• Cost of inaction section quantified (daily/weekly/monthly cost stated, not abstract).
• Common objections section complete (3-5 objections with root cause + Acknowledge/Reframe/Evidence response).
• Core messaging blocks complete: tagline ≤7 words, elevator pitch (1 sentence), 3-bullet value prop, proof point, audience-segmented messages.
• Every claim has source URL + access date; every quote verbatim; confidence level assigned (High/Medium/Low → [VERIFIED]/[INFERRED]/[ESTIMATED]).
• ≥60% [VERIFIED] confidence; ≤10% [ESTIMATED] (per ontology threshold for client deliverables).
• Data gaps section non-empty if any component is incomplete or low-confidence; recommendations provided for filling each gap.
• Source appendix lists ALL referenced URLs with access dates.
• Output title is # Product messaging library: [Product Name] exactly — no aliases.

Push

• Notion → Product Messaging Database (per-client). Refresh runs UPDATE the existing page (mcp__claude_ai_Notion__notion-update-page) — don't duplicate.

Integration map (feeds-into / receives-from / recommended chains) → references/iteration-prompts.md ("Integration with other skills").

Pre-slim original

Pre-slim SKILL.md (1,048 lines, v2.1) archived at .claude/skills/_archive/messaging/SKILL-pre-slim-20260429.md. See references/iteration-prompts.md ("Changelog") for the v2.2 entry documenting the slim.