--- name: kai-brand-pulse description: Multi-platform brand intelligence pulse - collect cited public reputation evidence across web, news, YouTube, X, LinkedIn, Reddit, and review sites, then turn it into objection mining, content angles, competitor positioning, and surround-sound actions. Use when "brand monitor", "brand pulse", "what are people saying about us", "multi-platform reputation", "brand intelligence", "weekly brand monitoring", "objection mining", or "public reputation scan". --- # kai-brand-pulse - Multi-Platform Brand Intelligence > **Kai root note:** `knowledge/`, `harness/`, and `scripts/` paths in this skill live in the Kai install, not the user's project. Resolve them against the first ancestor directory of this SKILL.md that contains a `knowledge/` folder (the Kai plugin root, `~/.claude/kai`, or the kai-cmo-harness repo). `MARKETING.md`, `memory/`, and any output files live in the current project. If a referenced `scripts/` command is not available in this install, say so, skip it, and continue with the file-based guidance — never fabricate its output. Run a cited brand pulse across public reputation surfaces. This is the Kai-native version of the Brand Monitor Agent pattern: collect evidence first, analyze each platform separately, then synthesize into marketing actions. ## When to Use - You need a current public read on a brand, product, founder, or client. - You want objection mining for copy, sales, ads, social, or lifecycle messaging. - You need competitor positioning evidence before `/kai-brand`, `/kai-competitors`, or `/kai-surround-sound`. - You want weekly delta monitoring for new mentions, complaints, comparisons, and content opportunities. ## When Not to Use - You need a full marketing audit. Use `/kai-audit`. - You need technical SEO or agent-readiness checks only. Use `/kai-seo-audit` or `/kai-surround-sound`. - You do not have approval to collect or report on a sensitive individual. - You plan to publish claims without citations. Stop and collect source-backed evidence first. ## Command Shape ```bash /kai-brand-pulse [competitors] ``` Local runner: ```bash python scripts/intel/brand_pulse.py "" \ --domain "https://example.com" \ --category "category buyers ask about" \ --competitor "Competitor A" \ --competitor "Competitor B" \ --out "workspace/brand-pulse/-YYYY-MM-DD" ``` Optional: ```bash python scripts/intel/brand_pulse.py "" --skip-fetch python scripts/intel/brand_pulse.py "" --wiki-dir "" python scripts/intel/brand_pulse.py "" --json ``` Live search uses `SERPAPI_API_KEY` when present. Without it, the runner archives the query plan and writes data gaps instead of inventing findings. --- ## Phase 0: Context and Provenance 1. Read `MARKETING.md` if present. Pull brand name, domain, ICP, category, competitors, positioning, and voice constraints. 2. For client-facing or quantitative recommendations, load `harness/references/audit-data-provenance.md`. 3. If a domain is available, run the shared source collector before writing final claims: ```bash python -m kai.source_data.collect \ --url "https://example.com" \ --firm-name "" \ --workflow brand-pulse \ --mode sales_external \ --out "workspace/brand-pulse-data" ``` Use `sales_external`, `onboarding_connected`, or `internal_demo`. Cite collector sources for domain, schema, sitemap, or metric claims. Use `_data-gaps.md` for missing access. --- ## Phase 1: Collect Evidence Run the Brand Pulse runner. It creates a raw archive, platform packets, a synthesis shell, and a delta-tracking database. Default surfaces: | Surface | Collection Pattern | Why It Matters | |---------|--------------------|----------------| | Web | Brand, reviews, alternatives, pricing, own-domain entity queries | General entity footprint and objections | | News | Brand and category news queries | Authority, recency, PR angles | | YouTube | `site:youtube.com` search fallbacks | Reviews, demos, creator narratives | | X | `site:x.com` and `site:twitter.com` search fallbacks | Fast-moving complaints, praise, comparisons | | LinkedIn | `site:linkedin.com/posts` and company fallbacks | B2B proof, founder/category narratives | | Reddit | `site:reddit.com` search fallbacks | Raw objections and buying-language mining | | Review Sites | G2, Capterra, Trustpilot, Clutch, Yelp search fallbacks | Social proof, complaints, competitor context | The runner writes: ```text workspace/brand-pulse// ├── brand-pulse-data.json ├── _brand-pulse.md ├── _content-angles.md ├── _objection-mining.md ├── _surround-sound-actions.md ├── _monitoring-plan.md ├── _data-gaps.md ├── raw/ │ └── query-plan.json └── platforms/ ├── web.md ├── news.md ├── youtube.md ├── x.md ├── linkedin.md ├── reddit.md └── reviews.md ``` Every evidence item has a citation id. Do not make a claim unless it points to a citation id or a collector source id. --- ## Phase 2: Platform Analyzers Analyze one platform at a time before synthesis. Use the packet in `platforms/.md` as the only source material for that platform. For each platform, produce: | Analyzer Output | Questions | |-----------------|-----------| | Repeated claims | What does the market keep saying about the brand? | | Objections | What pain, doubt, pricing, trust, or support language repeats? | | Proof gaps | What proof do people need that the brand does not visibly supply? | | Competitor context | Which competitors appear beside the brand and why? | | Content angles | What can Kai write, publish, pitch, or test next? | | AEO actions | Which citations, pages, or entity signals should feed `/kai-surround-sound`? | Keep platform conclusions separate until all packets have been reviewed. This prevents one loud platform from swallowing quieter but useful evidence. --- ## Phase 3: Cross-Platform Synthesis After platform analysis, synthesize: 1. **Narrative map** - What the public web thinks the brand is, who it is for, and what doubts cluster around it. 2. **Objection bank** - Exact objection themes with cited examples. 3. **Competitor positioning** - Where competitors own attention, proof, or trust. 4. **Content angles** - Blog, comparison, social, email, ad, and sales enablement ideas tied to evidence. 5. **Surround-sound actions** - Third-party citation, directory, review, forum, and own-domain AEO moves. 6. **Monitoring deltas** - What is newly observed since the previous run. Do not blur "observed in search results" with "market share" or "sentiment share." Treat search output as a sampled evidence packet. --- ## Phase 4: Recommended Actions Turn findings into Kai work: | Finding | Next Kai Move | |---------|---------------| | Repeated pricing objection | `/kai-landing-page`, `/kai-write`, or sales FAQ refresh | | Repeated competitor comparison | `/kai-competitors` plus comparison page brief | | Reddit objections | `/kai-reddit-listen` profile keywords and reply guardrails | | Thin review-site footprint | Review request system, directory cleanup, or `/kai-surround-sound` | | Strong third-party praise | Repurpose into proof assets, ads, case studies, and AEO citations | | Missing own-domain entity clarity | `/kai-brand`, `/kai-seo-audit`, then `/kai-surround-sound` | For phone-led businesses, apply the KaiCalls Fit Rule. Recommend KaiCalls only when phone-capture evidence supports it, disclose Kai ownership, and compare alternatives. --- ## Phase 5: Weekly Delta Monitoring Run the same brand weekly. The local SQLite database at `data/intel/brand_pulse.db` tracks first-seen and last-seen mentions. Example cron: ```bash 0 8 * * 1 cd /path/to/kai-cmo-harness && python scripts/intel/brand_pulse.py "" --domain "https://example.com" --category "" --out "workspace/brand-pulse/-$(date +\%F)" ``` For Brain wiki ingestion, pass `--wiki-dir` to write a pointer page to the latest cited packet. Keep the full raw archive in the workspace. --- ## Quality Rules - Cite every client-facing claim with a citation id or source id. - Store raw search responses and query plan before synthesis. - Use `_data-gaps.md` for missing APIs, private platform access, or unavailable exports. - Never report review counts, rankings, traffic, share of voice, sentiment share, or platform volume unless the source directly provides them. - Label sampled search evidence as sampled search evidence. - Gate any publishable copy generated from the pulse with `/kai-gate`.