All Skills

Write a useful, author-consistent article and substantively improve it before verification.

Select one publishable SEO opportunity from verified Ahrefs evidence.

Decide whether an article deserves publication through hard checks and skeptical comparison.

Improve existing content and close the learning loop without cannibalizing new-content work.

Verify the article’s factual, product, citation, and link integrity before visual production.

Expand an annotated outline into full article prose using brand voice anchored in example articles, hitting the outline's per-section depth targets. Triggered after /product-mentions.

Create a structured H2/H3 outline with BLUF openers and MECE coverage, bound by the research dossier's beat spec. Triggered after /research and /brand-reference.

Render the cited draft as an HTML preview styled like the brand's blog so the writer can review the article in browser before publishing.

Gather keyword metrics, related terms, questions, full SERP benchmark, top-page extractions, and deep web research for a target keyword, then emit a beat spec the outline must satisfy. Triggered by /research <keyword> or as the first content stage of /blog-pipeline.

Test a pipeline stage's skill file by running the stage WITH and WITHOUT the skill on the same input, comparing outputs, and proposing skill edits. Ryan Law principle 3 — recursive self-improvement. Run after any board complaint about a stage, and monthly per core stage.

Lightweight ContentShake AI self-check the /draft stage can call before saving. Returns just SEO + Quality scores (no full optimization) so the writer knows whether the draft is in winning territory before /quality-check runs. Fails soft when SEMRUSH_API_KEY is unset.

Benchmark-relative quality gate. Scores the draft against the research dossier's beat spec (depth, consensus coverage, evidence) plus AI-tell and voice signals, runs an adversarial read armed with the SERP benchmark, and emits the verdict that gates the pipeline.

Find outdated stats and assertions in an extracted article. For each, check freshness and propose a replacement with a current source.

Find sources for every numerical claim in the draft, add inline hyperlinks, and add internal links to brand-reference articles. Triggered after /draft.

Render a side-by-side HTML diff of the original article vs the updated draft so the editor can review every change in browser.

Find existing articles on the brand's own blog covering the target keyword or related topics. Extract reusable modules, internal-linking opportunities, and product use cases to anchor the new article in the brand's existing voice.

Walk through the manual-capture.md checklist for a slug, driving Chrome via the Claude in Chrome MCP to capture each visual that needs more than a static URL — multi-step flows, conversation states, settings panels, age gates on third-party sites. Runs equally well locally (your desktop Chrome) or on a VPS with always-on Chrome + the extension installed. Defaults to unattended mode when `BLOG_AGENT_AUTONOMOUS=1` (which forces `UNATTENDED=1`). Use after /generate-visuals has flagged action-shot or failed-screenshot entries.

Layer 4 of the keyword research pipeline. Spawns a "skeptical SEO" adversarial sub-agent to argue against every survivor of Layers 1-3. Catches mechanical-classifier blind spots — wrong SERP intent, hidden link-graph gauntlets, AIO trajectory shifts, vanity-rank metrics. Same pattern as quality-check's adversarial draft read, applied to keyword selection.

Layer 0 of the keyword research pipeline. Builds a topic-graph snapshot for the brand's category before any seed work, approximated from Semrush phrase_related + phrase_questions on the category seeds plus the brand's own ranking footprint (domain_organic_unique). Idempotent on brand-config hash; never blocks the pipeline; cheap.

Set update priorities for an article before running detailed audits. Reviews extracted content and proposes which update audits to focus on (claims-stale, product-features-missing, topic-gaps).

Execute a relaunch on a decayed-but-valuable article (Lesson 5 audit + Lesson 8 "don't abandon old winners"). Take a page the audit flagged as decaying or rank-slipping, refresh it against the LIVE SERP (freshen data, re-verify searcher intent, squeeze new keywords, refresh visuals), bump its published date, and re-promote it as if brand new. The "update ~half the calendar" half of the strategy. Triggered from the audit's Relaunch plan.

Realize every typed [VISUAL:...] placeholder in the cited draft into an actual asset — Playwright screenshots of brand UI, Replicate-generated images (GPT Image 2 default, Nano Banana backup), matplotlib charts. Manual-capture flag for video/external/gif/adult-image. Updates the draft to reference local image paths.

Optimize the cited draft against Semrush ContentShake AI scores. Calls .claude/skills/optimize-content/scripts/contentshake_optimize.py for SEO + Quality scoring + recommendations, then judgment-rewrites the additions in brand voice. Iterates until both scores ≥ 8 or voice drift triggers a rollback. No Chrome MCP, no TipTap injection — pure API.

AI skill for building ApexCharts.js charts and data visualizations. Use when the user asks to create, configure, or troubleshoot any chart using ApexCharts (line, area, bar, pie, donut, radialBar, scatter, bubble, heatmap, candlestick, boxPlot, radar, polarArea, rangeBar, rangeArea, treemap). Covers correct data formats, lifecycle, formatters, tree-shaking, SSR, and framework integration. In React / Vue / Angular projects, prefer the framework wrapper packages (`react-apexcharts`, `vue3-apexcharts`, `ng-apexcharts`) over the core API.

Convert the cited draft into a Strapi-ready package — clean markdown body + Strapi-shaped JSON payload + a README with paste/publish instructions. Pushes directly to Strapi via API when STRAPI_API_TOKEN is set. With --auto-publish (or BLOG_AGENT_AUTO_PUBLISH=1), publishes the article live (publishedAt = now) instead of as draft.

Measure pleasur.ai's AI-citation share across ChatGPT / Perplexity / Gemini / Google AI Overviews for the tracked query list, using SemRush (data API for AIO-presence screening + AI Toolkit via browser for share-of-voice / mention + citation gaps) and direct engine queries. Scores each query into the GEO ledger and surfaces the highest-leverage gaps to fix. The GEO Lead's core measurement loop.

Craft Higgsfield-grade, hyper-structured image-generation prompts for every blog visual. MANDATORY before any image generation call (generate-visuals, Replicate, GPT-Image, Nano Banana). A weak one-line prompt is a gate failure — every [VISUAL] placeholder gets a full structured prompt built with this skill first.

Skeptical pushback on visual placement — both density and quality. Reads the annotated outline plus the visuals manifest and asks (a) whether the article hits the density target from editorial-principles-visuals.md, (b) whether each [VISUAL:...] earns its place, (c) whether sections without one would benefit. One revision pass on FAIL (BLOG_AGENT_VISUALS_REVISION_BUDGET, default 1).

Layer 1b of the keyword research pipeline. Finds keyword opportunities by comparing the brand's blog against competitors AND by expanding seeds + modifiers via Semrush (phrase_fullsearch / phrase_related). Auto-discovers competitors via domain_organic_organic when none are provided, derives the keyword gap via domain_domains, tags every row with `gap_mode`, and outputs a candidate-keyword CSV ready for downstream BID/AIO vetting.

Linkable-Asset Skill — data studies that pull links (Lesson 7)

Layer 6 of the keyword research pipeline. Organizes the vetted keyword queue into money clusters (from clusters.md), picks each cluster's keystone vs supporting articles, tracks coverage, and PROPOSES new clusters from high-business-value topics or live products not yet covered — so the blog strategy expands as the company grows. Emits cluster-tagged queue + cluster-map.md + cluster-proposals.md.

Layer 1d of the keyword research pipeline. Mines question-shaped keywords from Semrush phrase_questions (per surviving seed) plus People-Also-Ask strings from the SERP. Appends rows to keyword-ideas.csv with source=question_mining (or merges to source=both when the keyword already exists) and a question_subtype column. Cap of 100 rows per run.

Post-draft pass that expands a drafted article to capture the FULL keyword family — keywords the page already or could rank for, plus the Ahrefs Content Gap (keywords competitors rank for but we don't) — by weaving the worthwhile ones in as natural added paragraphs/sections. NOT keyword stuffing. Triggered after /draft, before /quality-check.

Knowledge base from "Contagious: Why Things Catch On" by Jonah Berger. Use when applying Berger's STEPPS framework for word of mouth, virality, social currency, triggers, emotion, social proof, practical value, and storytelling, studying the book, or referencing its concepts.

Off-page playbook (Lesson 9, link building). Mines our competitors' backlink profiles via Ahrefs to produce a VETTED link-prospect list — their "superfans" (sites linking to several of a competitor's best-by-links pages), their "power-linkers" (sites linking to multiple competitors but NOT to us), and their fresh new links — filtered for relevance and de-duped against sites that already link to us. The Link Intersect method, encoded. Output is a prospect queue for /outreach; it does NOT send anything.

After any AI-generated explanation, require the learner to identify one place it could be wrong, one thing to check, and one source to consult. Builds epistemic vigilance — treats AI output as a claim to evaluate, not truth to absorb.