Research

Gives your OpenClaw agent persistent memory across every session. MEMORIA maintains a structured knowledge layer: who you are, what you're building, every decision made, every lesson learned, every project in flight. Your agent stops being a stranger and starts being a colleague who was there for everything. Zero cloud. Zero API keys. All memory lives in a single local markdown file you own and control forever.

Run an autoresearch-style growth loop for landing pages, onboarding, pricing, and experiment candidates. Collect or read analytics snapshots, preserve product truth, generate/critique/synthesize variants, blind-rank with Borda scoring, and output two review-ready A/B test variants. Works with any analytics data; best with Agent Analytics CLI/API.

Expert AI agent specializing in ux researcher. From The Agency (github.com/msitarzewski/agency-agents).

Transform rough drafts into publication-ready manuscripts following Nature, Science, and top-tier journal conventions. Supports both English and Chinese academic writing.

12-agent academic paper writing pipeline on Hermes Agent. 10 modes (full/plan/outline/revision/revision-coach/abstract/lit-review/format-convert/citation-check/disclosure). 6 paper types, 5 citation formats, bilingual abstracts, LaTeX/DOCX/PDF output. Uses delegate_task for each agent. Triggers: write paper, academic paper, guide my paper, parse reviews, AI disclosure, 寫論文, 學術論文, 引導我寫論文, 審查意見.

7-agent paper review system on Hermes Agent. 6 modes (full/re-review/quick/methodology-focus/guided/calibration). 5-panel review with editorial decision, revision roadmap, and calibration metrics. Uses delegate_task for each reviewer. Triggers: review paper, peer review, manuscript review, check revisions, calibrate reviewer, 審稿, 同儕審查, 論文審查.

Academic writing assistant for **research and learning purposes**: search academic sources, build evidence-based outlines, expand into fully cited essays (APA / MLA / Chicago), and improve writing style with local quantitative analysis.

Search codebases across repositories using Sourcegraph MCP integration — code search, commit history, diffs, symbol navigation, and DeepSearch. Use when a question spans many repositories and a Sourcegraph MCP server is configured.

Analyze a Zoom user interview — merges a VTT transcript with PM interview notes (markdown) to produce a complete research summary saved as a local markdown file. Use after a user research session when you have the transcript and notes; for ordinary meetings, use convert-meeting-notes.

Synthesize all captured observation data into a case study draft and a harness guide improvement plan. Invoke when the user runs /case-study-synthesize at build completion or at any milestone where a synthesis snapshot is useful.

Log a manual observation about the current session. Invoke when the user runs /case-study-capture to record something noteworthy that automatic hooks cannot detect -- a successful pattern, a human override, a context architecture insight, or friction the hooks missed.

When the user wants to analyze backlinks, audit link profile, or identify link issues. Also use when the user mentions "backlink analysis," "backlink audit," "referring domains," "toxic links," "link profile," or "disavow file."

When the user wants to improve E-E-A-T, add trust signals, or optimize for expertise and authority. Also use when the user mentions "E-E-A-T," "E-E-A-T signals," "experience expertise authority trust," "author bio," "YMYL," "trust signals," "expertise signals," "authority signals," "citations," "references," or "credibility."

When the user wants to analyze competitors for SEO, content, backlinks, or positioning. Also use when the user mentions "competitor analysis," "competitor research," "competitor keywords," "competitor backlinks," "link gap," "content gap," "competitor content," "competitive analysis," or "competitor comparison."

When the user wants to create, optimize, or validate URL slugs for content pages. Also use when the user mentions "URL slug," "URL path," "blog URL," "article URL," "short URL," "clean slug," "permalink," "slug optimization," "URL structure," "SEO-friendly URL," "create URL slug," or "SEO slug."

When the user wants to analyze Google Search Console data, use GSC API, or interpret search performance. Also use when the user mentions "GSC," "Search Console," "indexing report," "Core Web Vitals," "Enhancements," "Insights report," "search performance," "search queries," "search performance report," "URL inspection," "impressions," "CTR," "average position," "index coverage," "title tag," "meta description," "GSC data analysis," "Search Console API," or "searchanalytics.query."

Craft a high-quality prompt for a deep research agent (like ChatGPT Deep Research) through adaptive interviewing. Use when the user wants to research something but needs help formulating what to ask — when they say "I need to research X", "help me figure out what to ask about Y", "write a research prompt for Z", "I want to use deep research on...", or when they have a vague research need and want a precise, comprehensive prompt that will get excellent results from a research agent. Also use w...

Product analytics expert using PostHog MCP. Triggers on requests to understand user behavior, surface insights, create dashboards, analyze funnels, track metrics, set up experiments, or answer questions about product performance. Use when working with PostHog data, discussing analytics strategy, investigating user journeys, retention, conversion, feature adoption, or when asked to help understand what's happening in the product.

Synthesize outputs from multiple AI models into a comprehensive, verified assessment. Use when: (1) User pastes feedback/analysis from multiple LLMs (Claude, GPT, Gemini, etc.) about code or a project, (2) User wants to consolidate model outputs into a single reliable document, (3) User needs conflicting model claims resolved against actual source code. This skill verifies model claims against the codebase, resolves contradictions with evidence, and produces a more reliable assessment than an...

Conduct a thorough alignment interview to deeply understand a task before starting work. Use when starting any non-trivial task — take-home exercises, ambiguous problems, design challenges, complex implementations, research questions — anything where shared understanding matters more than speed. Triggers on phrases like "interview me", "let's align on this", "before we start", "kick off this task", "probe me on this", "I have a take-home", "help me think through", "I want to align before we b...

Conduct exhaustive, citation-rich research on any topic using all available tools: web search, browser automation, documentation APIs, and codebase exploration. Use when asked to "research X", "find out about Y", "investigate Z", "deep dive into...", "what's the current state of...", "compare options for...", "fact-check this...", or any request requiring comprehensive, accurate information from multiple sources. Prioritizes accuracy over speed, cross-references claims across sources, identif...

Identify non-obvious signals, hidden patterns, and clever correlations in datasets using investigative data analysis techniques. Use when analyzing social media exports, user data, behavioral datasets, or any structured data where deeper insights are desired. Pairs with personality-profiler for enhanced signal extraction. Triggers on requests like "what patterns do you see", "find hidden signals", "correlate these datasets", "what am I missing in this data", "analyze across datasets", "find n...

Interview-driven blog post drafting for technical product audiences. Use when user wants to write a blog post, article, or essay and needs help developing their thesis, structure, and initial draft. Triggers on "write a blog post", "draft an article", "help me write about X", "blog drafter", or when user has a topic they want to turn into written content. Conducts structured interviews using AskUserQuestion to extract the user's unique insights before generating drafts.

Remove AI-generated writing patterns from rebuttal prose to make it sound natural, direct, and authentically human-authored. Use when a Stage 2 refined draft or Stage 4 follow-up response reads too formulaic, robotic, or "GPT-like". Supports academic English.