linkedin-series
LinkedIn Content Series
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LinkedIn Content Series
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
LinkedIn Post
Initialize a working session. Loads full workspace context (personal info, business, strategy, current data, pipeline, key contacts, datastore index), runs CRM and sync health checks, surfaces what needs attention, and lists available skills with recommendations for the day. Use at the start of every working session. NEVER auto-trigger from natural language - this is an explicit "/prime" command only.
Parse documents (PDF, DOCX, PPTX, XLSX) with spatial bounding boxes via LiteParse. Answer questions with visual citations showing exact source locations on page images. Generate 31C-branded HTML/PDF reports. Maintains a parse cache for efficiency. Use when: "parse this document", "docparse", "visual citations", "show me where it says", "document analysis with citations", "parse with bounding boxes", "extract from this PDF". NOT for: plain text extraction without spatial data (use datastore-extract.py), email analysis (use /email-intel), web scraping (use /playwright or /firecrawl).
Market or regional intelligence brief for a sector or geography - TAM/sizing, competitive landscape, regulatory environment, entry timing, and 31C positioning, framed through the sovereign/DPI+ lens. Use for sector- or region-level analysis, not a single company. Trigger when the user says "market intel", "market for [sector]", "regional analysis", "sector overview", or "TAM for [sector]". Do NOT use for a specific named company (use /competitor-intel or /osint) or global geopolitical briefs (use /ceo-intel).
Structured sequential thinking engine for complex reasoning, multi-variable decisions, and strategy under uncertainty. Breaks problems into numbered thought steps with revision and branching support. Replaces the Sequential Thinking MCP server with visible, challengeable reasoning tailored to CEO decision-making. Engage this skill PROACTIVELY -- without waiting for the user to ask -- whenever a problem involves multi-variable decisions, contradictory signals, high-stakes reasoning, strategy under uncertainty, or when you catch yourself making unexamined assumptions. Use when the user says "think through this", "break this down", "reason through", "what are we missing", "think step by step", "structured thinking", "analyze this carefully", "help me think about", "deep think", or any request requiring deliberate multi-step reasoning before action. This is the thinking engine that precedes and sharpens every other skill.
Document-level STRUCTURAL editor for long deliverables. Reviews a draft's argument architecture -- section ordering, claim-to-evidence linkage, hierarchy, redundancy, buried lede, missing sections -- and proposes CUT / MERGE / MOVE / CONDENSE / SPLIT / ADD / PROMOTE / PRESERVE operations with word-savings estimates, BEFORE any sentence is touched. Content is sacrosanct: it reorganizes, it never argues with the ideas. Phase 2 hands all sentence-level work (rhythm, specificity, vocabulary) to the always-on humanization.md prose rule -- it never duplicates that. Use when the user says "editorial pass", "structural review", "review the structure of this", "tighten this document", "restructure this draft", or wants a long proposal / brief / report's argument arc checked. Do NOT use for: sentence-level prose / "make this sound human" (that is humanization.md), typo or grammar fixes (sanitize-text + humanization-check), fact-checking (/validate), artifact grading (/evaluate), short chat replies, or atomic /zk notes.
| name | linkedin-series |
| description | LinkedIn Content Series |
| argument-hint | [theme] |
| allowed-tools | Read |
| metadata | {"author":"Misha Hanin","email":"misha.hanin@odinix.com","version":"1.2"} |
| x-heading-orchestration | {"parallel_safe":true,"shared_state":[],"triggers":["linkedin series","content series","plan posts for the week","3 posts"]} |
| x-heading-capability | {"what":"A multi-post LinkedIn content series plan in Misha's voice around one theme - series overview, per-post angle/hook/proof-point/hashtags, the narrative arc, plus a ready-to-publish draft of Post 1.\n","how":"Run /linkedin-series [theme]. Keeps an append-only memlog at outputs/content/linkedin/[theme-slug]/.memlog.md so the plan survives across sessions.\n","when":"Use to plan several connected posts around a strategic moment. For a single standalone post use /linkedin-post.\n"} |
| x-heading-routing | {"category":"Content","triggers":["linkedin series","content series","plan posts for the week","3 posts"],"exclusions":["Single post -> /linkedin-post"],"compound":"Yes: Weekly Content (trigger)","router":"auto"} |
Plan a multi-post LinkedIn content series in Misha's voice around a theme or strategic moment.
theme: [Core theme or strategic narrative — e.g., "sovereignty vs. compliance", "the DPI category we're creating", "what MWC taught us"] posts: [Number of posts — default: 4] timeframe: [When to publish — e.g., "leading up to MWC", "during launch week", "over 4 weeks"] goal: [What this series should accomplish — e.g., "establish category leadership", "build investor intrigue", "Tribe culture signal"]
Before planning, read:
reference/misha-voice.md — Voice guide including LinkedIn sectiondatastore/content/linkedin-archive/old-archive/goal-is-a-cage.md — Voice and narrative examplecontext/strategy.md — Strategic priorities to align content withcontext/current-data.md — Current milestones and proof points to referenceProduce a content series plan with:
Series Overview:
For each post:
Series Arc:
After the plan, produce a ready-to-publish draft of Post 1.
A multi-post series is planned across turns. Keep an append-only working memory so the plan survives a context compaction and a later session can resume it.
outputs/content/linkedin/[theme-slug]/.memlog.md is absent, python "${CLAUDE_PLUGIN_ROOT}"/scripts/memlog.py init --workspace outputs/content/linkedin/[theme-slug] --field topic="[theme]" --field mode=series. If it already exists, do NOT re-run init — read it to resume, then append/set.python "${CLAUDE_PLUGIN_ROOT}"/scripts/memlog.py append --workspace outputs/content/linkedin/[theme-slug] --text "post 2 anchors on the MWC line-rate demo" --type decision.python "${CLAUDE_PLUGIN_ROOT}"/scripts/memlog.py set --workspace outputs/content/linkedin/[theme-slug] --key status --value complete.The .memlog.md file is gitignored; the series plan is the deliverable derived from it.