linkedin-skills
Use when someone wants to grow an organic LinkedIn presence — a content strategy for a career change or consulting or thought leadership, a rewritten profile or headline, post drafts and hooks, a posting cadence or newsletter plan, connection notes and outreach, a commenting strategy, repurposing an article or talk into posts, or a read on why their reach dropped. Triggers on "grow my LinkedIn", "fix my headline", "write a LinkedIn post", "what should I post about", "LinkedIn strategy", "connection request", "my reach dropped". Forks context to route to one of five sub-skills, and refuses automation, scraping, pods, and bulk DMs before any drafting starts.
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- MIT
- 最近更新
- 2026-10-28
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01 前言 Front Matter
- name
- linkedin-skills
- context
- fork
- license
- MIT
- metadata
- { "author": "Alireza Rezvani", "updated": 1787616000000, "version": "1.0.0", "category": "marketing", "build_pattern": "Domain orchestrator — deterministic lane router + policy gate, five managed sub-skills", "distinct_from": "marketing-skill/x-twitter-growth (X/Twitter-specific); marketing-skill/social-content (multi-platform calendars); marketing-skill/social-media-analyzer (cross-platform reporting); productivity/andreessen (venture judgement, not audience building)" }
- description
- Use when someone wants to grow an organic LinkedIn presence — a content strategy for a career change or consulting or thought leadership, a rewritten profile or headline, post drafts and hooks, a posting cadence or newsletter plan, connection notes and outreach, a commenting strategy, repurposing an article or talk into posts, or a read on why their reach dropped. Triggers on "grow my LinkedIn", "fix my headline", "write a LinkedIn post", "what should I post about", "LinkedIn strategy", "connection request", "my reach dropped". Forks context to route to one of five sub-skills, and refuses automation, scraping, pods, and bulk DMs before any drafting starts.
02 资源文件 5
- 资产文件assets/linkedin_operating_agreement.md3.3 KB
- 参考文档references/linkedin_platform_canon.md7.8 KB
- 参考文档references/policy_and_account_safety.md7.7 KB
- 脚本scripts/linkedin_goal_router.py8.1 KB
- 脚本scripts/linkedin_policy_gate.py15.5 KB
03 SKILL.md 正文
LinkedIn — Organic Presence Orchestrator
Portability + safety: 17 stdlib-only Python scripts. No LinkedIn credentials, no API calls, no scraping, nothing auto-sent. Every output is text the account holder posts themselves — automated posting, connecting, and commenting are prohibited by LinkedIn's User Agreement §8.2, and a restricted account ends the whole project.
Building an authentic presence over months, not generating a post. The five lanes cover what actually moves: who you are (profile), what you stand for (strategy), what you publish (content), who you talk to (engagement), and what any of it did (analytics).
Step 1 — Gate, before anything is drafted
python3 scripts/linkedin_policy_gate.py --text "<the user's own words>" --output human
- exit 4 REFUSE — a named rule is broken (automation, scraping, pods, bulk DMs, fake identity, fabricated proof, a prohibited automation platform). Do not draft it: name the rule, offer the substitute the gate prints, and route there instead. A REFUSE outranks any route below.
- exit 3 CONSTRAIN — proceed, and state the constraint out loud in your reply.
- exit 0 ALLOW — proceed.
Step 2 — Route
python3 scripts/linkedin_goal_router.py --text "<the goal>" --output human
Exit 0 routes — invoke that lane, surfacing any prerequisite as a question first.
Exit 2 is ambiguous — ask one question naming both candidates, with a recommendation.
Exit 3 has no signal — ask what they want to walk away with, rather than guessing.
| Lane | Typical ask |
|---|---|
linkedin-profile |
"fix my headline", "my profile gets views but nothing happens" |
linkedin-strategy |
"what should I post about", "how often", "should I start a newsletter" |
linkedin-content |
"write this post", "turn my talk into posts", "is this hook any good" |
linkedin-engagement |
"who should I comment on", "write a connection note" |
linkedin-analytics |
"why did reach drop", "what's working", "should I test this" |
Step 3 — Forcing questions
One at a time, each with a recommended answer. Stop as soon as the lane can run honestly.
/cs:grill-linkedin walks all five with the recommendation and the canon behind each.
- What has to be true in 90 days for this to have been worth it? (Not a follower count.)
- Who is this for, specifically enough that someone is excluded?
- How many minutes a week will you protect — measured from a bad week?
- What proof already exists? (If none, the first pillar is process, not results.)
- What will you not post about?
Hard rules
- Nothing is automated and nothing is sent. No credentials, no API, no scraping.
- Refuse, then substitute. Every REFUSE names the compliant alternative.
- The account holder is the author of record. They read every line before it ships.
- No claim they cannot substantiate. A real number, a bounded range, or nothing.
- Never silently chain lanes. Offer the next one as a question.
- Cite the confidence level. LinkedIn-official is ?, third-party studies are ?, folklore is ? and gets named as folklore.
Scripts
| Script | Role |
|---|---|
scripts/linkedin_policy_gate.py |
ALLOW / CONSTRAIN / REFUSE against User Agreement §8.2 + Community Policies. 7 refusal rules, each with a substitute. |
scripts/linkedin_goal_router.py |
Deterministic five-lane classifier: route (0) / ask (2) / no-signal (3), with cross-lane prerequisites. |
References and assets
references/linkedin_platform_canon.md— how the feed ranks, evidence-graded (7 sources)references/policy_and_account_safety.md— §8.2, prohibited software, restriction triggers (7 sources)assets/linkedin_operating_agreement.md— the standing rules in one page, agreed before work starts
Distinct from
marketing-skill/x-twitter-growth— X/Twitter mechanics. Different platform and rules.marketing-skill/social-content/social-media-manager— multi-platform brand calendars. This is one person's presence on one platform, in depth.marketing-skill/social-media-analyzer— cross-platform campaign reporting.
Version: 1.0.0 · 5 lanes · 17 stdlib scripts · nothing auto-sent
04 同仓库更多 Skills
syllabus
Generates a curated supplementary reading list from any course syllabus using Consensus academic search. Grill-me intake (syllabus input format + course audience + year range) plus a grouping forcing-options checkpoint before any search runs — so the reading list matches the course's level and recency need. Parses the syllabus to extract topics and learning outcomes, searches Consensus for recent peer-reviewed papers per topic, and produces a professionally formatted .docx with clickable Consensus links, plain-language summaries calibrated to audience level, and Bloom-higher-order discussion questions tied to course learning goals. Use when the user uploads a syllabus, course outline, or curriculum document and wants supplementary readings (e.g., 'create a reading list from this syllabus', 'find recent papers for my course') — even casual mentions with a syllabus attached should trigger this skill.
pulse
Multi-source recency research skill that takes the pulse of any topic across Reddit, Hacker News, the open web, and optionally X/Twitter within a configurable recent window (default 30 days). Forcing intake clarifies topic specificity, angle (trend/sentiment/problems/opportunities/comparison), time window, and platform scope before searching. Returns a synthesized briefing with citations, engagement metrics, and cross-platform pattern analysis. Use when the user requests multi-source recency intelligence on a topic (e.g., 'pulse on [topic]', 'what's happening with [topic]', 'what are people saying about [topic]', 'current conversation about [topic]', 'take the pulse of [topic]', 'trending: [topic]', 'find me info on [topic]'), and for competitor research, trend discovery, tool comparisons, and audience sentiment analysis.
patent
Patent prior-art and landscape intelligence skill — not generic patent help. Commits to one of five sub-use-cases via forcing intake (novelty search / freedom-to-operate / competitive landscape / acquisition diligence / litigation prior-art) before any search runs. Searches Google Patents, Espacenet, USPTO, and optionally Lens.org for citation-graph signals. Output is an editable Word document (.docx) with verdict, ranked closest art (claim-text extracted), CPC-class-aware landscape, family-resolved hits, geographic coverage, FTO flags where applicable, strategy recommendations, and full audit log. Use when the user asks for patent searching or analysis (e.g., 'prior art search for [invention]', 'freedom to operate analysis for [product]'). Produces search signal, not legal advice — always recommends consulting a patent attorney before filing or licensing decisions. Trademark, copyright, and trade-secret questions are out of scope.
notebooklm
Browser automation skill for controlling Google's NotebookLM. Use when the user wants anything done in NotebookLM (e.g., 'open NotebookLM', 'check my [name] notebook', 'ask my notebook about X', 'add [source] to NotebookLM', 'generate a Video Overview from my notebook', 'use NotebookLM Studio'). Handles reading and querying notebooks, adding sources (URLs, text, files, YouTube links, synthesized content), generating Studio outputs (Audio/Video Overviews, Mind Maps, Reports incl. Briefing Doc/Study Guide/FAQ, Flashcards, Quiz, slide decks, infographics — discover the exact set from the live Studio panel; the UI evolves fast), and creating new notebooks. Requires browser automation environment — fails gracefully when unavailable.
litreview
Academic literature orientation skill that searches papers via free keyless APIs (PubMed E-utilities + OpenAlex) by default — with the Consensus MCP as an optional enhancement lane when connected — builds a strategic search plan using PICO (default) or SPIDER / Decomposition / hybrid as fallbacks, and synthesizes findings into a formatted Word (.docx) research guide. Grill-me intake (research question specificity + framework hint + tentative depth) before the recon search; a second forcing checkpoint after Phase 2 confirms framework + sub-areas + depth before searches consume budget. Configurable depth (5/10/20 queries) controls coverage vs. speed. Output is a 'launching pad' — an orientation guide that lets a researcher dive in confidently, not a finished review. Use when the user starts literature-oriented research (e.g., 'litreview on [topic]', 'literature review on [topic]', 'I'm starting a literature review on X', 'I'm writing a paper on X', 'help me research X', 'I'm doing research on X', 'can you help me research X'). Do NOT use for single one-off paper searches wanting a quick list — that's a plain PubMed/OpenAlex (or Consensus) query.
grants
NIH grant research skill for clinical researchers. Grill-me intake (research idea + career stage + preliminary data + environment + submission posture + known institute targets) locks down the funding strategy before any search runs. Runs a 5-facet Consensus positioning analysis (with draft Significance/Innovation language), maps the research to the right NIH institutes and study sections via RePORTER, finds NOSIs and funded overlap, and produces an editable Word document (.docx) with budget/scope-aware mechanism recommendations, submission timelines, and a mandatory program officer recommendation. Use when the user asks about research funding or makes any grant-related request (e.g., 'grants for [topic]', 'find grants for my research idea', 'what grants match my research', 'help me find NIH funding', 'grant opportunities for my research'). NIH-only scope — non-NIH funders (PCORI, DOD CDMRP, VA, foundations) are out of scope and flagged at intake.