Banner Design System
nextlevelbuilder/ui-ux-pro-max-skill
Walks through designing a banner for social media, ads, a website hero or print, from gathering requirements to building 2 or 3 art-direction options in HTML and CSS.
A skill your agent uses when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis.
MITAuto-check passed
Install Linkedin Analytics
$ npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install alirezarezvani/claude-skills linkedin-analytics --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/marketing/linkedin/skills/linkedin-analytics .claude/skills/linkedin-analytics && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "linkedin-analytics" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin/skills/linkedin-analytics into .claude/skills/linkedin-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-analytics", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin/skills/linkedin-analyticsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install alirezarezvani/claude-skills linkedin-analytics --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/marketing/linkedin/skills/linkedin-analytics .agents/skills/linkedin-analytics && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "linkedin-analytics" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin/skills/linkedin-analytics into .agents/skills/linkedin-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-analytics", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install alirezarezvani/claude-skills linkedin-analytics --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/marketing/linkedin/skills/linkedin-analytics .cursor/skills/linkedin-analytics && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "linkedin-analytics" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin/skills/linkedin-analytics into .cursor/skills/linkedin-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-analytics", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/alirezarezvani/claude-skills.git --path marketing/linkedin/skills/linkedin-analytics--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install alirezarezvani/claude-skills linkedin-analytics --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/marketing/linkedin/skills/linkedin-analytics .gemini/skills/linkedin-analytics && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "linkedin-analytics" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin/skills/linkedin-analytics into .gemini/skills/linkedin-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-analytics", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install alirezarezvani/claude-skills linkedin-analyticsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/marketing/linkedin/skills/linkedin-analytics .github/skills/linkedin-analytics && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "linkedin-analytics" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin/skills/linkedin-analytics into .github/skills/linkedin-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-analytics", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install alirezarezvani/claude-skills linkedin-analytics --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/marketing/linkedin/skills/linkedin-analytics .opencode/skills/linkedin-analytics && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "linkedin-analytics" agent skill from https://github.com/alirezarezvani/claude-skills/tree/main/marketing/linkedin/skills/linkedin-analytics into .opencode/skills/linkedin-analytics/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "linkedin-analytics", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
linkedin-analytics- GitHub stars
- 28k
- Token cost
- ~1.3k tokens
- SKILL.md length
- 571 words
- Files
- 8 (incl. scripts, references, assets)
- Skills in repo
- 342
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis.
- Someone wants to understand their own LinkedIn numbers — which posts worked
- SKILL.md covers Workflow, Rules, Scripts and References and assets, plus 1 more section
- Runs Python scripts from its folder; calls python3
- Why reach dropped
What it does
Linkedin Analytics is an agent skill from alirezarezvani/claude-skills. Use when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis. Triggers on "why did my reach drop", "what's working on my LinkedIn", "analyze my posts", "do carousels do better for me", "should I test this", "LinkedIn analytics". Reads your own exported post data, reports medians and outlier bands, tests candidate patterns against a permutation null, and sizes a real experiment — refusing to conclude anything below…
Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/measurement_log_template.md`, `references/evidence_thresholds.md` and `references/linkedin_metrics_canon.md`).
It works with LinkedIn. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.
When your agent uses it
- Someone wants to understand their own LinkedIn numbers — which posts worked
- Why reach dropped
- Whether a pattern is real
- How to test a hypothesis
Example prompts
- “why did my reach drop”
- “s working on my LinkedIn”
- “analyze my posts”
- “/linkedin-analytics”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Linkedin Analytics loads about 1.3k tokens when it runs, and up to ~4.5k if it reads all its reference files. Until then it costs about 136 tokens; SKILL.md has 571 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 571 words, ~1,330 tokens.
Download SKILL.mdSave it as
.claude/skills/linkedin-analytics/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- linkedin-analytics
- description
- Use when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis. Triggers on "why did my reach drop", "what's working on my LinkedIn", "analyze my posts", "do carousels do better for me", "should I test this", "LinkedIn analytics". Reads your own exported post data, reports medians and outlier bands, tests candidate patterns against a permutation null, and sizes a real experiment — refusing to conclude anything below 10 posts.
- license
- MIT
- metadata.version
- 1.0.0
- metadata.author
- Alireza Rezvani
- metadata.category
- marketing
- metadata.updated
- 2026-08-25
LinkedIn Analytics — describe honestly, then refuse to over-conclude
The characteristic sentence of LinkedIn analytics is "carousels do 3x better for me", built on four posts. With engagement as heavy-tailed as it is, four posts will show a 3x difference between almost any two groups you care to define. These three scripts stop that sentence becoming a strategy.
Your own data only. Nothing is fetched; scraping post or profile data is prohibited by User Agreement §8.2 and none of this analysis needs it.
Workflow
1. Get the export. LinkedIn Analytics → Post impressions → Export, or Settings → Data privacy → Get a copy of your data. CSV and JSON both work.
2. Describe it. Exit 0 analysed / 2 below the 10-post floor, descriptive only / 3 unusable. Reports median and MAD rather than mean and standard deviation — one breakout post makes a mean describe a distribution none of your posts belong to — plus Tukey percentile bands and a 1.5×IQR breakout threshold, so "this did well" has a number behind it.
python3 scripts/post_performance_analyzer.py --input posts.csv --csv --output human3. Test the pattern they think they see.
python3 scripts/pattern_miner.py --input posts.json --output humanExit 0 something survived / 2 nothing survived / 3 under 10 posts. Four gates: 5 posts in and 5 out; a 15% relative difference in medians; beating 90% of 2,000 seeded label shuffles; and a multiple-comparisons accounting of how many candidates would pass on noise alone.
"Nothing survived" is the most common honest answer and it is a real finding. Report it as one. Do not soften it into a hedge that reads like a conclusion.
4. Turn a survivor into a test.
python3 scripts/experiment_planner.py --hypothesis "..." --variable "..." \
--cv 0.45 --effect 0.30 --posts-per-week 2 --max-weeks 12 --output humanCV comes from step 2: 1.4826 * MAD / median. Exit 0 feasible / 2 too long, with the minimum
detectable effect in their window / 3 refused. It will frequently say the test needs more
posts than a quarter allows — that is the honest answer, and more useful than a confident
conclusion from retrospective data.
Show full SKILL.md (264 more words)Show less
Rules
- Under 10 posts, describe; do not conclude. Say so plainly.
- A pattern in past posts is a hypothesis. Retrospective data is confounded — you made carousels when you had structured material, on topics you knew best, in weeks you had time. No statistics on the same data removes that.
- Never benchmark against someone else's numbers. Different denominator, different audience, usually a vendor's sample.
- Follower count is not a success metric. Track inbound conversations, specific references, invitations — the Tier 1 metrics you count by hand.
- Report the confidence level. LinkedIn-official 🟢, third-party study 🟡, folklore 🔴.
- One good post is not evidence. It is the most common cause of a strategy change and the least informative event available.
Scripts
| Script | Role |
|---|---|
scripts/post_performance_analyzer.py | Median/MAD, percentile bands, IQR outlier fence, per-post BREAKOUT→DUD classification; refuses conclusions below 10 posts. |
scripts/pattern_miner.py | Four-gate permutation test with multiple-comparisons accounting; reports why every rejected candidate failed. |
scripts/experiment_planner.py | Sizes a two-arm posting experiment, names the confounds to hold constant, and writes the falsification condition before the first post. |
References and assets
references/linkedin_metrics_canon.md— what each number is, what it is not, and which three tiers to track (7 sources)references/evidence_thresholds.md— the four gates, forking paths, and the uncomfortable arithmetic of LinkedIn A/B tests (7 sources)assets/example_post_export.csv— a 12-post export in the expected shapeassets/measurement_log_template.md— the Tier 1 outcome log you keep by hand
Distinct from
marketing-skill/social-media-analyzer— cross-platform brand campaign reporting. This is one person's own LinkedIn export, with refusals attached.linkedin-strategy— decides what to do next. This says what happened.product-team/experiment-designer— product A/B tests with real traffic; here n is posts, and usually too small.
Version: 1.0.0
© alirezarezvani, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 7 other files (scripts, references, assets) in marketing/linkedin/skills/linkedin-analytics of alirezarezvani/claude-skills.
- SKILL.md
- assets/example_post_export.csv
- assets/measurement_log_template.md
- references/evidence_thresholds.md
- references/linkedin_metrics_canon.md
- scripts/experiment_planner.py
- scripts/pattern_miner.py
- scripts/post_performance_analyzer.py
Open the folder on GitHubat commit 19392f7
Compare with similar skills
Linkedin Analytics next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Linkedin Analytics this skillalirezarezvani/claude-skills | 28k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Banner Design Systemnextlevelbuilder/ui-ux-pro-max-skill | 134k | 1 repos | ~1.8k | Automated safety check: Pass | MIT | |
| Agent ReachPanniantong/Agent-Reach | 93k | — | ~1.4k | Automated safety check: Pass | MIT | |
| Social Contentfreekmurze/dotfiles | 1k | 22 repos | ~2.1k | Automated safety check: Pass | None | |
| Ad CreativeLeoYeAI/openclaw-marketing-skills | 1k | 8 repos | ~3.4k | Automated safety check: Pass | Custom licence | |
| Linkedin Marketingsergebulaev/linkedin-skills | 4.3k | 1 repos | ~3.2k | Automated safety check: Notes | MIT |
Similar skills
Agent Reach
Panniantong/Agent-Reach
Routes web research and platform lookups across 16 sites, including Twitter, Reddit, YouTube, Bilibili, Xiaohongshu and GitHub, through one command-line tool.
Social Content
freekmurze/dotfiles
When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms.
Ad Creative
LeoYeAI/openclaw-marketing-skills
When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform.
Linkedin Marketing
sergebulaev/linkedin-skills
Plan, draft, audit, and publish LinkedIn posts and comments.
LinkedIn Job Search
MadsLorentzen/ai-job-search
Searches LinkedIn's public job listings for any location or remote work and fetches the full description of a posting, with no login or API key.
More from alirezarezvani/claude-skills
All 342 skills in this repoAgile Product Owner
alirezarezvani/claude-skills
Writes INVEST-checked user stories with acceptance criteria, splits epics, plans sprints from velocity and ranks the backlog with a weighted score.
Product Strategist
alirezarezvani/claude-skills
OKR cascade toolkit for product leaders: generates aligned company-to-team OKRs from five strategy types and scores how well they line up.
App Store Optimization
alirezarezvani/claude-skills
App Store Optimization (ASO) toolkit for researching keywords, analyzing competitor rankings, generating metadata suggestions, and improving app visibility on Apple App Store and Google Play Store.
AWS Solution Architect
alirezarezvani/claude-skills
Design AWS architectures for startups using serverless patterns and IaC templates.
Campaign Analytics
alirezarezvani/claude-skills
Calculates attribution, funnel and ROI figures for marketing campaigns with three Python scripts that need only the standard library.
Code to PRD
alirezarezvani/claude-skills
Reverse-engineers a frontend, backend or fullstack codebase into a product requirements document with per-page docs, an enum dictionary and an API inventory.
Related
Works with
Questions about Linkedin Analytics
What does Linkedin Analytics do?
A skill your agent uses when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis. Linkedin Analytics is an agent skill from alirezarezvani/claude-skills. Use when someone wants to understand their own LinkedIn numbers — which posts worked, why reach dropped, whether a pattern is real, or how to test a hypothesis.
When should I use Linkedin Analytics?
Linkedin Analytics fits situations like: someone wants to understand their own LinkedIn numbers — which posts worked; why reach dropped; whether a pattern is real; how to test a hypothesis.
How do I install Linkedin Analytics in Claude Code?
Run `npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a claude-code`. Or copy the skill folder (marketing/linkedin/skills/linkedin-analytics in alirezarezvani/claude-skills) into .claude/skills/linkedin-analytics in your project. Claude Code loads it when a task matches its description.
How do I install Linkedin Analytics in Codex?
Run `npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a codex`. Or copy the skill folder (marketing/linkedin/skills/linkedin-analytics in alirezarezvani/claude-skills) into .agents/skills/linkedin-analytics in your project. Codex loads it when a task matches its description.
Can I use Linkedin Analytics in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alirezarezvani/claude-skills --skill linkedin-analytics -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/linkedin-analytics, .gemini/skills/linkedin-analytics, .github/skills/linkedin-analytics and .opencode/skills/linkedin-analytics in your project.
What does Linkedin Analytics need to run?
Going by SKILL.md and its folder, Linkedin Analytics needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Linkedin Analytics access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Linkedin Analytics safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Linkedin Analytics use?
Linkedin Analytics is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Linkedin Analytics use?
About 1.3k tokens (SKILL.md is roughly 5.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.1k tokens, read only when the agent opens those files.
What are the alternatives to Linkedin Analytics?
Skills that share tags, products or a category with Linkedin Analytics: Banner Design System (nextlevelbuilder/ui-ux-pro-max-skill, 134k stars), Agent Reach (Panniantong/Agent-Reach, 93k stars), Social Content (freekmurze/dotfiles, 1k stars) and Ad Creative (LeoYeAI/openclaw-marketing-skills, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Linkedin Analytics?
alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,788 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.
Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.