Humanizer
Azure-Samples/interview-coach-agent-framework
Remove signs of AI-generated writing from text. An agent skill from Azure-Samples/interview-coach-agent-framework.
Analyze engagement patterns across published posts to identify what works.
Install Analyze Performance
$ npx skills add techwolf-ai/ai-first-toolkit --skill analyze-performance -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install techwolf-ai/ai-first-toolkit analyze-performance --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/techwolf-ai/ai-first-toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/content-studio/skills/analyze-performance .claude/skills/analyze-performance && 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 "analyze-performance" agent skill from https://github.com/techwolf-ai/ai-first-toolkit/tree/main/plugins/content-studio/skills/analyze-performance into .claude/skills/analyze-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-performance", 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/techwolf-ai/ai-first-toolkit/tree/main/plugins/content-studio/skills/analyze-performanceType 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 techwolf-ai/ai-first-toolkit --skill analyze-performance -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install techwolf-ai/ai-first-toolkit analyze-performance --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkit.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/content-studio/skills/analyze-performance .agents/skills/analyze-performance && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "analyze-performance" agent skill from https://github.com/techwolf-ai/ai-first-toolkit/tree/main/plugins/content-studio/skills/analyze-performance into .agents/skills/analyze-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-performance", 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 techwolf-ai/ai-first-toolkit --skill analyze-performance -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install techwolf-ai/ai-first-toolkit analyze-performance --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkit.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/content-studio/skills/analyze-performance .cursor/skills/analyze-performance && 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 "analyze-performance" agent skill from https://github.com/techwolf-ai/ai-first-toolkit/tree/main/plugins/content-studio/skills/analyze-performance into .cursor/skills/analyze-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-performance", 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/techwolf-ai/ai-first-toolkit.git --path plugins/content-studio/skills/analyze-performance--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 techwolf-ai/ai-first-toolkit --skill analyze-performance -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install techwolf-ai/ai-first-toolkit analyze-performance --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkit.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/content-studio/skills/analyze-performance .gemini/skills/analyze-performance && 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 "analyze-performance" agent skill from https://github.com/techwolf-ai/ai-first-toolkit/tree/main/plugins/content-studio/skills/analyze-performance into .gemini/skills/analyze-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-performance", 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 techwolf-ai/ai-first-toolkit analyze-performanceInstalls 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 techwolf-ai/ai-first-toolkit --skill analyze-performance -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkit.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/content-studio/skills/analyze-performance .github/skills/analyze-performance && 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 "analyze-performance" agent skill from https://github.com/techwolf-ai/ai-first-toolkit/tree/main/plugins/content-studio/skills/analyze-performance into .github/skills/analyze-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-performance", 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 techwolf-ai/ai-first-toolkit --skill analyze-performance -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install techwolf-ai/ai-first-toolkit analyze-performance --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/techwolf-ai/ai-first-toolkit.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/content-studio/skills/analyze-performance .opencode/skills/analyze-performance && 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 "analyze-performance" agent skill from https://github.com/techwolf-ai/ai-first-toolkit/tree/main/plugins/content-studio/skills/analyze-performance into .opencode/skills/analyze-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "analyze-performance", 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
analyze-performance- GitHub stars
- 132
- Used in
- 1 other repo
- Token cost
- ~689 tokens
- SKILL.md length
- 222 words
- Files
- 1
- Skills in repo
- 29
- Repo updated
- First seen
- Licence
- MIT
At a glance
Analyze engagement patterns across published posts to identify what works.
- Works in 3 steps: Run ./scripts/print-published.sh… → Extract posts that have engagement data… → Analyze patterns across high-performing…
- Asked to review performance
- SKILL.md covers Process, Analysis Dimensions, Performance Tiers and Output Format, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Analyze Performance is an agent skill from techwolf-ai/ai-first-toolkit. Analyze engagement patterns across published posts to identify what works. Use when asked to review performance, find successful patterns, or optimize future content.
Its SKILL.md is about 690 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Writing & Content. The repository describes itself as: Open-source Claude Code skills and Codex skills for AI-first work. Audit, re-engineer, and bootstrap projects with AI-first design principles. The licence is MIT.
When your agent uses it
- Asked to review performance
- Find successful patterns
- Optimize future content
Example prompts
- “/analyze-performance”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Run ./scripts/print-published.sh linkedin-post to read all published LinkedIn posts
- Extract posts that have engagement data (engagement.reactions, engagement.views, etc.)
- Analyze patterns across high-performing vs low-performing posts
What it can do on your machine
Read from SKILL.md and the folder at commit 2ee7841. 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
No scripts in the folder and no shell commands in SKILL.md.
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
Analyze Performance loads about 689 tokens when it runs. Until then it costs about 47 tokens; SKILL.md has 222 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); files beside SKILL.md are not scanned.
SKILL.md
The full file from techwolf-ai/ai-first-toolkit at commit 2ee7841, republished under its MIT licence (© techwolf-ai). 222 words, ~689 tokens.
Download SKILL.mdSave it as
.claude/skills/analyze-performance/SKILL.md (or your agent's skills folder).- name
- analyze-performance
- description
- Analyze engagement patterns across published posts to identify what works. Use when asked to review performance, find successful patterns, or optimize future content.
Analyze Content Performance
Identify patterns in high-performing posts to inform future content strategy.
Process
- Run
./scripts/print-published.sh linkedin-postto read all published LinkedIn posts - Extract posts that have engagement data (engagement.reactions, engagement.views, etc.)
- Analyze patterns across high-performing vs low-performing posts
Analysis Dimensions
Hook Analysis
- What hook styles correlate with higher engagement?
- Personal anecdote vs company experience vs surprising data vs news hook?
- First 210 characters (LinkedIn cutoff) - what patterns work?
Content Characteristics
- Word count vs engagement correlation
- Use of concrete examples vs abstract concepts
- Presence of frameworks or mental models
- Use of lists/structure vs flowing narrative
Topic Analysis
- Which tags correlate with higher engagement?
- Which themes resonate most?
- Timing patterns (if publishedDate available)
Structural Patterns
- Opening style (question, statement, story)
- Closing style (call-to-action, reflection, question)
- Paragraph length and density
Performance Tiers
Categorize posts by reaction count:
- High performers: 100+ reactions
- Medium performers: 30-99 reactions
- Lower performers: <30 reactions
Output Format
Provide:
- Summary statistics - Total posts analyzed, average engagement by tier
- Top performers - List highest-engagement posts with their key characteristics
- Pattern insights - What distinguishes high vs lower performers?
- Recommendations - Actionable suggestions for future content
Example Analysis Output
## Performance Summary
- Posts analyzed: 12 (with engagement data)
- High performers (100+): 3 posts
- Medium performers (30-99): 5 posts
- Lower performers (<30): 4 posts
## Top Performers
1. "Title" - 245 reactions
- Hook: Personal anecdote
- Topic: AI productivity
- Word count: 180
## Key Patterns
- Personal anecdotes in the first sentence correlate with 2x higher engagement
- Posts with concrete examples outperform abstract posts by 40%
- Optimal word count appears to be 150-200 words
## Recommendations
1. Lead with personal or company-specific openings
2. Include at least one specific example or data point
3. Keep total length under 220 wordsNotes
- Only analyze posts with engagement data (skip posts without metrics)
- Correlation is not causation - note patterns but don't overclaim
- Consider recency bias - newer posts may still be accumulating engagement
© techwolf-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in plugins/content-studio/skills/analyze-performance of techwolf-ai/ai-first-toolkit.
Open the folder on GitHubat commit 2ee7841
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in techwolf-ai/ai-first-toolkit, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Analyze Performance 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 |
|---|---|---|---|---|---|---|
| Analyze Performance this skilltechwolf-ai/ai-first-toolkit | 132 | 1 repos | ~689 | Automated safety check: Pass | MIT | |
| HumanizerAzure-Samples/interview-coach-agent-framework | 172 | 37 repos | ~5.8k | Automated safety check: Pass | MIT | |
| Avoid AI Writingconorbronsdon/avoid-ai-writing | 4.9k | 3 repos | ~8.1k | Automated safety check: Pass | MIT | |
| JavaScript Concept Fact Checkerleonardomso/33-js-concepts | 67k | 1 repos | ~5k | Automated safety check: Pass | MIT | |
| User-Facing Text Cleanupguillaumemeyer/watermarks-remover | 23k | — | ~3.5k | Automated safety check: Pass | MIT | |
| Install Anti Sloptrycompai/crm | 11k | 1 repos | ~881 | Automated safety check: Pass | MIT |
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Questions about Analyze Performance
What does Analyze Performance do?
Analyze engagement patterns across published posts to identify what works. Analyze Performance is an agent skill from techwolf-ai/ai-first-toolkit. Analyze engagement patterns across published posts to identify what works.
When should I use Analyze Performance?
Analyze Performance fits situations like: asked to review performance; find successful patterns; optimize future content.
How do I install Analyze Performance in Claude Code?
Run `npx skills add techwolf-ai/ai-first-toolkit --skill analyze-performance -a claude-code`. Or copy the skill folder (plugins/content-studio/skills/analyze-performance in techwolf-ai/ai-first-toolkit) into .claude/skills/analyze-performance in your project. Claude Code loads it when a task matches its description.
How do I install Analyze Performance in Codex?
Run `npx skills add techwolf-ai/ai-first-toolkit --skill analyze-performance -a codex`. Or copy the skill folder (plugins/content-studio/skills/analyze-performance in techwolf-ai/ai-first-toolkit) into .agents/skills/analyze-performance in your project. Codex loads it when a task matches its description.
Can I use Analyze Performance 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 techwolf-ai/ai-first-toolkit --skill analyze-performance -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/analyze-performance, .gemini/skills/analyze-performance, .github/skills/analyze-performance and .opencode/skills/analyze-performance in your project.
What does Analyze Performance need to run?
SKILL.md names no scripts, command-line tools or credentials: Analyze Performance is instructions for the agent only.
Does Analyze Performance 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 Analyze Performance 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. Review the folder before installing.
What licence does Analyze Performance use?
Analyze Performance is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Analyze Performance use?
About 689 tokens (SKILL.md is roughly 2.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Analyze Performance?
Skills that share tags, products or a category with Analyze Performance: Humanizer (Azure-Samples/interview-coach-agent-framework, 172 stars), Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars), JavaScript Concept Fact Checker (leonardomso/33-js-concepts, 67k stars) and User-Facing Text Cleanup (guillaumemeyer/watermarks-remover, 23k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Analyze Performance?
techwolf-ai (a GitHub organization) maintains it in techwolf-ai/ai-first-toolkit, which has 132 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on September 29, 2026.
Source: techwolf-ai/ai-first-toolkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.