Code Review Checklist
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
CRITICAL: Use for performance optimization. An agent skill from fjrevoredo/mini-diarium.
Install M10 Performance
$ npx skills add fjrevoredo/mini-diarium --skill m10-performance -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install fjrevoredo/mini-diarium m10-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/fjrevoredo/mini-diarium.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/m10-performance .claude/skills/m10-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 "m10-performance" agent skill from https://github.com/fjrevoredo/mini-diarium/tree/master/.agents/skills/m10-performance into .claude/skills/m10-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "m10-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/fjrevoredo/mini-diarium/tree/master/.agents/skills/m10-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 fjrevoredo/mini-diarium --skill m10-performance -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install fjrevoredo/mini-diarium m10-performance --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fjrevoredo/mini-diarium.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/m10-performance .agents/skills/m10-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 "m10-performance" agent skill from https://github.com/fjrevoredo/mini-diarium/tree/master/.agents/skills/m10-performance into .agents/skills/m10-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "m10-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 fjrevoredo/mini-diarium --skill m10-performance -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install fjrevoredo/mini-diarium m10-performance --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fjrevoredo/mini-diarium.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/m10-performance .cursor/skills/m10-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 "m10-performance" agent skill from https://github.com/fjrevoredo/mini-diarium/tree/master/.agents/skills/m10-performance into .cursor/skills/m10-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "m10-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/fjrevoredo/mini-diarium.git --path .agents/skills/m10-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 fjrevoredo/mini-diarium --skill m10-performance -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install fjrevoredo/mini-diarium m10-performance --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fjrevoredo/mini-diarium.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/m10-performance .gemini/skills/m10-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 "m10-performance" agent skill from https://github.com/fjrevoredo/mini-diarium/tree/master/.agents/skills/m10-performance into .gemini/skills/m10-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "m10-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 fjrevoredo/mini-diarium m10-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 fjrevoredo/mini-diarium --skill m10-performance -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/fjrevoredo/mini-diarium.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/m10-performance .github/skills/m10-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 "m10-performance" agent skill from https://github.com/fjrevoredo/mini-diarium/tree/master/.agents/skills/m10-performance into .github/skills/m10-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "m10-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 fjrevoredo/mini-diarium --skill m10-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 fjrevoredo/mini-diarium m10-performance --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/fjrevoredo/mini-diarium.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/m10-performance .opencode/skills/m10-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 "m10-performance" agent skill from https://github.com/fjrevoredo/mini-diarium/tree/master/.agents/skills/m10-performance into .opencode/skills/m10-performance/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "m10-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
m10-performance- GitHub stars
- 308
- Used in
- 2 other repos
- Token cost
- ~1k tokens
- SKILL.md length
- 307 words
- Files
- 2
- Skills in repo
- 41
- Repo updated
- First seen
- Licence
- MIT
At a glance
CRITICAL: Use for performance optimization. An agent skill from fjrevoredo/mini-diarium.
- Works in 3 steps: Have you measured? → What's the priority? → What's the trade-off?
- Performance optimization
- SKILL.md covers Core Question, Performance Decision →…, Thinking Prompt and Trace Up ↑, plus 7 more sections
- Calls cargo
What it does
M10 Performance is an agent skill from fjrevoredo/mini-diarium. CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `patterns/optimization-guide.md`).
It sits in Development, covering Performance optimization. The repository describes itself as: A local-only journal with serious encryption. Free, open source, and never touches the internet. The licence is MIT.
When your agent uses it
- Performance optimization
- Tasks that involve Performance optimization
Example prompts
- “/m10-performance”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- Have you measured?
- What's the priority?
- What's the trade-off?
What it can do on your machine
Read from SKILL.md and the folder at commit 75c1286. 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
Shell commands in SKILL.md call:
cargo
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
M10 Performance loads about 1k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 307 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 fjrevoredo/mini-diarium at commit 75c1286, republished under its MIT licence (© fjrevoredo). 307 words, ~1,034 tokens.
Download SKILL.mdSave it as
.claude/skills/m10-performance/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- m10-performance
- description
- CRITICAL: Use for performance optimization. Triggers: performance, optimization, benchmark, profiling, flamegraph, criterion, slow, fast, allocation, cache, SIMD, make it faster, 性能优化, 基准测试
- user-invocable
- false
Performance Optimization
Layer 2: Design Choices
Core Question
What's the bottleneck, and is optimization worth it?
Before optimizing:
- Have you measured? (Don't guess)
- What's the acceptable performance?
- Will optimization add complexity?
Performance Decision → Implementation
| Goal | Design Choice | Implementation |
|---|---|---|
| Reduce allocations | Pre-allocate, reuse | with_capacity, object pools |
| Improve cache | Contiguous data | Vec, SmallVec |
| Parallelize | Data parallelism | rayon, threads |
| Avoid copies | Zero-copy | References, Cow<T> |
| Reduce indirection | Inline data | smallvec, arrays |
Thinking Prompt
Before optimizing:
Have you measured?
- Profile first → flamegraph, perf
- Benchmark → criterion, cargo bench
- Identify actual hotspots
What's the priority?
- Algorithm (10x-1000x improvement)
- Data structure (2x-10x)
- Allocation (2x-5x)
- Cache (1.5x-3x)
What's the trade-off?
- Complexity vs speed
- Memory vs CPU
- Latency vs throughput
Trace Up ↑
To domain constraints (Layer 3):
"How fast does this need to be?"
↑ Ask: What's the performance SLA?
↑ Check: domain-* (latency requirements)
↑ Check: Business requirements (acceptable response time)| Question | Trace To | Ask |
|---|---|---|
| Latency requirements | domain-* | What's acceptable response time? |
| Throughput needs | domain-* | How many requests per second? |
| Memory constraints | domain-* | What's the memory budget? |
Trace Down ↓
To implementation (Layer 1):
"Need to reduce allocations"
↓ m01-ownership: Use references, avoid clone
↓ m02-resource: Pre-allocate with_capacity
"Need to parallelize"
↓ m07-concurrency: Choose rayon or threads
↓ m07-concurrency: Consider async for I/O-bound
"Need cache efficiency"
↓ Data layout: Prefer Vec over HashMap when possible
↓ Access patterns: Sequential over random accessQuick Reference
| Tool | Purpose |
|---|---|
cargo bench | Micro-benchmarks |
criterion | Statistical benchmarks |
perf / flamegraph | CPU profiling |
heaptrack | Allocation tracking |
valgrind / cachegrind | Cache analysis |
Optimization Priority
1. Algorithm choice (10x - 1000x)
2. Data structure (2x - 10x)
3. Allocation reduction (2x - 5x)
4. Cache optimization (1.5x - 3x)
5. SIMD/Parallelism (2x - 8x)Common Techniques
| Technique | When | How |
|---|---|---|
| Pre-allocation | Known size | Vec::with_capacity(n) |
| Avoid cloning | Hot paths | Use references or Cow<T> |
| Batch operations | Many small ops | Collect then process |
| SmallVec | Usually small | smallvec::SmallVec<[T; N]> |
| Inline buffers | Fixed-size data | Arrays over Vec |
Common Mistakes
| Mistake | Why Wrong | Better |
|---|---|---|
| Optimize without profiling | Wrong target | Profile first |
| Benchmark in debug mode | Meaningless | Always --release |
| Use LinkedList | Cache unfriendly | Vec or VecDeque |
Hidden .clone() | Unnecessary allocs | Use references |
| Premature optimization | Wasted effort | Make it work first |
Anti-Patterns
| Anti-Pattern | Why Bad | Better |
|---|---|---|
| Clone to avoid lifetimes | Performance cost | Proper ownership |
| Box everything | Indirection cost | Stack when possible |
| HashMap for small sets | Overhead | Vec with linear search |
| String concat in loop | O(n^2) | String::with_capacity or format! |
Related Skills
| When | See |
|---|---|
| Reducing clones | m01-ownership |
| Concurrency options | m07-concurrency |
| Smart pointer choice | m02-resource |
| Domain requirements | domain-* |
© fjrevoredo, 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 1 other file in .agents/skills/m10-performance of fjrevoredo/mini-diarium.
- SKILL.md
- patterns/optimization-guide.md
Open the folder on GitHubat commit 75c1286
Used in 2 other repositories
We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in fjrevoredo/mini-diarium, which our catalogue first saw on October 7, 2026.
Compare with similar skills
M10 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 |
|---|---|---|---|---|---|---|
| M10 Performance this skillfjrevoredo/mini-diarium | 308 | 2 repos | ~1k | Automated safety check: Pass | MIT | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 5 repos | ~1.1k | Automated safety check: Pass | MIT | |
| LLM Torch Profiler Analysissgl-project/sglang | 37k | 2 repos | ~6.4k | Automated safety check: Pass | Apache-2.0 | |
| Pycrazyguitar/pysheeet | 8.2k | — | ~886 | Automated safety check: Pass | MIT | |
| Cmux Debugging Guidemanaflow-ai/cmux | 28k | 1 repos | ~1.1k | Automated safety check: Pass | Custom licence | |
| Electron Heap Snapshot Analysiskeybase/client | 9.3k | — | ~875 | Automated safety check: Pass | BSD-3-Clause |
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Related
Categories
Questions about M10 Performance
What does M10 Performance do?
CRITICAL: Use for performance optimization. An agent skill from fjrevoredo/mini-diarium. M10 Performance is an agent skill from fjrevoredo/mini-diarium. CRITICAL: Use for performance optimization.
When should I use M10 Performance?
M10 Performance fits situations like: performance optimization; tasks that involve Performance optimization.
How do I install M10 Performance in Claude Code?
Run `npx skills add fjrevoredo/mini-diarium --skill m10-performance -a claude-code`. Or copy the skill folder (.agents/skills/m10-performance in fjrevoredo/mini-diarium) into .claude/skills/m10-performance in your project. Claude Code loads it when a task matches its description.
How do I install M10 Performance in Codex?
Run `npx skills add fjrevoredo/mini-diarium --skill m10-performance -a codex`. Or copy the skill folder (.agents/skills/m10-performance in fjrevoredo/mini-diarium) into .agents/skills/m10-performance in your project. Codex loads it when a task matches its description.
Can I use M10 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 fjrevoredo/mini-diarium --skill m10-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/m10-performance, .gemini/skills/m10-performance, .github/skills/m10-performance and .opencode/skills/m10-performance in your project.
What does M10 Performance need to run?
Going by SKILL.md and its folder, M10 Performance needs the command-line tools its instructions call (cargo).
Does M10 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 M10 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 M10 Performance use?
M10 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 M10 Performance use?
About 1k tokens (SKILL.md is roughly 4.1k 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 M10 Performance?
Skills that share tags, products or a category with M10 Performance: Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), LLM Torch Profiler Analysis (sgl-project/sglang, 37k stars), Py (crazyguitar/pysheeet, 8.2k stars) and Cmux Debugging Guide (manaflow-ai/cmux, 28k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains M10 Performance?
fjrevoredo (a GitHub user) maintains it in fjrevoredo/mini-diarium, which has 308 GitHub stars. The repository holds 41 skills in this directory. The repository was last updated on October 4, 2026.
Source: fjrevoredo/mini-diarium on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.