performance-review
Skill3 starsChanged 34 days agoMITView on GitHub
Weekly or monthly review of your own posts: read real insights, compare to each channel's baseline, name what worked, propose next week.
26 other projects use a version of this.
Adopted by
Most recently taken up by
- Smaui94/ClaudeSkillCollectiontheir own version, first seen Nov 8, 2026
- nisarth/claude-skills-storetheir own version, first seen Nov 8, 2026
- frnkgns/Overgeared-Skillstheir own version, first seen Nov 8, 2026
- flopperj/dotfiles-coretheir own version, first seen Nov 4, 2026
- Cure-Consulting-Group/ProductEngineeringSkillstheir own version, first seen Nov 4, 2026
- nledford/engineering-review-boardtheir own version, first seen Nov 3, 2026
Used with
Projects with it also use ci-cd-pipeline, architecture-review and 3 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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SentrySkillarchitecture-review
Staff-level codebase health review. Finds monolithic modules, silent failures, type safety gaps, test coverage holes, and LLM-friendliness issues.
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SentrySkillsecurity-review
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MicrosoftSkillapi-design
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OpenAISkillsystematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Also in 3 projects that use this
Other versions26 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 26
- anthropics/knowledge-work-plugins★ 35ksame name
- genspark-ai/genoffice★ 12ksame name
- microsoft/intelligent-terminal★ 2.2ksame name
- borgbase/vykar★ 722same name
- ShipSecAI/studio★ 380same name
- nledford/engineering-review-board★ 11same name
- bis-code/claude-toolkit★ 8same name
- frnkgns/Overgeared-Skills★ 7same name
- Sagargupta16/agent-recipes★ 4same name
- vikisingh23/neuraforge-ai★ 4same name
16 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository50 other files it gives its agents.
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- naver-ai-citeSkill
- naver-draftsSkill
- naver-engageSkill
- naver-keywordsSkill
- naver-postSkill
- publishSkill
- repurposeSkill
- schedule-weekSkill
- setupSkill
- threadsSkill
- troubleshootSkill
- voice-profileSkill
- yt-auditSkill
- yt-benchmarkSkill
- yt-chaptersSkill
- yt-commentSkill
- yt-editSkill
- yt-packageSkill
- yt-planSkill
- yt-retentionSkill
- yt-scriptSkill
- yt-seoSkill
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- yt-uploadSkill
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The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 22 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 8
Use this for "how did my posts do this week", a monthly report, or before planning the next batch.
- Very specific: line 12
If a call answers workspace_required, the account has more than one workspace: show the names it lists, ask which one, and pass that …
“Common” is measured: kept by at least 6 in 10 of the 22 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Performance review
Use this for "how did my posts do this week", a monthly report, or before planning the next batch.
Procedure
If a call answers workspace_required, the account has more than one workspace: show the names it lists, ask which one, and pass that workspaceId on every later call in this session.
- Window: ask for the period if the person did not say (this week, last 30 days).
- Collect posts:
list_postswithsinceanduntilfor posts made through Uplika, andlist_channel_postsfor posts written in the channels' own apps when the person wants those too. - For each post,
get_insights: views, likes, replies, reposts, quotes, shares. Null is not zero: some channels do not report views or shares, or not yet. Keep nulls out of averages and say which channel did not report. - Baseline per channel: compare each post to the median of the same channel's posts in the window, never across channels (a Threads post and a YouTube video do not share a scale). With too few posts on a channel, say the baseline is weak.
- What worked: look at the top and bottom posts per channel and name concrete differences you can see in the posts themselves: the hook type (question, number, claim, story), length, chain or single post, media or text, posting time. Say how confident you are; one post is an anecdote.
- Say what Uplika does not have: impressions per follower, click-through rate, watch time and retention curves are not in these tools (for YouTube retention, see
yt-retention).
Output
One table (post, channel, date, the metrics, against baseline), then three bullets for what worked, then three concrete things to try next week, each tied to a post in the table. Offer to draft next week with schedule-week.
Tools
list_posts: posts made through Uplika in the windowlist_channel_posts: posts on the channel, including ones written in the appget_insights: per-post metrics (null means not reported)
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
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- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

