Performance Report
Affitor/affiliate-skills
Generate affiliate performance reports with KPIs and recommendations.
Manage for output using Grove's "High Output Management": a manager's output is their organization's output, raised by high-leverage activities.
$ npx skills add wondelai/skills --skill high-output-management -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install wondelai/skills high-output-management --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/wondelai/skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/high-output-management .claude/skills/high-output-management && 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 "high-output-management" agent skill from https://github.com/wondelai/skills/tree/main/high-output-management into .claude/skills/high-output-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "high-output-management", 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/wondelai/skills/tree/main/high-output-managementType 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 wondelai/skills --skill high-output-management -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install wondelai/skills high-output-management --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/high-output-management .agents/skills/high-output-management && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "high-output-management" agent skill from https://github.com/wondelai/skills/tree/main/high-output-management into .agents/skills/high-output-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "high-output-management", 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 wondelai/skills --skill high-output-management -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install wondelai/skills high-output-management --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/high-output-management .cursor/skills/high-output-management && 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 "high-output-management" agent skill from https://github.com/wondelai/skills/tree/main/high-output-management into .cursor/skills/high-output-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "high-output-management", 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/wondelai/skills.git --path high-output-management--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 wondelai/skills --skill high-output-management -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install wondelai/skills high-output-management --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/high-output-management .gemini/skills/high-output-management && 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 "high-output-management" agent skill from https://github.com/wondelai/skills/tree/main/high-output-management into .gemini/skills/high-output-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "high-output-management", 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 wondelai/skills high-output-managementInstalls 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 wondelai/skills --skill high-output-management -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/high-output-management .github/skills/high-output-management && 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 "high-output-management" agent skill from https://github.com/wondelai/skills/tree/main/high-output-management into .github/skills/high-output-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "high-output-management", 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 wondelai/skills --skill high-output-management -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install wondelai/skills high-output-management --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/wondelai/skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/high-output-management .opencode/skills/high-output-management && 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 "high-output-management" agent skill from https://github.com/wondelai/skills/tree/main/high-output-management into .opencode/skills/high-output-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "high-output-management", 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.
high-output-managementManage for output using Grove's "High Output Management": a manager's output is their organization's output, raised by high-leverage activities.
High Output Management is an agent skill from wondelai/skills. Manage for output using Grove's "High Output Management": a manager's output is their organization's output, raised by high-leverage activities. Use when the user mentions "high output management", "managerial leverage", "one-on-ones", "1:1 agenda", "OKRs", "performance review", "task-relevant maturity", "delegation", "meeting overload", "new manager", "how do I run a 1:1", or "just got promoted to manager". Also trigger when structuring a manager's calendar and meeting cadence, designing team metrics, running…
Its SKILL.md is about 5.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including reference files (for example `references/case-studies.md`, `references/decisions-planning-okrs.md` and `references/indicators-and-production.md`).
It sits in Business, Finance & HR, covering Performance reviews and OKRs and executive reporting. The repository describes itself as: Wondel.ai Agent Skills — Business, Marketing, UX & Coding Frameworks from Bestselling Books. 50 skills + 12 guided journeys for Claude Code, Codex, Cursor & other agentskills.io… The licence is MIT.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit c172996. It shows what the files ask for, not the result of running them.
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.
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.
Links to these hosts (documentation or services it may open):
amazon.comFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
High Output Management loads about 5.1k tokens when it runs, and up to ~22k if it reads all its reference files. Until then it costs about 206 tokens; SKILL.md has 2,691 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.
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.
The full file from wondelai/skills at commit c172996, republished under its MIT licence (© wondelai). 2,691 words, ~5,135 tokens.
.claude/skills/high-output-management/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.Manage teams the way Andy Grove ran Intel: a manager's output is not what the manager does — it is what their organization produces. This skill turns High Output Management into auditable practice: production principles for knowledge work, output indicators, managerial leverage, meetings as the medium of management, clean decisions, OKRs, and a management style matched to task-relevant maturity.
A manager's output = the output of their organization + the output of the neighboring organizations under their influence. Nothing a manager does — emails, meetings, reviews, decisions — counts in itself; it counts only through how it raises that combined output. Since managerial time is the scarce input, the craft reduces to one question asked relentlessly: of everything I could do right now, what creates the most output per hour spent? Choose high-leverage activities; eliminate negative-leverage ones.
Goal: 10/10. Rate management practices, calendars, and processes 0-10 against the principles below. State the current score and the specific changes needed to reach 10/10.
Core concept: Grove's breakfast factory — deliver a three-minute egg, buttered toast, and hot coffee simultaneously, at acceptable quality and lowest cost — contains all of production: build the flow around the limiting step (the egg), fix problems at the lowest-value stage, batch where setup costs dominate, and choose deliberately between building to forecast and building to order. Every team — engineering, support, recruiting — runs a production line, whether or not anyone has drawn it.
Why it works: Knowledge work hides its assembly line, and invisible flow invites firefighting. Production thinking makes flow visible: once you know the limiting step, everything else gets scheduled around it; once defects are caught at the egg stage instead of on the customer's plate, fixing them costs a fraction.
Key insights:
Applications:
| Context | Application | Example |
|---|---|---|
| Sprint flow | Schedule around the limiting step | Review is the bottleneck → protect reviewer hours before starting new work |
| Quality gates | Inspect at the lowest-value stage | Spec review kills a flawed design before a three-week build |
| Hiring pipeline | Batch and build to forecast | Phone screens batched Tue/Thu; interviewer capacity staffed to the offer-date forecast |
Ethical boundary: Run systems hot, not humans — production thinking optimizes the work, never treats people as interchangeable machines.
See: references/indicators-and-production.md when finding a limiting step or building a dashboard — limiting-step analysis, worked indicator pairs, leading vs trend indicators, stagger charts, and how to run an operation review.
Core concept: Measure output, not activity — what the team shipped that survived, not how busy it looked. Pair every quantity indicator with a quality counterpart so neither can be optimized at the other's expense, favor leading indicators that buy time to act, and report forecasts in stagger charts that show how each forecast evolved.
Why it works: People do what management measures, so an unpaired indicator is an instruction to game it. The pair closes the loop: push throughput and the escape rate exposes the corner-cutting. Leading indicators and stagger charts convert measurement from autopsy to steering.
Key insights:
Applications:
| Context | Application | Example |
|---|---|---|
| Eng dashboard | Pair quantity with quality | Deploys/week paired with change-failure rate |
| Support ops | Output plus its quality shadow | Tickets resolved/day paired with reopen rate and CSAT |
| Quarterly forecast | Stagger chart | Re-forecast quarter-end ARR monthly; drift visible down each column |
Ethical boundary: Indicators measure the work, not the worker — used for surveillance, they teach people to optimize the number instead of the output.
Core concept: Leverage is the output created per unit of managerial time. High-leverage activities affect many people at once (training, well-prepared decisions, information gathering) or redirect months of work with a small, well-timed nudge. The calendar is the manager's production system: forecast the key events, batch the rest, and say no at the source when capacity is full.
Why it works: Managerial activities differ by orders of magnitude in output per hour — ninety minutes preparing a review shapes a year of someone's work, while a day of meddling subtracts output. A manager who lets the calendar happen to them spends prime hours on whatever shouted loudest.
Key insights:
Applications:
| Context | Application | Example |
|---|---|---|
| Week design | Forecast fixed events, batch the rest | 1:1s Tue-Wed mornings, PR reviews batched daily at 4pm, Monday deep-work block |
| Delegation | Monitoring depth by TRM | New hire's first migration: plan review plus daily spot checks; veteran's: rollout plan only |
| Interrupts | Convert random pings to office hours | Two daily drop-in slots replace ad hoc Slack escalations |
Ethical boundary: Leverage means multiplying others' output, never hoarding information or approvals until you become the bottleneck everyone must visit.
See: references/leverage-and-calendar.md when auditing a calendar or setting up delegation — the weekly leverage audit, positive/negative-leverage catalog, delegation protocol with TRM-based monitoring depth, calendar-redesign procedure, and interruption management.
Core concept: A meeting is not a symptom of bad management; it is where managerial work — gathering information, imparting it, deciding, nudging — actually happens. Process-oriented meetings (one-on-ones, staff meetings, operation reviews) run on a regular cadence and should carry the bulk of that work, roughly a quarter of the calendar. Mission-oriented meetings are ad hoc and exist solely to produce a decision.
Why it works: Regularity makes meetings cheap — standing agendas, shared expectations, zero setup cost — and starves the expensive kind: issues get caught small in 1:1s and staff meetings instead of exploding into emergency decision meetings. Grove's malorganization test: ad hoc mission-oriented meetings eating more than about a quarter of managerial time means the process is broken.
Key insights:
Applications:
| Context | Application | Example |
|---|---|---|
| New report | Weekly 1:1, their agenda | First 90 days: 60 minutes weekly; agenda arrives the day before |
| Team sync | Controlled free discussion | Two-minute updates, then debate on two pre-flagged issues |
| Recurring "urgent" meeting | Convert to process | Third ad hoc incident review this month becomes a standing ops review |
Ethical boundary: Hijacking the 1:1 for status extraction teaches people to stop bringing real problems — status belongs in writing.
See: references/meetings-and-one-on-ones.md when designing a meeting cadence or running a 1:1 — the full 1:1 playbook with agenda templates, staff-meeting design, operation-review roles, and meeting-cost math for when to kill a meeting.
Core concept: The ideal decision moves through free discussion (all views aired, dissent welcome), a clear decision (stated crisply — the more contentious, the crisper), and full support (disagree and commit). Decisions belong at the lowest competent level, closest to current technical knowledge. Planning runs the same arc: assess environmental demand, face present status honestly, close the gap — because the output of planning is decisions and actions taken now, not documents.
Why it works: Free discussion surfaces knowledge that lives at the edges; a clear decision prevents the costliest outcome, ambiguity; full support lets the organization move without unanimity. And today's firefight is yesterday's planning failure — planning works on next year's gap, not this week's smoke.
Key insights:
Applications:
| Context | Application | Example |
|---|---|---|
| Architecture choice | Free discussion → clear decision → commit | RFC debated one week; tech lead decides; dissent recorded, then full support |
| Decision prep | Six-question brief | "Pick payments vendor by Jun 30; platform PM decides; eng and finance consulted; VP ratifies" |
| Quarterly planning | Cascading OKRs | Company KR "checkout p95 under 800ms" becomes the platform team's objective |
See: references/decisions-planning-okrs.md when prepping a contentious decision or a planning cycle — the six-question brief, peer-group-syndrome counters, three-step planning, and a Grove-style OKR cascade with pitfalls.
Core concept: There is no universally good management style. The right style depends on the subordinate's task-relevant maturity (TRM) — their experience, training, and confidence for this specific task: low TRM calls for structured "how" instruction, medium for mutual reasoning about "what and why", high for agreed objectives with light monitoring. TRM is task-specific, not seniority, so style must shift the moment the task does.
Why it works: Mismatched style fails in both directions — hands-off at low TRM is abandonment dressed as empowerment; detailed instruction at high TRM is meddling that destroys ownership. The performance review is where the cost of a mismatch compounds: a year's feedback delivered in the wrong register lands as either neglect or insult.
Key insights:
Applications:
| Context | Application | Example |
|---|---|---|
| Newly promoted manager | Re-rate TRM per task | Weekly structured 1:1s on hiring and delegation, even for a star engineer |
| Review prep | Assess first, message second | Full written assessment, then the three messages that change next year |
| Team capability | Manager-taught training | EM personally teaches a four-session incident-response course |
See: references/case-studies.md when preparing a review or coaching a newly promoted manager — three worked scenarios (meeting-drowned new manager, velocity-up/quality-down, a botched review repaired with TRM coaching).
| Mistake | Why It Fails | Fix |
|---|---|---|
| Measuring activity, not output | Busyness is gameable and says nothing about results | Count what shipped and survived; pair quantity with quality |
| Publishing unpaired indicators | The team optimizes the number at quality's expense | Add the quality counterpart before the metric goes live |
| Skipping 1:1s when busy | Cancels the highest-leverage 90 minutes on the calendar | Treat 1:1s as forecasted production steps: reschedule, never drop |
| Decisions by rank | Knowledge lives at the lowest competent level; rank silences it | Free discussion, then a clear decision by the named decider |
| OKRs as a compensation formula | Guarantees sandbagged, safe objectives | Keep OKRs a stretch tool; comp weighs more than OKR hit rate |
| One management style for everyone | Abandons the new, smothers the experienced | Match style to task-relevant maturity, task by task |
| Catching defects at the highest-value stage | Cost multiplies at every stage a flaw survives | Inspect specs and plans, not just production |
| Saving feedback for the annual review | It detonates all at once; trust and the year are both lost | No-surprises rule: deliver feedback when the event happens |
| Question | If No | Action |
|---|---|---|
| Can you state your team's output in one sentence? | You are managing activity | Define output; build 4-6 indicators around it |
| Does every quantity metric have a quality pair? | The number is being gamed already | Pair it: throughput with escapes, closes with reopens |
| Do you know your team's limiting step? | Flow is built around the wrong constraint | Find where work queues longest; schedule around it |
| Did your reports set the agendas of their last 1:1s? | You ran status meetings instead | Hand the agenda to the subordinate; you take the notes |
| Is 1:1 frequency set by task-relevant maturity? | Someone is over- or under-managed | Weekly for new-to-task, monthly for veterans |
| Was your last big decision made at the lowest competent level? | Rank decided; knowledge watched | Name decider, consulted, and ratifier before the meeting |
| Would your team set the same OKRs if pay weren't attached? | Objectives are sandbagged | Decouple OKRs from the compensation formula |
| Have you personally taught your team anything this quarter? | Highest-leverage activity skipped | Schedule a manager-taught course now |
Andrew S. Grove (1936-2016) fled Hungary at twenty, became Intel's third employee, and rose to president, CEO, and chairman, driving the company's famous pivot from memory chips to microprocessors. Time's 1997 Man of the Year, he mentored a generation of Silicon Valley leaders, and his management-by-objectives system became the OKR method now standard across tech.
© wondelai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 5 other files (references) in high-output-management of wondelai/skills.
Open the folder on GitHubat commit c172996
High Output Management 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 |
|---|---|---|---|---|---|---|
| High Output Management this skillwondelai/skills | 2.4k | — | ~5.1k | Automated safety check: Pass | MIT | |
| Performance ReportAffitor/affiliate-skills | 701 | — | ~2.5k | Automated safety check: Pass | MIT | |
| Performance Managementsickn33/agentic-awesome-skills | 47k | 1 repos | ~4.1k | Automated safety check: Pass | MIT | |
| 65 Team Performance Review Globalminhnv0807/ai-business-skills | 609 | — | ~2.1k | Automated safety check: Pass | MIT | |
| 65 Team Performance Reviewminhnv0807/ai-business-skills | 609 | — | ~1.6k | Automated safety check: Pass | MIT | |
| Trading As Businessagentii-ai/agentii-investment-intelligence | 207 | — | ~655 | Automated safety check: Pass | Apache-2.0 |
Affitor/affiliate-skills
Generate affiliate performance reports with KPIs and recommendations.
sickn33/agentic-awesome-skills
Performance review register: review type, period, employee and reviewer, KPI, OKR and behaviour scores, overall rating, PIP and promotion flags, development plan.
minhnv0807/ai-business-skills
A skill your agent uses when a leader evaluates a marketing TEAM MEMBER using data — a KPI scorecard by role, strengths with real examples, areas to improve stated as observable behavior, a 30 and…
minhnv0807/ai-business-skills
Dung khi can danh gia CON NGUOI trong team marketing dua tren du lieu — KPI scorecard theo tung vai tro writer, designer, media buyer; diem manh co vi du that; diem can cai thien; development plan…
agentii-ai/agentii-investment-intelligence
Trading as a business, performance review process, trade journaling, capital allocation discipline, business infrastructure for traders, KPI tracking for trading operations
aaron-he-zhu/aaron-marketing-skills
A skill your agent uses when the user asks to "plan my launch tier", "how big should this launch be", or "build a launch risk register with kill criteria"; produces a tier decision (Tier 1 flagship…
wondelai/skills
Navigate the technology adoption lifecycle from early adopters to mainstream market.
wondelai/skills
Apply foundational design principles: affordances, signifiers, constraints, feedback, and conceptual models.
wondelai/skills
Run a structured 5-day process to prototype, test, and validate product ideas with real users.
wondelai/skills
Design habit-forming product loops using the Hook Model (Trigger, Action, Variable Reward, Investment).
wondelai/skills
Diagnose and fix retention problems using behavior design (B=MAP).
wondelai/skills
Design products and pricing around validated willingness to pay, from Ramanujam & Tacke's "Monetizing Innovation".
Categories
Manage for output using Grove's "High Output Management": a manager's output is their organization's output, raised by high-leverage activities. High Output Management is an agent skill from wondelai/skills. Manage for output using Grove's "High Output Management": a manager's output is their organization's output, raised by high-leverage activities.
High Output Management fits situations like: the user mentions high output management; managerial leverage; performance review; task-relevant maturity.
Run `npx skills add wondelai/skills --skill high-output-management -a claude-code`. Or copy the skill folder (high-output-management in wondelai/skills) into .claude/skills/high-output-management in your project. Claude Code loads it when a task matches its description.
Run `npx skills add wondelai/skills --skill high-output-management -a codex`. Or copy the skill folder (high-output-management in wondelai/skills) into .agents/skills/high-output-management in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wondelai/skills --skill high-output-management -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/high-output-management, .gemini/skills/high-output-management, .github/skills/high-output-management and .opencode/skills/high-output-management in your project.
SKILL.md names no scripts, command-line tools or credentials: High Output Management is instructions for the agent only.
SKILL.md names 1 domain. As links in the text: amazon.com. This is read from the text; nothing was executed.
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.
High Output Management is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 5.1k tokens (SKILL.md is roughly 21k 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 17k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with High Output Management: Performance Report (Affitor/affiliate-skills, 701 stars), Performance Management (sickn33/agentic-awesome-skills, 47k stars), 65 Team Performance Review Global (minhnv0807/ai-business-skills, 609 stars) and 65 Team Performance Review (minhnv0807/ai-business-skills, 609 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
wondelai (a GitHub organization) maintains it in wondelai/skills, which has 2,371 GitHub stars. The repository holds 62 skills in this directory. The repository was last updated on September 10, 2026.
Source: wondelai/skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.