Extract Design
Manavarya09/design-extract
Extract the full design language from any website URL. An agent skill from Manavarya09/design-extract.
Plan, build, and iterate UX-friendly frontend mockups via a ground→contract→mockup→test→fix→learn loop, acting as an expert UX designer who grounds every decision in externally documented public…
$ npx skills add BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install BlackBeltTechnology/pi-agent-dashboard frontend-mockup-loop --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/BlackBeltTechnology/pi-agent-dashboard.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/mockup-loop/.pi/skills/frontend-mockup-loop .claude/skills/frontend-mockup-loop && 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 "frontend-mockup-loop" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/mockup-loop/.pi/skills/frontend-mockup-loop into .claude/skills/frontend-mockup-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "frontend-mockup-loop", 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/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/mockup-loop/.pi/skills/frontend-mockup-loopType 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 BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install BlackBeltTechnology/pi-agent-dashboard frontend-mockup-loop --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/BlackBeltTechnology/pi-agent-dashboard.git skills-src && mkdir -p .agents/skills && cp -r skills-src/packages/mockup-loop/.pi/skills/frontend-mockup-loop .agents/skills/frontend-mockup-loop && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "frontend-mockup-loop" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/mockup-loop/.pi/skills/frontend-mockup-loop into .agents/skills/frontend-mockup-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "frontend-mockup-loop", 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 BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install BlackBeltTechnology/pi-agent-dashboard frontend-mockup-loop --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/BlackBeltTechnology/pi-agent-dashboard.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/packages/mockup-loop/.pi/skills/frontend-mockup-loop .cursor/skills/frontend-mockup-loop && 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 "frontend-mockup-loop" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/mockup-loop/.pi/skills/frontend-mockup-loop into .cursor/skills/frontend-mockup-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "frontend-mockup-loop", 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/BlackBeltTechnology/pi-agent-dashboard.git --path packages/mockup-loop/.pi/skills/frontend-mockup-loop--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 BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install BlackBeltTechnology/pi-agent-dashboard frontend-mockup-loop --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/BlackBeltTechnology/pi-agent-dashboard.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/packages/mockup-loop/.pi/skills/frontend-mockup-loop .gemini/skills/frontend-mockup-loop && 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 "frontend-mockup-loop" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/mockup-loop/.pi/skills/frontend-mockup-loop into .gemini/skills/frontend-mockup-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "frontend-mockup-loop", 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 BlackBeltTechnology/pi-agent-dashboard frontend-mockup-loopInstalls 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 BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/BlackBeltTechnology/pi-agent-dashboard.git skills-src && mkdir -p .github/skills && cp -r skills-src/packages/mockup-loop/.pi/skills/frontend-mockup-loop .github/skills/frontend-mockup-loop && 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 "frontend-mockup-loop" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/mockup-loop/.pi/skills/frontend-mockup-loop into .github/skills/frontend-mockup-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "frontend-mockup-loop", 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 BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install BlackBeltTechnology/pi-agent-dashboard frontend-mockup-loop --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/BlackBeltTechnology/pi-agent-dashboard.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/packages/mockup-loop/.pi/skills/frontend-mockup-loop .opencode/skills/frontend-mockup-loop && 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 "frontend-mockup-loop" agent skill from https://github.com/BlackBeltTechnology/pi-agent-dashboard/tree/develop/packages/mockup-loop/.pi/skills/frontend-mockup-loop into .opencode/skills/frontend-mockup-loop/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "frontend-mockup-loop", 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.
frontend-mockup-loopPlan, build, and iterate UX-friendly frontend mockups via a ground→contract→mockup→test→fix→learn loop, acting as an expert UX designer who grounds every decision in externally documented public…
Frontend Mockup Loop is an agent skill from BlackBeltTechnology/pi-agent-dashboard. Plan, build, and iterate UX-friendly frontend mockups via a ground→contract→mockup→test→fix→learn loop, acting as an expert UX designer who grounds every decision in externally documented public design rules (Nielsen heuristics, Laws of UX, WCAG, GOV.UK/USWDS/Material). Uses the bundled servemockup, scoremockup, and inituicontract tools plus a ui-contract.md design control plane to keep screens consistent. Works in any React/Tailwind/shadcn (or plain HTML) project. Use when designing new screens, adapting…
Its SKILL.md is about 2.9k 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 Frontend & Design, covering Design systems, Accessibility and CSS and styling. It works with shadcn/ui, Tailwind CSS and React. The repository describes itself as: Real-time web dashboard for pi coding-agent sessions. Multi-session view, live chat mirroring, integrated terminal, diff viewer, pi-flows execution, and mobile-first remote… The licence is MIT.
7 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 86e8e4d. 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.
Shell commands in SKILL.md call:
npxFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.
From 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.
Frontend Mockup Loop loads about 2.9k tokens when it runs. Until then it costs about 194 tokens; SKILL.md has 1,438 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 BlackBeltTechnology/pi-agent-dashboard at commit 86e8e4d, republished under its MIT licence (© BlackBeltTechnology). 1,438 words, ~2,904 tokens.
.claude/skills/frontend-mockup-loop/SKILL.md (or your agent's skills folder).A disciplined loop for designing frontend surfaces. It exists to defeat distributional convergence: an undirected agent regresses to the statistical mean of its training data — generic Inter font, a purple gradient, a centered hero. "Make it look better" just returns the average again.
The fix the whole agentic-design field converged on, and what this loop enforces every time:
This skill is paired with an extension that registers five tools:
serve_mockup, score_mockup, init_ui_contract, list_design_systems,
validate_mockup.
The loop runs design-system agnostic by default (generic anti-slop rubric).
To target a specific system, pick a preset and pass its id to the tools'
system param. v1 presets (list_design_systems enumerates them):
| id | system | platform | substrate |
|---|---|---|---|
shadcn | shadcn/ui + Tailwind | web | HTML + Tailwind |
mui | Material UI | web | HTML |
material-3 | Material Design 3 | web | HTML |
fluent-2 | Fluent 2 | web | HTML |
apple-hig | Apple HIG | iOS | HTML approximation → SwiftUI on promote |
With a system selected: init_ui_contract{system} writes that system's DTCG
token contract (from a bundled, offline snapshot; refresh:true re-fetches
upstream), score_mockup{system} swaps in the system's boolean rubric, and
validate_mockup{system,dir} runs the gated pipeline.
Validation is layered. Gates block pass; advisory layers only score
and drive the fix loop (LLM visual scores skew positive — never hard-block):
hig-doctor / material3-mcp etc., advisory,
shelled out only if installed (absent → skipped + noted, never errors).score = pass/N computed in
code, advisory.validate_mockup returns { gates, advisory, pass }; pass is gate-only.
Apple publishes no token JSON, so apple-hig ships a hand-authored rule pack
(presets-data/apple-hig/rules.md). Render an HTML approximation of the iOS
screen so serve_mockup can serve it and hig-doctor (if installed) can audit
it — no SwiftUI/Xcode required in-loop:
font-family: -apple-system, "SF Pro Text", system-ui.padding: env(safe-area-inset-top) … env(safe-area-inset-bottom).On PROMOTE, optionally emit real SwiftUI — validated on source by
hig-doctor / orchard-hig (no live browser preview; real-device fidelity
needs macOS/Xcode). SwiftUI is never required for the in-loop preview.
Rule: ground every UX decision in an externally documented, public-facing design rule — never invent one. When you make a call, you must be able to name the rule and cite its public source. "I think it looks better" is not a reason; "Hick's Law — reduce the choices here (lawsofux.com/hicks-law)" is.
The full citable rule corpus lives in
references/ux-best-practices.md:
Nielsen's 10 heuristics, Laws of UX, Gestalt, cognitive load, per-component
pattern rules, the 5-step expert evaluation protocol, and a 22-item checkable
rubric seed. Read it before designing or reviewing.
Source order (adapt, don't copy): the selected design system's documented guidance first → then the universal sources, in licensing-safe order (USWDS is CC0; GOV.UK is OGL; NN/g + Laws of UX cite-with-attribution; Material/Carbon are Apache-2.0). Adapt the principle to this product; never copy proprietary assets/text (Apple HIG, Refactoring UI, Mobbin).
Anti-slop companion (advisory). For the AI-tell layer — the countable
signatures an undirected model defaults to (AI-purple, Inter-everywhere,
em-dashes, div-based fake screenshots, eyebrow-per-section, Jane Doe / Acme
data) — pull the anti-slop-frontend skill
(@blackbelt-technology/anti-slop-frontend). It is advisory only: its tells
feed the FIX step's defect list (step 5), but they NEVER override this loop's
hard gates. When an anti-slop tell conflicts with a cited public rule or the
WCAG-AA / severity-4 floor, the cited rule and the gate win. Apply its Part A
(universal) to any surface; skip its Part B (marketing-only) for product UI.
Designing or refining any frontend surface — new screens, redesigns, or a consistency pass across existing screens. Skip for trivial one-class tweaks. Not for backend/protocol work.
Two grounds, both external:
--background, --primary, --radius), spacing, dark + light.references/ux-best-practices.md and the
selected design system's public guidance. Identify the specific patterns and
laws that govern this surface (e.g. a form → NN/g web-form-design + GOV.UK
error-summary; a nav → Hick's Law + hamburger-menu guidance).Designing without either ground produces a parallel style that looks "off" and a UX that violates well-known rules — the opposite of adapting documented design.
Read or scaffold ui-contract.md (run init_ui_contract). It is the single
source of truth for cross-screen properties: color ramps, spacing scale, type
scale, radius, elevation, motion, component invariants. Every value
references a design token — never a raw hex or px literal. If a surface needs
a token that doesn't exist, add it to the theme layer first, then cite it in
the contract. This file is what stops screens from drifting apart.
Build standalone HTML/Tailwind mockups grounded in steps 1–2. Serve them with
serve_mockup and hand back the clickable local + LAN URL (the LAN URL
opens on a phone) — not a screenshot — so the human reacts to a real page.
Render dark AND light.
Run score_mockup to capture full-page screenshots at mobile/tablet/desktop
widths, then apply the 5-step protocol from references/ux-best-practices.md:
Score = passed / N, derived in code — never a subjective "looks good" and never a free-form float (LLM visual scores skew positive). Each failed check cites the rule it violates.
Apply the top failing item, re-serve, re-score. Loop 3–5 until every rubric line passes in both themes at all three breakpoints.
Translate the approved HTML direction into real React/shadcn components. Do this in an ISOLATED environment (temp workspace, non-production ports), never against a live server. Map the mockup's tokens 1:1 so shipped code matches the approved mockup with zero drift.
Record durable taste decisions so the next run starts smarter: stable rules →
agent memory; repo design rules → patch ui-contract.md; one-off rationale →
the change's notes.
serve_mockup{dir, port?, stop?} — Node static server on 0.0.0.0; returns
local + LAN URLs. Zero external deps.score_mockup{url, widths?, outDir?, system?} — Playwright breakpoint screenshots +
scoring rubric. Chromium is declared in this package's pi.tools (optional
pw-browser probe); absent → install guidance via the registry's Install
dropdown or pi-dashboard-ensure (npx playwright@1.62.1 install chromium).init_ui_contract{path?, force?, system?, refresh?} — scaffold the
token-referencing contract. With system, write that preset's DTCG contract
(offline snapshot; refresh re-fetches upstream first). No system →
generic blank template (unchanged).list_design_systems{} — enumerate the preset registry (id, label, platform,
substrate, validators).validate_mockup{system, url?, dir?} — run L1+L2 (gates) + L3+L4 (advisory);
returns { gates, advisory, pass }. Pass dir so L1/L2 can scan the source.references/ux-best-practices.md).ui-contract.md exists; every value references a token; the new surface's
tokens appear in it.© BlackBeltTechnology, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in packages/mockup-loop/.pi/skills/frontend-mockup-loop of BlackBeltTechnology/pi-agent-dashboard.
Open the folder on GitHubat commit 86e8e4d
Frontend Mockup Loop 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 |
|---|---|---|---|---|---|---|
| Frontend Mockup Loop this skillBlackBeltTechnology/pi-agent-dashboard | 315 | — | ~2.9k | Automated safety check: Pass | MIT | |
| Extract DesignManavarya09/design-extract | 4.2k | — | ~786 | Automated safety check: Notes | MIT | |
| UI Design Systemtry-works/role-model | 118 | — | ~5k | Automated safety check: Pass | MIT | |
| Audit AI Frontendjxnl/personal-monorepo-template | 563 | — | ~1.3k | Automated safety check: Pass | None | |
| Light Frontend DesignLight0305/Light-skills | 640 | — | ~3.1k | Automated safety check: Pass | MIT | |
| Frontend Designseb1n/awesome-ai-agent-skills | 206 | — | ~2.3k | Automated safety check: Pass | MIT |
Manavarya09/design-extract
Extract the full design language from any website URL. An agent skill from Manavarya09/design-extract.
try-works/role-model
React UI component systems with TailwindCSS + Radix + shadcn/ui.
jxnl/personal-monorepo-template
Audit AI-generated, AI-shaped, or AI-looking frontend code, UI screenshots, and design diffs.
Light0305/Light-skills
Light 按需工程技能·前端设计:把模糊的「做个好看的界面」落成能跑的 React/Tailwind/shadcn 代码 + 设计决策说明—— 有视觉记忆点(signature element)、风格自洽(design tokens 一致)、适配场景(学术海报/数据大屏/管理后台/移动端/营销 landing 信息密度各不同)、反「一眼 AI」(紫蓝渐变/Inter/16px 圆角/巨型…
seb1n/awesome-ai-agent-skills
Design and build production-ready frontend interfaces with design systems, responsive layouts, accessible components, and dark mode support.
Ohh-889/skyroc
Create beautiful, accessible user interfaces with shadcn/ui components (built on Radix UI + Tailwind), Tailwind CSS utility-first styling, and canvas-based visual designs.
BlackBeltTechnology/pi-agent-dashboard
Browser automation via the agent-browser CLI. An agent skill from BlackBeltTechnology/pi-agent-dashboard.
BlackBeltTechnology/pi-agent-dashboard
Diagnose failed GitHub Actions runs for pi-agent-dashboard: the 11-file workflow taxonomy, affected-test selection, the release pipeline, known failure modes, and how to read gh run logs and…
BlackBeltTechnology/pi-agent-dashboard
Diagnose problems in the running pi-agent-dashboard system: server.log, /api/health, bridge WebSocket connectivity, vitest triage, known-issue FAQ entries.
BlackBeltTechnology/pi-agent-dashboard
Disciplined implementation in pi-agent-dashboard: the rebuild matrix (extension→reload, server→restart, client→build+restart, openspec-apply→full rebuild) plus the project's code discipline rules.
BlackBeltTechnology/pi-agent-dashboard
Monitor and control the pi-dashboard server. An agent skill from BlackBeltTechnology/pi-agent-dashboard.
BlackBeltTechnology/pi-agent-dashboard
Turn a pi session into a Markdown "how-we-did-it" collaboration guideline: reads the session's JSONL transcript and synthesizes a reusable playbook of which prompts worked, what had to be steered…
Works with
Categories
Plan, build, and iterate UX-friendly frontend mockups via a ground→contract→mockup→test→fix→learn loop, acting as an expert UX designer who grounds every decision in externally documented public…. Frontend Mockup Loop is an agent skill from BlackBeltTechnology/pi-agent-dashboard.UK/USWDS/Material).
Frontend Mockup Loop fits situations like: designing new screens; adapting existing UI; enforcing cross-screen consistency; doing a UX review.
Run `npx skills add BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a claude-code`. Or copy the skill folder (packages/mockup-loop/.pi/skills/frontend-mockup-loop in BlackBeltTechnology/pi-agent-dashboard) into .claude/skills/frontend-mockup-loop in your project. Claude Code loads it when a task matches its description.
Run `npx skills add BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a codex`. Or copy the skill folder (packages/mockup-loop/.pi/skills/frontend-mockup-loop in BlackBeltTechnology/pi-agent-dashboard) into .agents/skills/frontend-mockup-loop 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 BlackBeltTechnology/pi-agent-dashboard --skill frontend-mockup-loop -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/frontend-mockup-loop, .gemini/skills/frontend-mockup-loop, .github/skills/frontend-mockup-loop and .opencode/skills/frontend-mockup-loop in your project.
Going by SKILL.md and its folder, Frontend Mockup Loop needs the command-line tools its instructions call (npx). Our summary lists: Node.js.
SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. 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.
Frontend Mockup Loop is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Frontend Mockup Loop: Extract Design (Manavarya09/design-extract, 4.2k stars), UI Design System (try-works/role-model, 118 stars), Audit AI Frontend (jxnl/personal-monorepo-template, 563 stars) and Light Frontend Design (Light0305/Light-skills, 640 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
BlackBeltTechnology (a GitHub organization) maintains it in BlackBeltTechnology/pi-agent-dashboard, which has 315 GitHub stars. The repository holds 66 skills in this directory. The repository was last updated on October 8, 2026.
Source: BlackBeltTechnology/pi-agent-dashboard on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.