CSS At Property
thedaviddias/Front-End-Checklist
A skill your agent uses when implementing animated gradients, complex CSS transitions that involve custom property values, or building a typed design token system where custom property misuse should…
A skill your agent uses when property-service operations need an AI plus ontology plus DMAIC design for work orders, dispatch, quotes, evidence, CTQ metrics, and control dashboards.
MITAuto-check passed
Install AI Six Sigma Property Os
$ npx skills add Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills ai-six-sigma-property-os --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/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-six-sigma-property-os .claude/skills/ai-six-sigma-property-os && 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 "ai-six-sigma-property-os" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/ai-six-sigma-property-os into .claude/skills/ai-six-sigma-property-os/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-six-sigma-property-os", 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/Mark393295827/third-brain-v7-skills/tree/main/skills/ai-six-sigma-property-osType 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 Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills ai-six-sigma-property-os --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-six-sigma-property-os .agents/skills/ai-six-sigma-property-os && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-six-sigma-property-os" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/ai-six-sigma-property-os into .agents/skills/ai-six-sigma-property-os/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-six-sigma-property-os", 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 Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills ai-six-sigma-property-os --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-six-sigma-property-os .cursor/skills/ai-six-sigma-property-os && 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 "ai-six-sigma-property-os" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/ai-six-sigma-property-os into .cursor/skills/ai-six-sigma-property-os/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-six-sigma-property-os", 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/Mark393295827/third-brain-v7-skills.git --path skills/ai-six-sigma-property-os--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 Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills ai-six-sigma-property-os --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-six-sigma-property-os .gemini/skills/ai-six-sigma-property-os && 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 "ai-six-sigma-property-os" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/ai-six-sigma-property-os into .gemini/skills/ai-six-sigma-property-os/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-six-sigma-property-os", 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 Mark393295827/third-brain-v7-skills ai-six-sigma-property-osInstalls 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 Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-six-sigma-property-os .github/skills/ai-six-sigma-property-os && 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 "ai-six-sigma-property-os" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/ai-six-sigma-property-os into .github/skills/ai-six-sigma-property-os/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-six-sigma-property-os", 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 Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Mark393295827/third-brain-v7-skills ai-six-sigma-property-os --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Mark393295827/third-brain-v7-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-six-sigma-property-os .opencode/skills/ai-six-sigma-property-os && 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 "ai-six-sigma-property-os" agent skill from https://github.com/Mark393295827/third-brain-v7-skills/tree/main/skills/ai-six-sigma-property-os into .opencode/skills/ai-six-sigma-property-os/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-six-sigma-property-os", 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
ai-six-sigma-property-os- GitHub stars
- 141
- Token cost
- ~1.4k tokens
- SKILL.md length
- 625 words
- Files
- 2 (incl. references)
- Skills in repo
- 21
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when property-service operations need an AI plus ontology plus DMAIC design for work orders, dispatch, quotes, evidence, CTQ metrics, and control dashboards.
- Works in 8 steps: Define: set customer pain, process… → Measure: map each CTQ to formula, source… → Analyze: for red metrics, use process… → …
- Property-service operations need an AI plus ontology plus DMAIC design for work orders
- SKILL.md covers Usage Template, Workflow, Failure Protocol and Output Contract, plus 3 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
AI Six Sigma Property Os is an agent skill from Mark393295827/third-brain-v7-skills. Use when property-service operations need an AI plus ontology plus DMAIC design for work orders, dispatch, quotes, evidence, CTQ metrics, and control dashboards.
Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/property-control-model.md`).
The repository describes itself as: agent wiki +engineering skills. The licence is MIT.
When your agent uses it
- Property-service operations need an AI plus ontology plus DMAIC design for work orders
- Control dashboards
Example prompts
- “/ai-six-sigma-property-os”
Workflow steps
8 steps, taken from the first numbered list in SKILL.md.
- Define: set customer pain, process boundary, work-order type, SLA, CTQs, and excluded scope.
- Measure: map each CTQ to formula, source field, owner, baseline, target, and data-quality check.
- Analyze: for red metrics, use process bottlenecks, fishbone categories, and 5 Why until the cause can change a rule, field, SOP, training…
- Improve: propose one bounded change with hypothesis, owner, rollout cohort, budget, success/guardrail metrics, and rollback trigger.
- Control: define dashboard, alert, approval, exception, audit sample, and review cadence.
- Define ontology objects and legal work-order transitions before assigning agent roles.
- Give each agent a bounded input, action, output, confidence, evidence, and human gate.
- Keep customer-facing quotes, pricing/policy changes, low-confidence dispatch, safety, compliance, privacy, payment, case closure, and…
What it can do on your machine
Read from SKILL.md and the folder at commit 5a64514. 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
AI Six Sigma Property Os loads about 1.4k tokens when it runs, and up to ~2.2k if it reads all its reference files. Until then it costs about 47 tokens; SKILL.md has 625 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 Mark393295827/third-brain-v7-skills at commit 5a64514, republished under its MIT licence (© Mark393295827). 625 words, ~1,410 tokens.
Download SKILL.mdSave it as
.claude/skills/ai-six-sigma-property-os/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- ai-six-sigma-property-os
- description
- Use when property-service operations need an AI plus ontology plus DMAIC design for work orders, dispatch, quotes, evidence, CTQ metrics, and control dashboards.
- metadata.version
- 8.1.0
- metadata.updated
- 2026-08-18
- metadata.profile
- high-risk
- metadata.assumes
- A real or planned service workflow has identifiable customers, work orders, workers, quotes, evidence, and accountable operators.
- metadata.conflicts_with
- Automating undefined processes, hiding safety or pricing decisions, or expanding into a full ERP before the core quality loop works.
AI Six Sigma Property OS
<skill_contract>
<input>Named property-service workflow, actors, evidence, CTQs, approval boundaries, and MVP constraints.</input>
<output>A bounded ontology, DMAIC control plan, agent roles, gates, metrics, and rollback-ready MVP design.</output>
<done>Every proposed state transition and CTQ has an owner, evidence source, verifier, approval gate, and control receipt.</done>
<non_goals>Full ERP replacement, autonomous safety or pricing decisions, and automation of undefined processes.</non_goals>
Ontology defines the operating world; bounded agents execute and audit; DMAIC improves rules from work-order evidence. Design the management system before software scope. Load references/property-control-model.md for the baseline ontology, CTQs, and state machine.
Usage Template
Provide: business type, stage, first workflow, current process/data, service standards, approval boundaries, failure history, and MVP budget. Optional: table schemas and sample work orders.
Workflow
<intake>Verify the operating objective and select one first workflow: classification, dispatch recommendation, quote draft, evidence audit, or quality dashboard. Map actors, current states, systems of record, customer/safety impact, and data maturity.
</intake><unknowns_gate>
If service standard, accountable owner, safety boundary, or system of record is missing, return NEEDS_INPUT. Treat absent baseline data as a Measure-phase task; never invent CTQ thresholds or automation accuracy.
</unknowns_gate>
<execute>- Define: set customer pain, process boundary, work-order type, SLA, CTQs, and excluded scope.
- Measure: map each CTQ to formula, source field, owner, baseline, target, and data-quality check.
- Analyze: for red metrics, use process bottlenecks, fishbone categories, and 5 Why until the cause can change a rule, field, SOP, training item, or threshold.
- Improve: propose one bounded change with hypothesis, owner, rollout cohort, budget, success/guardrail metrics, and rollback trigger.
- Control: define dashboard, alert, approval, exception, audit sample, and review cadence.
- Define ontology objects and legal work-order transitions before assigning agent roles.
- Give each agent a bounded input, action, output, confidence, evidence, and human gate.
- Keep customer-facing quotes, pricing/policy changes, low-confidence dispatch, safety, compliance, privacy, payment, case closure, and disciplinary action under human approval.
Use an independent quality reviewer for closure and abnormal cases. Rollback must restore the prior rule/SOP/version without deleting work-order evidence.
</execute><evaluate>Trace every agent action and dashboard metric to a field, state transition, CTQ, owner, and gate. Simulate normal, missing-data, exception, rework, and cancellation paths. Reject modules with no objective metric or safe manual fallback.
</evaluate><retry_policy>
max_attempts: 2. Retry design only after changing scope, data definition, rule, or control. Stop on repeated missing baseline, unsafe transition, or NO_PROGRESS; escalate the decision to the accountable operator.
</retry_policy>
<state_contract>
Persist {run_id, status, attempt, budget, evidence, unknowns, last_error, next_action} plus process version, ontology, state machine, CTQ dictionary, agent contracts, approval matrix, experiment cohort, exceptions, independent review, and rollback receipt.
</state_contract>
Show full SKILL.md (189 more words)Show less
Failure Protocol
NEEDS_INPUT: owner, service standard, safety boundary, or data source is unclear.INSUFFICIENT_EVIDENCE: baseline cannot support threshold or automation decisions.BLOCKED_PERMISSION: required approval/system access is absent; remain in manual mode.VERIFY_FAILED: state, metric, or agent action is not traceable; block rollout.NO_PROGRESS: two changed designs fail the same control.max_attempts: 2.BUDGET_STOP: preserve the manual workflow and return the smallest measurable MVP.
Output Contract
Return status, result (DMAIC memo, ontology, states, CTQs, agent/gate matrix, dashboard, MVP), evidence, unknowns, and next_action with approval and rollback condition.
Edge Cases
- Quote automation has no reliable material-cost feed: generate an internal draft with uncertainty and require human pricing approval; do not send it.
- Worker recommendation is high-confidence but violates access/safety rules: rules override score and the case moves to exception review.
Success Metrics
- One bounded workflow is measurable end to end.
- Every automated action maps to state, evidence, CTQ, owner, and human gate.
- Red metrics produce controlled countermeasures rather than commentary.
Quality Gates
- MVP excludes unrelated ERP/marketplace/payroll scope.
- CTQs have formulas, source fields, baselines, and owners.
- Independent review, approval, manual fallback, and rollback are explicit.
- Exception and rework paths were simulated.
</skill_contract>
© Mark393295827, 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 (references) in skills/ai-six-sigma-property-os of Mark393295827/third-brain-v7-skills.
- SKILL.md
- references/property-control-model.md
Open the folder on GitHubat commit 5a64514
Compare with similar skills
AI Six Sigma Property Os 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 |
|---|---|---|---|---|---|---|
| AI Six Sigma Property Os this skillMark393295827/third-brain-v7-skills | 141 | — | ~1.4k | Automated safety check: Pass | MIT | |
| CSS At Propertythedaviddias/Front-End-Checklist | 74k | — | ~602 | Automated safety check: Pass | MIT | |
| Logical Propertiesthedaviddias/Front-End-Checklist | 74k | — | ~526 | Automated safety check: Pass | MIT | |
| Ontology Term ResolutionK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.6k | Automated safety check: Notes | MIT | |
| Setting Up Warehouse PropertiesPostHog/posthog | 40k | — | ~2.3k | Automated safety check: Pass | Custom licence | |
| CSS Custom Propertiesthedaviddias/Front-End-Checklist | 74k | — | ~492 | Automated safety check: Pass | MIT |
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Questions about AI Six Sigma Property Os
What does AI Six Sigma Property Os do?
A skill your agent uses when property-service operations need an AI plus ontology plus DMAIC design for work orders, dispatch, quotes, evidence, CTQ metrics, and control dashboards. AI Six Sigma Property Os is an agent skill from Mark393295827/third-brain-v7-skills. Use when property-service operations need an AI plus ontology plus DMAIC design for work orders, dispatch, quotes, evidence, CTQ metrics, and control dashboards.
When should I use AI Six Sigma Property Os?
AI Six Sigma Property Os fits situations like: property-service operations need an AI plus ontology plus DMAIC design for work orders; control dashboards.
How do I install AI Six Sigma Property Os in Claude Code?
Run `npx skills add Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a claude-code`. Or copy the skill folder (skills/ai-six-sigma-property-os in Mark393295827/third-brain-v7-skills) into .claude/skills/ai-six-sigma-property-os in your project. Claude Code loads it when a task matches its description.
How do I install AI Six Sigma Property Os in Codex?
Run `npx skills add Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a codex`. Or copy the skill folder (skills/ai-six-sigma-property-os in Mark393295827/third-brain-v7-skills) into .agents/skills/ai-six-sigma-property-os in your project. Codex loads it when a task matches its description.
Can I use AI Six Sigma Property Os 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 Mark393295827/third-brain-v7-skills --skill ai-six-sigma-property-os -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-six-sigma-property-os, .gemini/skills/ai-six-sigma-property-os, .github/skills/ai-six-sigma-property-os and .opencode/skills/ai-six-sigma-property-os in your project.
What does AI Six Sigma Property Os need to run?
SKILL.md names no scripts, command-line tools or credentials: AI Six Sigma Property Os is instructions for the agent only.
Does AI Six Sigma Property Os 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 AI Six Sigma Property Os 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 AI Six Sigma Property Os use?
AI Six Sigma Property Os 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 AI Six Sigma Property Os use?
About 1.4k tokens (SKILL.md is roughly 5.6k 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 826 tokens, read only when the agent opens those files.
What are the alternatives to AI Six Sigma Property Os?
Skills that share tags, products or a category with AI Six Sigma Property Os: CSS At Property (thedaviddias/Front-End-Checklist, 74k stars), Logical Properties (thedaviddias/Front-End-Checklist, 74k stars), Ontology Term Resolution (K-Dense-AI/scientific-agent-skills, 48k stars) and Setting Up Warehouse Properties (PostHog/posthog, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains AI Six Sigma Property Os?
Mark393295827 (a GitHub user) maintains it in Mark393295827/third-brain-v7-skills, which has 141 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on September 19, 2026.
Source: Mark393295827/third-brain-v7-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.