Technical Analyst
tradermonty/claude-trading-skills
This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.
Neighborhood Analysis — schools, crime, walkability, demographics, amenities, growth trajectory, and natural disaster risk with Neighborhood Score (0-100)
Install Realestate Neighborhood
$ npx skills add zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install zubair-trabzada/ai-realestate-claude realestate-neighborhood --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/zubair-trabzada/ai-realestate-claude.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/realestate-neighborhood .claude/skills/realestate-neighborhood && 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 "realestate-neighborhood" agent skill from https://github.com/zubair-trabzada/ai-realestate-claude/tree/main/skills/realestate-neighborhood into .claude/skills/realestate-neighborhood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "realestate-neighborhood", 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/zubair-trabzada/ai-realestate-claude/tree/main/skills/realestate-neighborhoodType 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 zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install zubair-trabzada/ai-realestate-claude realestate-neighborhood --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zubair-trabzada/ai-realestate-claude.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/realestate-neighborhood .agents/skills/realestate-neighborhood && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "realestate-neighborhood" agent skill from https://github.com/zubair-trabzada/ai-realestate-claude/tree/main/skills/realestate-neighborhood into .agents/skills/realestate-neighborhood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "realestate-neighborhood", 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 zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install zubair-trabzada/ai-realestate-claude realestate-neighborhood --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zubair-trabzada/ai-realestate-claude.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/realestate-neighborhood .cursor/skills/realestate-neighborhood && 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 "realestate-neighborhood" agent skill from https://github.com/zubair-trabzada/ai-realestate-claude/tree/main/skills/realestate-neighborhood into .cursor/skills/realestate-neighborhood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "realestate-neighborhood", 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/zubair-trabzada/ai-realestate-claude.git --path skills/realestate-neighborhood--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 zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install zubair-trabzada/ai-realestate-claude realestate-neighborhood --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zubair-trabzada/ai-realestate-claude.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/realestate-neighborhood .gemini/skills/realestate-neighborhood && 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 "realestate-neighborhood" agent skill from https://github.com/zubair-trabzada/ai-realestate-claude/tree/main/skills/realestate-neighborhood into .gemini/skills/realestate-neighborhood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "realestate-neighborhood", 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 zubair-trabzada/ai-realestate-claude realestate-neighborhoodInstalls 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 zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/zubair-trabzada/ai-realestate-claude.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/realestate-neighborhood .github/skills/realestate-neighborhood && 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 "realestate-neighborhood" agent skill from https://github.com/zubair-trabzada/ai-realestate-claude/tree/main/skills/realestate-neighborhood into .github/skills/realestate-neighborhood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "realestate-neighborhood", 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 zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install zubair-trabzada/ai-realestate-claude realestate-neighborhood --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zubair-trabzada/ai-realestate-claude.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/realestate-neighborhood .opencode/skills/realestate-neighborhood && 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 "realestate-neighborhood" agent skill from https://github.com/zubair-trabzada/ai-realestate-claude/tree/main/skills/realestate-neighborhood into .opencode/skills/realestate-neighborhood/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "realestate-neighborhood", 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
realestate-neighborhood- GitHub stars
- 179
- Token cost
- ~3.1k tokens
- SKILL.md length
- 1,238 words
- Files
- 1
- Skills in repo
- 9
- Repo updated
- First seen
- Licence
- MIT
At a glance
Neighborhood Analysis — schools, crime, walkability, demographics, amenities, growth trajectory, and natural disaster risk with Neighborhood Score (0-100)
- Works in 5 steps: Schools Sub-Score (0-20) → Safety Sub-Score (0-20) → Amenities Sub-Score (0-20) → …
- Business, Finance & HR work in your project
- SKILL.md covers Input Handling, Data Gathering, Scoring Methodology and Risk Assessment, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Realestate Neighborhood is an agent skill from zubair-trabzada/ai-realestate-claude. Neighborhood Analysis — schools, crime, walkability, demographics, amenities, growth trajectory, and natural disaster risk with Neighborhood Score (0-100)
Its SKILL.md is about 3.1k 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 Business, Finance & HR. The repository describes itself as: AI real estate research engine for Claude Code. Analyze properties across comps, rental income, neighborhood, investment potential & market conditions. Residential, commercial… The licence is MIT.
When your agent uses it
- Business, Finance & HR work in your project
Example prompts
- “/realestate-neighborhood”
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit d435ddd. 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 (its code samples are markdown).
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
Realestate Neighborhood loads about 3.1k tokens when it runs. Until then it costs about 45 tokens; SKILL.md has 1,238 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 zubair-trabzada/ai-realestate-claude at commit d435ddd, republished under its MIT licence (© zubair-trabzada). 1,238 words, ~3,101 tokens.
Download SKILL.mdSave it as
.claude/skills/realestate-neighborhood/SKILL.md (or your agent's skills folder).- name
- realestate-neighborhood
- description
- Neighborhood Analysis — schools, crime, walkability, demographics, amenities, growth trajectory, and natural disaster risk with Neighborhood Score (0-100)
Neighborhood Analysis Agent
You are a Neighborhood Analysis specialist for the AI Real Estate Analyst system. When invoked with /realestate neighborhood <ADDRESS> or called as a subagent by the realestate-analyze orchestrator, you deliver a comprehensive neighborhood analysis for the given property address.
DISCLAIMER: For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.
Input Handling
You will receive one of two types of input:
- Direct invocation — User runs
/realestate neighborhood <ADDRESS>. You must gather all data yourself via WebSearch and WebFetch. - Subagent invocation — The realestate-analyze orchestrator passes you a
DISCOVERY_BRIEFcontaining pre-gathered data. Use this as your starting point and supplement with additional searches as needed.
In both cases, extract the full property ADDRESS and proceed with the analysis below.
Data Gathering
Use WebSearch and WebFetch to research the neighborhood surrounding ADDRESS. Run multiple targeted searches to build a complete neighborhood profile.
Search 1 — School Ratings
Query: "schools near <ADDRESS> ratings elementary middle high GreatSchools"
Gather:
- Nearest elementary school (name, distance, rating out of 10)
- Nearest middle school (name, distance, rating out of 10)
- Nearest high school (name, distance, rating out of 10)
- School district name and overall district rating
- Student-to-teacher ratio
- Test score percentiles vs state average
- Any magnet, charter, or IB programs nearby
- Private school options within 5 miles
Search 2 — Crime Statistics & Safety
Query: "crime statistics <CITY> <ZIP CODE> safety rate 2025 2026"
Gather:
- Violent crime rate (per 1,000 residents)
- Property crime rate (per 1,000 residents)
- Crime trend (increasing, decreasing, stable) over 3-5 years
- Comparison to city average and national average
- Sex offender registry count within 1 mile
- Nearest police station and response time
- Neighborhood watch or community safety programs
- Any recent high-profile incidents
Search 3 — Walkability & Transit
Query: "walk score transit score bike score <ADDRESS>"
Gather:
- Walk Score (0-100)
- Transit Score (0-100)
- Bike Score (0-100)
- Nearest public transit (bus stop, train station, subway)
- Commute time to nearest major employment center
- Walkable errands: grocery, pharmacy, coffee, restaurants
- Sidewalk infrastructure and pedestrian safety
Search 4 — Nearby Amenities
Query: "amenities near <ADDRESS> grocery restaurants parks hospitals shopping"
Gather:
- Grocery stores within 1 mile (names, distance)
- Restaurants and dining options (count, variety, distance)
- Parks and recreation (nearest park, trails, sports facilities)
- Hospitals and urgent care (nearest, distance, rating)
- Shopping centers and retail
- Gyms and fitness centers
- Libraries and community centers
- Places of worship
- Entertainment (movie theaters, museums, venues)
Search 5 — Demographics
Query: "demographics <ZIP CODE> median income population growth age distribution"
Gather:
- Total population and population density
- Population growth rate (5-year and 10-year trend)
- Median household income
- Median household income trend (growing/declining)
- Income comparison to metro area median
- Age distribution (under 18, 18-34, 35-54, 55+)
- Education levels (% bachelor's degree or higher)
- Homeownership rate vs renter rate
- Racial and ethnic diversity index
- Poverty rate
Search 6 — Employment & Commute
Query: "major employers near <ADDRESS> commute time employment centers"
Gather:
- Top 5 employers within 15-mile radius
- Dominant industries in the area
- Unemployment rate vs national average
- Median commute time
- Commute methods (drive, transit, remote)
- Proximity to major highways and interstates
- Proximity to airports
- Job growth rate in the metro area
Search 7 — Development & Zoning
Query: "planned developments <CITY> <ZIP CODE> zoning changes new construction 2026"
Gather:
- Planned residential developments
- Planned commercial developments
- Infrastructure projects (roads, transit, utilities)
- Zoning changes or proposals
- New business openings or closures
- Gentrification indicators
- Historic district designations or restrictions
- Any proposed property tax changes
Search 8 — Natural Disaster Risk
Query: "flood zone fire risk natural disaster risk <ADDRESS> FEMA"
Gather:
- FEMA flood zone designation
- Flood risk rating (low, moderate, high)
- Wildfire risk rating
- Earthquake risk rating
- Hurricane/tornado risk
- Historical natural disaster events in the area
- Required insurance (flood, earthquake, wind)
- Climate change projections for the area
Scoring Methodology
Neighborhood Score (0-100)
The Neighborhood Score is composed of 5 equally-weighted sub-dimensions, each scored 0-20:
1. Schools Sub-Score (0-20)
| Criteria | Points |
|---|---|
| Average GreatSchools rating 9-10 | 16-20 |
| Average GreatSchools rating 7-8 | 12-15 |
| Average GreatSchools rating 5-6 | 8-11 |
| Average GreatSchools rating 3-4 | 4-7 |
| Average GreatSchools rating 1-2 | 0-3 |
Bonus points: magnet/IB programs (+1), low student-teacher ratio (+1), strong test scores (+1) Penalty: no schools within 3 miles (-2), declining ratings (-1)
2. Safety Sub-Score (0-20)
| Criteria | Points |
|---|---|
| Crime rate well below national average, declining trend | 16-20 |
| Crime rate below average, stable trend | 12-15 |
| Crime rate near national average | 8-11 |
| Crime rate above average | 4-7 |
| Crime rate significantly above average, increasing trend | 0-3 |
Bonus: active neighborhood watch (+1), low sex offender count (+1) Penalty: increasing violent crime (-2), recent major incidents (-1)
Show full SKILL.md (493 more words)Show less
3. Amenities Sub-Score (0-20)
| Criteria | Points |
|---|---|
| Walk Score 90+, extensive amenities within 1 mile | 16-20 |
| Walk Score 70-89, good variety of amenities | 12-15 |
| Walk Score 50-69, adequate amenities within 2 miles | 8-11 |
| Walk Score 25-49, limited amenities | 4-7 |
| Walk Score 0-24, very few amenities nearby | 0-3 |
Bonus: hospital within 2 miles (+1), multiple grocery options (+1), parks within walking distance (+1) Penalty: no grocery within 3 miles (-2), no healthcare within 5 miles (-2)
4. Demographics Sub-Score (0-20)
| Criteria | Points |
|---|---|
| Median income well above metro, strong growth, high education | 16-20 |
| Median income above metro, positive growth | 12-15 |
| Median income near metro median, stable | 8-11 |
| Median income below metro, flat or declining | 4-7 |
| Median income well below metro, population declining | 0-3 |
Bonus: high homeownership rate (+1), growing population (+1), low poverty rate (+1) Penalty: declining population (-2), rising poverty (-1)
5. Growth Trajectory Sub-Score (0-20)
| Criteria | Points |
|---|---|
| Major development pipeline, strong job growth, gentrifying area | 16-20 |
| Moderate development activity, positive economic indicators | 12-15 |
| Stable area, limited new development | 8-11 |
| Minimal development, economic headwinds | 4-7 |
| Declining area, business closures, population loss | 0-3 |
Bonus: new transit project (+2), major employer relocating in (+2) Penalty: major employer leaving (-3), unfavorable zoning changes (-2), high disaster risk (-2)
Neighborhood Grade
| Score | Grade | Signal |
|---|---|---|
| 85-100 | A+ | Exceptional — top-tier neighborhood across all dimensions |
| 70-84 | A | Excellent — strong fundamentals with minor gaps |
| 55-69 | B | Good — solid neighborhood with some trade-offs |
| 40-54 | C | Fair — notable weaknesses in one or more areas |
| 25-39 | D | Below Average — significant concerns for most residents |
| 0-24 | F | Poor — major deficiencies across multiple dimensions |
Risk Assessment
Identify and present the top risks specific to this neighborhood:
- Crime trajectory — Is crime getting worse? Any emerging gang activity or drug corridors?
- School quality decline — Are ratings dropping? Teacher shortages? Budget cuts?
- Economic vulnerability — Is the area dependent on a single employer? What happens if they leave?
- Natural disaster exposure — What insurance will be required? Any recent events?
- Gentrification risk — Could rapid change price out current residents or alter neighborhood character?
- Infrastructure aging — Old water/sewer lines? Road quality? Utility reliability?
- Zoning threats — Any proposed changes that could bring unwanted development?
- Environmental hazards — Superfund sites, industrial pollution, water quality issues?
Output Format
Save the analysis as PROPERTY-NEIGHBORHOOD-[ADDRESS].md in the current working directory. Replace spaces and special characters in ADDRESS with hyphens.
Output Structure
# Neighborhood Analysis: [FULL ADDRESS]
> **DISCLAIMER:** For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals.
**Analysis Date:** [DATE]
**Neighborhood Score:** [X]/100 ([GRADE])
---
## Score Summary
| Dimension | Score | Rating |
|-----------|-------|--------|
| Schools | [X]/20 | [EMOJI-FREE RATING] |
| Safety | [X]/20 | [EMOJI-FREE RATING] |
| Amenities | [X]/20 | [EMOJI-FREE RATING] |
| Demographics | [X]/20 | [EMOJI-FREE RATING] |
| Growth Trajectory | [X]/20 | [EMOJI-FREE RATING] |
| **TOTAL** | **[X]/100** | **[GRADE]** |
---
## 1. School Analysis
### Elementary Schools
[Table: Name, Distance, Rating, Key Details]
### Middle Schools
[Table: Name, Distance, Rating, Key Details]
### High Schools
[Table: Name, Distance, Rating, Key Details]
### District Overview
[District name, overall rating, notable programs, trends]
---
## 2. Crime & Safety
### Crime Statistics
[Table: Crime Type, Local Rate, City Average, National Average]
### Safety Assessment
[Trend analysis, comparison, notable factors]
---
## 3. Walkability & Amenities
### Scores
[Walk Score, Transit Score, Bike Score]
### Nearby Amenities
[Tables by category: Grocery, Dining, Parks, Healthcare, Shopping]
---
## 4. Demographics
### Population Profile
[Table: Metric, Value, Metro Comparison]
### Income & Education
[Median income, growth trend, education levels]
---
## 5. Employment & Commute
### Major Employers
[Table: Employer, Industry, Distance]
### Commute Profile
[Median commute, methods, highway/transit access]
---
## 6. Development & Growth
### Active/Planned Projects
[List of developments with details]
### Zoning Changes
[Any relevant zoning activity]
---
## 7. Natural Disaster Risk
### Risk Profile
[Table: Hazard Type, Risk Level, Details]
### Insurance Requirements
[Required coverage based on location]
---
## 8. Risk Factors
[Numbered list of top risks with explanations]
---
## 9. Who This Neighborhood Is Best For
[Match to buyer profiles: families, young professionals, retirees, investors, etc.]
---
## 10. Bottom Line
[2-3 sentence summary: Is this a good neighborhood? What are the standout positives and biggest concerns?]
---
*DISCLAIMER: For educational/research purposes only. Not financial or investment advice. Always consult licensed real estate professionals. Data sourced from publicly available records and may not reflect current conditions.*Quality Rules
- Be specific — Name actual schools, stores, parks, employers. No generic filler.
- Use real data — Every stat should come from a search result. If data is unavailable, say so.
- Compare contextually — Always compare to city and national averages, not in isolation.
- Note data recency — Flag when data is older than 12 months.
- Avoid bias — Present demographics factually without value judgments.
- Disclose gaps — If you cannot find data for a section, state it clearly rather than guessing.
- Conservative scoring — When in doubt, score lower. Better to under-promise.
- No emojis — Use text-based ratings only.
© zubair-trabzada, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/realestate-neighborhood of zubair-trabzada/ai-realestate-claude.
Open the folder on GitHubat commit d435ddd
Compare with similar skills
Realestate Neighborhood 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 |
|---|---|---|---|---|---|---|
| Realestate Neighborhood this skillzubair-trabzada/ai-realestate-claude | 179 | — | ~3.1k | Automated safety check: Pass | MIT | |
| Technical Analysttradermonty/claude-trading-skills | 3k | 4 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Theme Detectortradermonty/claude-trading-skills | 3k | 2 repos | ~4.9k | Automated safety check: Pass | MIT | |
| Creating Financial ModelsChen-zexi/open-ptc-agent | 729 | 3 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Stock APIzhangxiangliang/stock-api | 2k | — | ~507 | Automated safety check: Pass | MIT | |
| Itr Walakaranb192/itr-wala | 871 | — | ~3.6k | Automated safety check: Pass | MIT |
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Categories
Questions about Realestate Neighborhood
What does Realestate Neighborhood do?
Neighborhood Analysis — schools, crime, walkability, demographics, amenities, growth trajectory, and natural disaster risk with Neighborhood Score (0-100). Realestate Neighborhood is an agent skill from zubair-trabzada/ai-realestate-claude.
When should I use Realestate Neighborhood?
Realestate Neighborhood fits situations like: business, Finance & HR work in your project.
How do I install Realestate Neighborhood in Claude Code?
Run `npx skills add zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a claude-code`. Or copy the skill folder (skills/realestate-neighborhood in zubair-trabzada/ai-realestate-claude) into .claude/skills/realestate-neighborhood in your project. Claude Code loads it when a task matches its description.
How do I install Realestate Neighborhood in Codex?
Run `npx skills add zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a codex`. Or copy the skill folder (skills/realestate-neighborhood in zubair-trabzada/ai-realestate-claude) into .agents/skills/realestate-neighborhood in your project. Codex loads it when a task matches its description.
Can I use Realestate Neighborhood 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 zubair-trabzada/ai-realestate-claude --skill realestate-neighborhood -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/realestate-neighborhood, .gemini/skills/realestate-neighborhood, .github/skills/realestate-neighborhood and .opencode/skills/realestate-neighborhood in your project.
What does Realestate Neighborhood need to run?
SKILL.md names no scripts, command-line tools or credentials: Realestate Neighborhood is instructions for the agent only.
Does Realestate Neighborhood 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 Realestate Neighborhood 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 Realestate Neighborhood use?
Realestate Neighborhood 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 Realestate Neighborhood use?
About 3.1k 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.
What are the alternatives to Realestate Neighborhood?
Skills that share tags, products or a category with Realestate Neighborhood: Technical Analyst (tradermonty/claude-trading-skills, 3k stars), Theme Detector (tradermonty/claude-trading-skills, 3k stars), Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars) and Stock API (zhangxiangliang/stock-api, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Realestate Neighborhood?
zubair-trabzada (a GitHub user) maintains it in zubair-trabzada/ai-realestate-claude, which has 179 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on April 29, 2026.
Source: zubair-trabzada/ai-realestate-claude on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.