Borrowing it
Nothing to install: this file belongs to ai-engineers-guild/apartment-hunter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ai-engineers-guild/apartment-hunter/main/.agents/skills/city-district-context-kz/SKILL.mdgit clone --depth 1 https://github.com/ai-engineers-guild/apartment-hunterWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/ai-engineers-guild/apartment-hunter/city-district-context-kz)<a href="https://agentmods.dev/skills/ai-engineers-guild/apartment-hunter/city-district-context-kz"><img src="https://agentmods.dev/badge/skills/ai-engineers-guild/apartment-hunter/city-district-context-kz/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/ai-engineers-guild/apartment-hunter/city-district-context-kz"><img src="https://agentmods.dev/badge/skills/ai-engineers-guild/apartment-hunter/city-district-context-kz.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00059 | $0.00415 |
| Opus 5 | $0.00030 | $0.00208 |
| Sonnet 5 | $0.00012 | $0.00083 |
| Haiku 4.5 | $0.00006 | $0.00042 |
Grade A, and why
city-district-context-kz scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
City District Context KZ
When to use
Use this skill when the user:
- asks which district is better for living or renting;
- wants local context before searching apartments;
- asks whether an area is safe, convenient, expensive, noisy, or well connected;
- wants a short district brief attached to apartment recommendations.
Workflow
- Identify city, target districts, budget band, and user priorities.
- Research current neighborhood context with recent web sources.
- Summarize by explicit dimensions, not vibes.
- Feed the conclusion back into apartment search filters or recommendation logic.
Required research dimensions
- district reputation and perceived livability;
- transport access: metro, buses, major roads, commute friction;
- price level relative to the city;
- cleanliness, greenery, walkability, and air/noise exposure;
- active construction, redevelopment, traffic, or nightlife pressure;
- family fit: schools, clinics, playgrounds, calmer courtyards;
- renter tradeoffs: prestige vs convenience vs budget.
Output format
For each district, produce:
- one-line profile;
- strengths;
- risks;
- who it fits best;
- budget implication relative to the city average.
Rules
- Use recent sources. If the user says "now", "currently", or "today", verify with live browsing.
- Do not present reputation claims as hard fact; label them as observed patterns or common perception.
- Translate vague labels like "good district" into concrete variables: commute, noise, price, cleanliness, schools, and safety perception.
- If the apartment search skill is also active, use this context to refine district filters or to rank results.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 11d ago First seen · 58 lines · 59 tokens per session scan A b7bb6428e6e2
city-district-context-kz is a skill published in the GitHub repository ai-engineers-guild/apartment-hunter (2 stars, last pushed 19d ago), licensed MIT. It adds 59 tokens to every session and 415 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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