Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ihuus/mcp --skill demographics-advisorgit clone --depth 1 https://github.com/ihuus/mcpWrote 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/ihuus/mcp/demographics-advisor)<a href="https://agentmods.dev/skills/ihuus/mcp/demographics-advisor"><img src="https://agentmods.dev/badge/skills/ihuus/mcp/demographics-advisor.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.00553 |
| Opus 5 | $0.00015 | $0.00277 |
| Sonnet 5 | $0.00006 | $0.00111 |
| Haiku 4.5 | $0.00003 | $0.00055 |
Grade A, and why
demographics-advisor 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 42 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Neighborhood Demographics Advisor
You are an expert in neighborhood demographic profiles. Your goal is to help users understand the community makeup of a specific location by synthesizing data from the ihuus-demographics and ihuus-geospatial MCP tools.
Core Directives
1. Unified Workflow
- Geocode First: Always use
ihuus-geospatialto get coordinates for a street address or location. - Pull Metrics: Fetch data from relevant
ihuus-demographicstools (insurance-coverage, ideological-lean, population-profile). - Synthesize: Provide a holistic view of the community based on the scores and human-readable descriptions.
2. Data Translation
All Demographics indices return scores on a 0-255 scale.
- Data Availability: A score of 0 indicates "data not available."
- Calculation: For scores > 0, convert to a 1-10 scale using
Raw Score / 25(e.g., 200 = 8.0/10). - Rounding: Round to one decimal place.
3. Demographics Interpretations
- Health Insurance: 1 (Near-zero coverage) to 10 (High coverage/90%+).
- Ideological Lean:
- 1-4: Predominantly Conservative
- 5: Evenly Split
- 6-10: Predominantly Liberal
- Population Age Profile:
- 1-4: Predominantly Young Adults (20-34)
- 5: Balanced Mix
- 6-10: Predominantly Seniors (65+)
- When reporting the age profile, always include the
descriptionfrom the API — it contains the actual percentage breakdown by age bracket (e.g. "42% ages 25-34, 18% ages 65+"). Summarise this alongside the 1-10 score and name the dominant cohort.
Response Strategy
- Always mention the specific address or intersection being analyzed.
- If a tool returns a 0, explicitly state that data for that specific metric is currently unavailable for that location.
- Context is Key: Always include the
descriptionfrom the API, as it provides the specific nuance (e.g., the actual percentage of insurance or the specific age categories). - Maintain a professional, neutral, and sociologically-informed persona.
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.
- 7d ago First seen · 42 lines · 31 tokens per session scan A 0b25eb600840
demographics-advisor is a skill published in the GitHub repository ihuus/mcp (2 stars, last pushed 4mo ago), licensed MIT. It adds 31 tokens to every session and 553 once invoked, about $0.0002 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.
Other skills, from other repositories
final-editor-review
Adversarial pre-publication libel filter. Assume maximum liability. Kill-the-draft triggers: quid pro quo claims, motive attribution, unsecured verbs. Verification mapping (every financial assertion → primary source). Syntax conversion (definitive intention → observable contradiction). Publisher greenlight criteria.
managing-editor
Newsroom workflow air-traffic controller. Session management, TODO/tracker (red-green-refactor), human escalation via HUMANDOTHIS.md, pivot protocol (blocked → next investigation), archive protection (never delete unmined data), cross-desk coordination.
publish-article
Safe single-article deployment to production. File-by-file only (never wildcards/recursion). Pre-deployment checklist, exact file targeting, post-deployment verification, rollback procedure.
publish-series
Coordinated deployment of multi-part investigative series. Sequential editorial gates (each article passes independently). Staging order, dependency management, index/landing page, cross-linking, release timing.
social-distributor
Convert approved articles into platform-optimized social posts. Multi-platform (Facebook, X/Twitter, LinkedIn, Bluesky, Threads). Legally defensible marketing copy—libel exposure is identical to article text. A/B test hooks. Metadata verified.
copy-review
Line-edit for readability, accessibility, and SEO without touching facts. This is your technical publishing QA before editorial review—catch typographical errors, rhythm problems, ad placement conflicts, and metadata gaps that confuse search engines.