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 agentmods add agents/datenoio/internacia-db/querygit clone --depth 1 https://github.com/datenoio/internacia-dbWhat 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 | $0.00000 | $0.01391 |
| Opus 5 | $0.00000 | $0.00696 |
| Sonnet 5 | $0.00000 | $0.00278 |
| Haiku 4.5 | $0.00000 | $0.00139 |
Grade A, and why
query 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 yesterday.
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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent guide: querying Internacia data
Platform-neutral workflow for looking up countries, borders, org membership, and entity linking. Works with Cursor, Claude Code, Copilot, Codex, and any agent with file or API access.
Before querying
- Read llms.txt for join keys and gotchas (compact index).
- Use exported datasets — do not parse
data/countries/*.yamlordata/intblocks/**/*.yamlunless authoring. - Full consumption contract: ai-consumers.md.
- Verified recipes: query-examples.md (DuckDB), query-examples-polars.md (Polars / Parquet), query-examples-r.md (R / dplyr), query-examples-observable.md (Observable / Plot).
Access paths
| Method | Path / URL |
|---|---|
| DuckDB (preferred, in-repo) | data/datasets/internacia.duckdb |
| Parquet | data/datasets/countries.parquet, intblocks.parquet, blocktypes.parquet, memberships.parquet |
| Version check | SELECT * FROM _meta; or data/datasets/*.manifest.json |
| Python SDK (no full checkout) | https://github.com/datenoio/internacia-python |
| HTTP API | https://github.com/datenoio/internacia-api (self-host only; no public hosted instance) |
Join keys
| Entity | Primary key | Also useful |
|---|---|---|
| Country | code (alpha-2) |
iso3code, numeric_code, wikidata_id |
| Intblock | id |
wikidata_id, blocktype, partof |
| Membership | includes[].id → country code |
Not includes[].name |
| Blocktype taxonomy | blocktypes.id |
matches values in intblocks.blocktype list |
| Borders | alpha-3 in borders |
join on neighbor iso3code |
Scope (in / out)
In scope: ISO identifiers, geography, demographics with source/year, World Bank classifications, languages/currencies/timezones, org membership, Wikidata links.
Out of scope: HDI, GDP, government type, internet penetration, time-series indicators — enrich downstream from other datasets.
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.
- yesterday First seen · 141 lines · 0 tokens per session scan A fbac1a58a273
query is an agent published in the GitHub repository datenoio/internacia-db (11 stars, last pushed 12d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,391 tokens. 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 2026-08-30.
Other agents, from other repositories
AUDIT_MANIFEST
Total unimplemented-tagged scenarios: 76 Classified: 76.
data-pipeline-engineer
Data pipeline specialist: embeddings, chunking strategies, vector indexes, data transformation for AI consumption.
architecture-patterns-prompt
You are an architecture and design patterns specialist. Your mission: guide optimal system architecture decisions using proven patterns, modern approaches, and real-world trade-off analysis.
data-engineering-prompt
You are a Data Engineering Specialist who designs and builds robust data pipelines, ensures data quality at scale, and implements both real-time streaming and batch processing architectures. You master modern data stack tools (dbt, Airflow, Spark, Kafka) and guide teams from raw data ingestion to production-ready…
compliance-governance-prompt
You are a Compliance & Governance Specialist who ensures software systems meet regulatory requirements (GDPR, HIPAA, SOC 2, PCI DSS), implements privacy by design, conducts threat modeling, and establishes governance frameworks. You bridge the gap between legal requirements and technical implementation.
monitoring-observability-prompt
You are a monitoring and observability specialist agent. Your mission: instrument systems with the three pillars of observability — logs, metrics, and traces — to ensure production reliability, rapid incident response, and data-driven operational decisions.