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 vaquarkhan/data-engineering-agent-skills --skill trino-presto-federated-querygit clone --depth 1 https://github.com/vaquarkhan/data-engineering-agent-skillsWrote 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/vaquarkhan/data-engineering-agent-skills/trino-presto-federated-query)<a href="https://agentmods.dev/skills/vaquarkhan/data-engineering-agent-skills/trino-presto-federated-query"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/trino-presto-federated-query/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/vaquarkhan/data-engineering-agent-skills/trino-presto-federated-query"><img src="https://agentmods.dev/badge/skills/vaquarkhan/data-engineering-agent-skills/trino-presto-federated-query.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 | $0.00044 | $0.01132 |
| Opus 5 | $0.00022 | $0.00566 |
| Sonnet 5 | $0.00009 | $0.00226 |
| Haiku 4.5 | $0.00004 | $0.00113 |
Grade A, and why
trino-presto-federated-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 9d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Trino Presto Federated Query
Overview
Use this skill when Trino or Presto sits across multiple data systems as a federated query layer. It helps agents reason about federation boundaries, predicate pushdown limits, consistency trade-offs, performance planning, and governed consumption patterns.
When to Use
- querying across multiple heterogeneous data stores with
TrinoorPresto - defining governed federated analytics access for users or applications
- managing performance, cost, and semantic consistency across systems
- building a query layer over lakehouse tables, relational databases, and object stores
- planning catalog and connector configuration for multi-source environments
Do not use this when all data lives in a single system or when a materialized serving layer would be simpler and more performant.
Workflow
-
Define the federation scope and use case. Include:
- which data systems are federated (data lake, warehouse, RDBMS, search, cache)
- what queries need to cross system boundaries
- who are the consumers (analysts, applications, dashboards)
- what latency and concurrency expectations exist
- is federation for ad-hoc exploration or production query patterns
-
Configure catalogs and connectors with explicit assumptions.
- document which connector is used for each source and its capabilities
- understand pushdown support per connector: predicates, projections, aggregations, limits
- define authentication and access control per catalog
- test connector behavior for null handling, type mapping, and timezone semantics
- version connector configurations and treat them as infrastructure code
-
Design queries for federation-aware performance.
- push filtering to the source where possible — cross-system joins are expensive
- minimize data movement: filter early, aggregate at the source when pushdown supports it
- avoid joining large datasets across different connectors — materialize one side first
- use
EXPLAINto verify pushdown behavior before assuming it works - set query timeouts and resource limits to prevent runaway federated scans
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.
- 9d ago First seen · 98 lines · 44 tokens per session scan A 67e68d77eb11
trino-presto-federated-query is a skill published in the GitHub repository vaquarkhan/data-engineering-agent-skills (45 stars, last pushed 3mo ago), licensed MIT. It adds 44 tokens to every session and 1,132 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 2026-09-03.
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