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 joaoguirunas/team-os --skill data-analytics-engineeringgit clone --depth 1 https://github.com/joaoguirunas/team-osWrote 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/joaoguirunas/team-os/data-analytics-engineering)<a href="https://agentmods.dev/skills/joaoguirunas/team-os/data-analytics-engineering"><img src="https://agentmods.dev/badge/skills/joaoguirunas/team-os/data-analytics-engineering/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/joaoguirunas/team-os/data-analytics-engineering"><img src="https://agentmods.dev/badge/skills/joaoguirunas/team-os/data-analytics-engineering.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 | $0.00040 | $0.01195 |
| Opus 5.5 | $0.00016 | $0.00478 |
| Sonnet 5.5 | $0.00008 | $0.00239 |
| Haiku 4.5 | $0.00004 | $0.00120 |
Grade A, and why
data-analytics-engineering 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 27d 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Analytics Engineering
Scope
- Define metrics, grains, and dimensional models.
- Build transformation layers and semantic models.
- Implement data quality tests and observability.
- Document datasets, lineage, and ownership.
- Align analytics outputs with BI and product needs.
Ask For Inputs
- Business metrics and decision use cases.
- Source systems, data freshness, and latency needs.
- Existing warehouse, tooling, and orchestration.
- Expected data volumes and change cadence.
- Governance requirements and access controls.
Workflow
- Define metric dictionary and grains.
- Design staging, intermediate, and mart layers.
- Model dimensions and facts with clear keys.
- Build semantic layer and metric definitions.
- Add tests for freshness, nulls, ranges, and duplicates.
- Document lineage, owners, and SLAs.
- Plan rollout, backfills, and validation checks.
Outputs
- Metric dictionary and semantic model.
- Data model with schema and grain definitions.
- Transformation plan and dbt or SQLMesh structure.
- Data quality test suite and alerting plan.
- Documentation and ownership map.
Quality Checks
- Keep metric definitions stable and versioned.
- Treat metrics as APIs: document changes, deprecate safely, and backfill deliberately.
- Define data contracts for core tables (schema, freshness, keys) to control downstream breakage.
- Avoid mixed grains in a single model.
- Ensure tests cover critical joins and aggregates.
- Validate against source of truth and historical baselines.
Templates
assets/metric-dictionary.mdfor metric definitions and owners.assets/semantic-layer-spec.mdfor entities, measures, and dimensions.assets/data-quality-test-plan.mdfor test coverage planning.
Resources
references/modeling-patterns.mdfor modeling guidance and data quality patterns.references/tool-comparison-2026.mdfor dbt vs SQLMesh vs Coalesce decision matrix.references/semantic-layer-patterns.mdfor semantic layer implementation (Cube, dbt Semantic Layer, AtScale, warehouse-native).references/data-quality-testing.mdfor data quality test strategies, dbt tests, Great Expectations, and alert design.references/metric-governance.mdfor metric lifecycle management, ownership models, deprecation policies, and metric debt prevention.data/sources.jsonfor curated vendor docs and trend-tracking sources (use as a WebSearch seed list).
What ships with it
9 files 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.
- assets/data-quality-test-plan.md 190 B
- assets/metric-dictionary.md 130 B
- assets/semantic-layer-spec.md 261 B
- data/sources.json 6.6 KB
- references/data-quality-testing.md 11 KB
- references/metric-governance.md 12 KB
- references/modeling-patterns.md 6.5 KB
- references/semantic-layer-patterns.md 9.9 KB
- references/tool-comparison-2026.md 9.5 KB
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.
- 27d ago Changed · +10 tokens per session a04bf87d9679
- 1mo ago Changed · +2 lines 20fa40869550
- 1mo ago First seen · 125 lines · 30 tokens per session scan A a39feef8458e
data-analytics-engineering is a skill published in the GitHub repository joaoguirunas/team-os (5 stars, last pushed 3d ago), licensed MIT. It adds 40 tokens to every session and 1,195 once invoked, about $0.0002 per session on Opus 5.5. 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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