Data Formulator is an interactive workspace where AI agents connect to data sources, answer questions, and create visualizations. It is used to explore and analyze data while branching into related questions without losing the context of each investigative path.
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.
git clone --depth 1 https://github.com/microsoft/data-formulatorWrote 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/rules/microsoft/data-formulator/implementation-review-checklist)<a href="https://agentmods.dev/rules/microsoft/data-formulator/implementation-review-checklist"><img src="https://agentmods.dev/badge/rules/microsoft/data-formulator/implementation-review-checklist/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/rules/microsoft/data-formulator/implementation-review-checklist"><img src="https://agentmods.dev/badge/rules/microsoft/data-formulator/implementation-review-checklist.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 | $0.00324 | $0.00324 |
| Opus 5.5 | $0.00130 | $0.00130 |
| Sonnet 5.5 | $0.00065 | $0.00065 |
| Haiku 4.5 | $0.00032 | $0.00032 |
Grade A, and why
implementation-review-checklist 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 1mo 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
Implementation Review Checklist
After any substantive implementation, before the final response, review the uncommitted diff from a maintainer/code-review perspective. Do not only verify that the feature works.
Required Checks
- Inspect
git diff --statand relevant diffs to understand the actual blast radius. - Check responsibility boundaries: frontend UI, API route, service/helper, storage/session, and tests should each own the right part of the behavior.
- Check API semantics: endpoint names, HTTP methods, response shapes, and side effects must match the product action. Similar UI actions should call the same backend API.
- Check frontend/backend state consistency: after mutations, make sure Redux/local state, backend session/token/vault state, and subsequent list/status APIs agree.
- Check duplication: if two paths clear the same state or perform the same API flow, extract a small helper or route instead of copying logic.
- Check regression surfaces: refresh/reload/list/status paths must respect new flags or state, not just the primary click path.
- Check tests: add or update focused tests for the changed contract; include at least one test for the bug/regression path when practical.
- Check docs/rules/dev-guides when the change introduces or changes a cross-cutting convention.
Reporting
If issues are found during this review, fix clear issues before finalizing. If a trade-off remains, call it out explicitly in the final response with the risk and why it was left as-is.
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.
- 1mo ago First seen · 29 lines · 324 tokens per session scan A cd161143e4bb
implementation-review-checklist is a cursor rule published in the GitHub repository microsoft/data-formulator (17,610 stars, last pushed today), licensed MIT. It adds 324 tokens to every session, about $0.0013 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 2026-08-30.
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