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 Datarails/dr-claude-code-plugins-re --skill anomalies-reportgit clone --depth 1 https://github.com/Datarails/dr-claude-code-plugins-reWrote 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/datarails/dr-claude-code-plugins-re/anomalies-report)<a href="https://agentmods.dev/skills/datarails/dr-claude-code-plugins-re/anomalies-report"><img src="https://agentmods.dev/badge/skills/datarails/dr-claude-code-plugins-re/anomalies-report.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 | $0.00124 | $0.07848 |
| Opus 5 | $0.00062 | $0.03924 |
| Sonnet 5 | $0.00025 | $0.01570 |
| Haiku 4.5 | $0.00012 | $0.00785 |
Grade A, and why
dr-anomalies-report 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 6d 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 — 550 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Anomaly Detection Report
Generate a comprehensive data-quality Excel workbook for a Finance OS table. Works with any table — no pre-configuration required.
Tool reality check: the MCP
profile_numeric_fieldsandprofile_categorical_fieldstools are thin wrappers — they return baseline aggregates only (SUM/AVG/MIN/MAX/COUNT for numerics, distinct-value samples capped at 5 fields for categoricals). There is no server-side anomaly tool. This skill computes every finding, severity bucket, and the Data Quality Score client-side. See/dr-anomaliesfor the per-category recipes; this skill consumes those same recipes and packages the result as an Excel workbook.
Excel Context — Routing Preamble
Before any data pull, establish whether this skill is running in a live Excel context (Claude for Excel with the Datarails Add-In loaded) and route accordingly.
Detect — never infer from the user's wording. A sheet list containing __dr_agent
means the add-in is loaded. Confirm with the agent.get_session probe, which you run by
executing Office.js through the execute_office_js tool (see the Excel Context Contract
in CLAUDE.md, §Transport) — it is not an MCP tool and has no MCP equivalent.
A failed probe is a normal detection result, not an error: it means "no bridge here",
which is the expected outcome in Claude Code. Do not surface it, do not retry it, and do
not apply this skill's connection-error or Connectors-UI guidance to it — that guidance is
about datarails-finance-os connector calls only.
A successful probe means Excel context, on either transport. The bridge serves two
add-in tracks and their session payloads differ: Flex (Office.js task pane) exposes
isLoggedIn; the COM desktop add-in — the majority of live workbooks — exposes
isConnected instead, and isConnected: false is not a login failure, an error, or a
reason to stop or send the user anywhere. It merely means the workbook isn't connected
to a Datarails file, which matters only to drilldown_* / create_dynamic_range (the
bridge skill gates those itself). Only Flex's explicit isLoggedIn: false means
sign-in is needed.
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.
- 6d ago First seen · 550 lines · 124 tokens per session scan A d495cc1b9af8
dr-anomalies-report is a skill published in the GitHub repository Datarails/dr-claude-code-plugins-re (3 stars, last pushed 7d ago), licensed MIT. It adds 124 tokens to every session and 7,848 once invoked, about $0.0006 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.
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