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 skills/datarails/dr-claude-code-plugins-re/extractnpx skills add Datarails/dr-claude-code-plugins-re --skill extractgit clone --depth 1 https://github.com/Datarails/dr-claude-code-plugins-reWhat 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 | $0.00095 | $0.07834 |
| Opus 5 | $0.00048 | $0.03917 |
| Sonnet 5 | $0.00019 | $0.01567 |
| Haiku 4.5 | $0.00010 | $0.00783 |
Grade A, and why
dr-extract 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 2d 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 — 425 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Datarails Financial Data Extraction
Extract validated financial data from Finance OS to Excel workbooks. Data is pulled via MCP tools and the workbook is built locally with openpyxl. No server-side rendering.
The workbook contains:
- P&L Data: Revenue, COGS, Operating Expenses by month
- KPI Data: quarterly KPIs the org's data can actually source — revenue by quarter always; SaaS metrics (ARR, Net New ARR, Churn, LTV) only when a KPI source exists (see the KPI-honesty rule under Sheets to Generate)
- Validation: Cross-checks between P&L and KPI tables
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.
- 2d ago First seen · 425 lines · 95 tokens per session scan A fecec1a8ea5d
dr-extract is a skill published in the GitHub repository Datarails/dr-claude-code-plugins-re (3 stars, last pushed 3d ago), licensed MIT. It adds 95 tokens to every session and 7,834 once invoked, about $0.0005 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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