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 ramp-public/cursor-plugin --skill spend-analysisgit clone --depth 1 https://github.com/ramp-public/cursor-pluginWrote 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/ramp-public/cursor-plugin/spend-analysis)<a href="https://agentmods.dev/skills/ramp-public/cursor-plugin/spend-analysis"><img src="https://agentmods.dev/badge/skills/ramp-public/cursor-plugin/spend-analysis/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/ramp-public/cursor-plugin/spend-analysis"><img src="https://agentmods.dev/badge/skills/ramp-public/cursor-plugin/spend-analysis.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 | $0.00121 | $0.02771 |
| Opus 5.5 | $0.00048 | $0.01108 |
| Sonnet 5.5 | $0.00024 | $0.00554 |
| Haiku 4.5 | $0.00012 | $0.00277 |
Grade A, and why
spend-analysis 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.
How it starts
The opening of the file, as written. The whole thing — 273 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Non-Negotiables
- Always query both transactions and bills for complete vendor spend. Card charges and bill payments are separate resources — there is no unified spend endpoint.
- Pass
--agentfor machine-readable JSON output on all commands. - Handle amount format differences: transactions use strings (
"$1,048.25","-$259.49"), bills use numbers (15000), PO amounts use numbers. Reimbursement amounts are in dollars. - Paginate until
next_page_cursoris null — a single page may not return everything. - Flag vendor name variants explicitly (e.g., "Delta Air Lines" vs "Delta Airlines") — the API does not normalize.
- Negative transaction amounts are refunds. Include them in totals but call them out.
Workflow
Step 1: Pull card transactions
For each vendor (or all vendors if doing a broad analysis):
ramp transactions list \
--transactions_to_retrieve all_transactions_across_entire_business \
--reason_memo_merchant_or_user_name_text_search "<vendor>" \
--from_date <YYYY-MM-DD> \
--to_date <YYYY-MM-DD> \
--include_count \
--page_size 200 \
--agent
If next_page_cursor is not null, paginate:
ramp transactions list \
--transactions_to_retrieve all_transactions_across_entire_business \
--reason_memo_merchant_or_user_name_text_search "<vendor>" \
--from_date <YYYY-MM-DD> \
--to_date <YYYY-MM-DD> \
--page_size 200 \
--next_page_cursor "<cursor>" \
--agent
For broad analysis (all vendors): Omit --reason_memo_merchant_or_user_name_text_search to pull all transactions, then group client-side.
Step 2: Pull bill payments
For a specific vendor:
ramp bills search --query "<vendor>" --include_paid --limit 50 --agent
For broad analysis (all vendors):
ramp bills list --include_paid --limit 50 --agent
Repeat either with --page_cursor if next_page_cursor is not null.
Note: bills search has no date range filter and returns due_date but not payment_date. For date-bounded actual spend, drill into paid bills with ramp bills get <id> --agent to get payment_date, then filter by that. If drilling into every bill is impractical, filter by due_date but label the result as "bills due in period" rather than "spend in period." Bills with payment_status: "OPEN" are unpaid — report them separately as commitments.
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 · 273 lines · 121 tokens per session scan A 0a00cd4967f7
spend-analysis is a skill published in the GitHub repository ramp-public/cursor-plugin (2 stars, last pushed 2mo ago), licensed MIT. It adds 121 tokens to every session and 2,771 once invoked, about $0.0005 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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