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/andre-salvati/databricks-template/project-costsnpx skills add andre-salvati/databricks-template --skill project-costsgit clone --depth 1 https://github.com/andre-salvati/databricks-templateWrote 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/andre-salvati/databricks-template/project-costs)<a href="https://agentmods.dev/skills/andre-salvati/databricks-template/project-costs"><img src="https://agentmods.dev/badge/skills/andre-salvati/databricks-template/project-costs.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 | $0.00093 | $0.01549 |
| Opus 5 | $0.00046 | $0.00775 |
| Sonnet 5 | $0.00019 | $0.00310 |
| Haiku 4.5 | $0.00009 | $0.00155 |
Grade A, and why
project-costs 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 5d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Project cost analysis
Run the project cost script, analyze the output for anomalies, spikes and trends, and write the analysis into the generated markdown report.
Steps
- Run
make project-costsvia Bash and capture the full output. It prints to stdout and writesreports/cost/YYYY-MM-DD.md(gitignored) containing every table in markdown, ending with an empty## Analysissection. The script writes only numbers, never prose. - Analyze the output (see below).
- Edit
reports/cost/YYYY-MM-DD.mdand replace the## Analysisplaceholder with your written analysis. Do not retype the tables — they are already in the file, and re-transcribing numbers risks introducing errors. Reference them instead. - Report the same analysis back in chat, and link the report path.
If make project-costs fails to reach Databricks with an auth error, the dev profile's OAuth
refresh token has expired. Tell the user to run ! databricks auth login --profile dev in the
session, then re-run. Do not attempt the browser login yourself.
What the script emits
Four tables, and only four:
- AWS by Week × Service (USD, Total column)
- Databricks by Week × SKU (USD at list price, Total column)
- Combined Totals by Service across both clouds — native
Quantity/Unitplus a totalledUSDcolumn. This is the only place native DBU/DSU/GB quantities appear. - Databricks by Job / Pipeline — one row per job or SDP pipeline that incurred spend, with
Kind, nativeQuantity/Unit,USDandDays(distinct days with usage). In the generated report it sits directly after Combined Totals; on stdout it prints last.
Databricks usage is monetized by joining system.billing.list_prices inside the script, so DBU/DSU
/GB and AWS dollars are directly comparable.
Per-day data is not printed to stdout — it lives only in the collapsed <details> blocks of the
generated report. You will need it: the weekly pivots average single-day spikes away, and those
blocks are the only place a spike can be attributed to a date. Read the report file, don't ask the
script for a daily table.
What ships with it
1 file 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.
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.
- 5d ago First seen · 108 lines · 93 tokens per session scan A 623fbcb41dd1
project-costs is a skill published in the GitHub repository andre-salvati/databricks-template (83 stars, last pushed 29d ago), licensed Apache-2.0. It adds 93 tokens to every session and 1,549 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 2026-08-30.
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