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 OneWave-AI/claude-skills --skill bi-measure-buildergit clone --depth 1 https://github.com/OneWave-AI/claude-skillsWrote 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/onewave-ai/claude-skills/bi-measure-builder)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/bi-measure-builder"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/bi-measure-builder/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/onewave-ai/claude-skills/bi-measure-builder"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/bi-measure-builder.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 | $0.00220 | $0.02096 |
| Opus 5.5 | $0.00088 | $0.00838 |
| Sonnet 5.5 | $0.00044 | $0.00419 |
| Haiku 4.5 | $0.00022 | $0.00210 |
Grade A, and why
bi-measure-builder 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 23d 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 — 69 lines — stays where its author put it; the contents beside it link to each section on GitHub.
BI Measure Builder
Most wrong BI numbers are not syntax errors. They are the right formula evaluated in the wrong context. Work context-first, and prove every measure against numbers computed independently.
Workflow
- Pin down the model before writing anything. Get (or state as an explicit assumption): the fact table and its grain (one row per order line? per snapshot?), dimension tables, relationship keys and direction, and the date table. Ask only for what changes the formula; otherwise state the assumption and proceed. Why: the same YoY formula is right on a star schema and wrong on a flat table with a text date.
- Name the platform and version features. DAX: classic vs calendar-based time intelligence (preview), marked date table or not. Tableau: live vs extract, context filters in use. Looker: dialect (window-function support,
period_over_periodsupport). - State the evaluation context in one or two sentences for a typical visual cell and for the grand total. Example: "Row = Month; filters = Region slicer; total = all months in the slicer range, recomputed, not summed." Why: this is where most bugs live, and saying it forces the check.
- Write the calculation from the matching pattern in the reference file. Use variables (DAX
VAR) for readability and to evaluate each sub-expression once. - Explain it line by line in terms of context: what each filter argument adds, removes, or overrides; where context transition happens; which Tableau pipeline step each part runs in; which part Looker runs in SQL vs after the query.
- Give a hand-computable test: a 5-10 row sample, the visual layout, and the expected value for each row and the total. Generate or confirm the numbers with
scripts/measure_check.py(below) rather than mental arithmetic. - Performance notes only where they matter: iterator size, context transition inside large iterators, table filters vs column filters, bidirectional relationships, LOD on high-cardinality dimensions, PDT persistence.
What ships with it
25 files 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.
- examples/actual_yoy_fixed.csv 62 B
- examples/actual_yoy_from_tool.csv 68 B
- examples/worked-example.md 4.5 KB
- examples/yoy_spec.json 160 B
- references/dax.md 10 KB
- references/looker.md 9.3 KB
- references/tableau.md 7.6 KB
- scripts/measure_check.py 8.0 KB runs code
- tests/fixtures/balances.csv 135 B
- tests/fixtures/sales.csv 278 B
- tests/specs/balance_global_last.json 326 B
- tests/specs/balance_per_entity.json 286 B
- tests/specs/distinct_customers.json 223 B
- tests/specs/new_customers_east.json 261 B
- tests/specs/new_customers.json 228 B
- tests/specs/pct_region.json 245 B
- tests/specs/prior_year.json 226 B
- tests/specs/rank_customer.json 216 B
- tests/specs/returning_customers.json 228 B
- tests/specs/rolling_3m.json 249 B
- tests/specs/running_total.json 230 B
- tests/specs/yoy_pct.json 240 B
- tests/specs/ytd_fiscal_jul.json 262 B
- tests/specs/ytd.json 220 B
- tests/test_measure_check.py 1.2 KB runs code
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.
- 23d ago First seen · 69 lines · 220 tokens per session scan A 0ae09bda75ec
bi-measure-builder is a skill published in the GitHub repository OneWave-AI/claude-skills (349 stars, last pushed 15d ago), licensed MIT. It adds 220 tokens to every session and 2,096 once invoked, about $0.0009 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 2026-09-24.
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