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 bonnard-data/bonnard-cli --skill bonnard-get-startedgit clone --depth 1 https://github.com/bonnard-data/bonnard-cliWrote 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/bonnard-data/bonnard-cli/bonnard-get-started)<a href="https://agentmods.dev/skills/bonnard-data/bonnard-cli/bonnard-get-started"><img src="https://agentmods.dev/badge/skills/bonnard-data/bonnard-cli/bonnard-get-started/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/bonnard-data/bonnard-cli/bonnard-get-started"><img src="https://agentmods.dev/badge/skills/bonnard-data/bonnard-cli/bonnard-get-started.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 | $0.00045 | $0.02239 |
| Opus 5.5 | $0.00018 | $0.00896 |
| Sonnet 5.5 | $0.00009 | $0.00448 |
| Haiku 4.5 | $0.00005 | $0.00224 |
Grade A, and why
bonnard-get-started 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Get Started with Bonnard
This skill guides you through building and deploying a semantic layer.
The user has already run bon init.
IMPORTANT — pacing: Complete ONE phase at a time. Before starting a phase, briefly explain what it does and why. After completing it, show the user what happened and ask if they're ready to move on. Do NOT run through all phases in one go.
Phase 1: Connect a Data Source
Ask the user if they have a warehouse to connect, or want to try a demo dataset first:
# Option A: Use demo data (no warehouse needed)
bon datasource add --demo
# Option B: Import from dbt (if they use it)
bon datasource add --from-dbt
# Option C: Add manually, non-interactive (preferred for agents)
bon datasource add --name my_warehouse --type postgres \
--host db.example.com --port 5432 --database mydb --schema public \
--user myuser --password mypassword
# Option D: Add manually, interactive (in user's terminal)
bon datasource add
Supported types: postgres, redshift, snowflake, bigquery, databricks, duckdb.
The demo option adds a read-only Contoso retail dataset with tables like
fact_sales, dim_product, dim_store, and dim_customer.
The connection will be tested automatically during bon deploy.
Phase 2: Explore the Data
Before creating cubes, understand what tables and columns are available in your warehouse.
Important: bon query is for querying the deployed semantic layer — it does NOT
access your database directly. Use your warehouse's native tools to explore tables.
Options for exploring your data:
- Use your database CLI (e.g.,
psqlfor Postgres/Redshift,snowsqlfor Snowflake,bqfor BigQuery) to list tables and columns - Check your dbt docs or existing documentation for table schemas
- Ask the user for table names and column details if you don't have direct database access
- For the demo dataset, the tables are:
contoso.fact_sales,contoso.dim_product,contoso.dim_store,contoso.dim_customer
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 · 253 lines · 45 tokens per session scan A 0c30458bf711
bonnard-get-started is a skill published in the GitHub repository bonnard-data/bonnard-cli (50 stars, last pushed 3mo ago), licensed MIT. It adds 45 tokens to every session and 2,239 once invoked, about $0.0002 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 2026-08-30.
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