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.
git 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/rules/bonnard-data/bonnard-cli/bonnard-build-dashboard)<a href="https://agentmods.dev/rules/bonnard-data/bonnard-cli/bonnard-build-dashboard"><img src="https://agentmods.dev/badge/rules/bonnard-data/bonnard-cli/bonnard-build-dashboard/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/rules/bonnard-data/bonnard-cli/bonnard-build-dashboard"><img src="https://agentmods.dev/badge/rules/bonnard-data/bonnard-cli/bonnard-build-dashboard.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 | $0.00039 | $0.01220 |
| Opus 5.5 | $0.00016 | $0.00488 |
| Sonnet 5.5 | $0.00008 | $0.00244 |
| Haiku 4.5 | $0.00004 | $0.00122 |
Grade A, and why
bonnard-build-dashboard 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 — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Build & Deploy a Markdown Dashboard
This guide walks through creating a markdown dashboard with built-in chart components and deploying it to Bonnard.
Phase 1: Explore Available Data
Discover what measures and dimensions are available to query:
# List all views and their fields
bon schema
# Inspect a specific view's measures and dimensions
bon schema <view_name>
# Query a specific view to see what data looks like
bon query '{"measures": ["view_name.measure"], "dimensions": ["view_name.dimension"], "limit": 5}'
# Or use SQL format
bon query --sql "SELECT MEASURE(total_revenue), date FROM sales_performance LIMIT 5"
Ask the user what data they want to visualize. Match their request to available views and measures.
Phase 2: Learn the Format
Review the dashboard format docs for reference:
bon docs dashboards # Overview + format
bon docs dashboards.components # Chart components (BigValue, LineChart, BarChart, etc.)
bon docs dashboards.queries # Query block syntax
bon docs dashboards.inputs # Interactive filters (DateRange, Dropdown)
bon docs dashboards.examples # Complete examples
Phase 3: Build the Markdown File
Create a .md file with three parts:
- YAML frontmatter — title and optional description
- Query blocks —
```query namecode fences with YAML query options - Components —
<BigValue />,<LineChart />,<BarChart />, etc.
Key points:
- All field names must be fully qualified:
orders.total_revenue, nottotal_revenue - Each component references a query by name:
data={query_name} - Consecutive
<BigValue>components auto-group into a row - Use
<Grid cols="2">to place charts side by side - Use
<DateRange>and<Dropdown>for interactive filters - BigValue supports
comparisonprop for ▲/▼ delta indicators (e.g. actual vs target) - Charts support
y2for secondary y-axis (combo charts: bars + line, dual scales) - For DataTable formatting, use
<Column>children instead of thefmtprop (avoids comma ambiguity with Excel format codes):<DataTable data={sales}> <Column field="orders.total_revenue" header="Revenue" fmt="eur2" /> <Column field="orders.count" header="Orders" fmt="num0" /> </DataTable>
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 · 172 lines · 39 tokens per session scan A 272669b12485
bonnard-build-dashboard is a cursor rule published in the GitHub repository bonnard-data/bonnard-cli (50 stars, last pushed 3mo ago), licensed MIT. It adds 39 tokens to every session and 1,220 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.
Other cursor rules, from other repositories
hatch3r-dynamic-stack-verification
Runtime-evidence gates for stacks with no static type layer (plain-JS Vue, dynamic persistence) — smoke-mount changed components, dormant-collection-read ratchet, runtime smoke evidence on module-boundary changes; a green lint+build+mock-suite proves a layer, not the system.
hatch3r-spec-currency
Spec-currency mandate — any diff changing user-observable behavior covered by a docs/specs/ file updates that spec in the same delivery; staleness definition, review-gate drift finding with a named owner, and a release-readiness sweep.
hatch3r-migrations
Database migration and schema change patterns — expand-contract, online DDL, backfills, compatibility windows, reversibility, multi-region, tooling.
hatch3r-data-classification
Data classification standards covering PII handling, encryption, retention policies, and regulatory compliance.
cursor-asdd
ASDD contribution rules for this repository.
hatch3r-security-patterns
Security patterns including input validation, auth enforcement, and AI/agentic security for the project.