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 PostHog/posthog-foss --skill building-a-dashboardgit clone --depth 1 https://github.com/PostHog/posthog-fossWrote 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/posthog/posthog-foss/building-a-dashboard)<a href="https://agentmods.dev/skills/posthog/posthog-foss/building-a-dashboard"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/building-a-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/skills/posthog/posthog-foss/building-a-dashboard"><img src="https://agentmods.dev/badge/skills/posthog/posthog-foss/building-a-dashboard.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00128 | $0.00872 |
| Opus 5 | $0.00064 | $0.00436 |
| Sonnet 5 | $0.00026 | $0.00174 |
| Haiku 4.5 | $0.00013 | $0.00087 |
Grade A, and why
building-a-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 7d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- building-a-dashboard — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Building a dashboard
A dashboard is a collection of insight tiles on one page. Your job is to figure out which insights belong on it, reuse what already exists, create what's missing, and lay them out sensibly — not to blindly generate charts.
Create vs update
First work out whether you're creating a new dashboard or changing an existing one.
- Search existing dashboards with
dashboards-get-all(itssearchparam does fuzzy name/description matching). If the user is clearly describing something that already exists, they probably want an update. - Read a candidate with
dashboard-getto see its current tiles before you change anything. - If the request is ambiguous — "get my financial metrics together" could mean build new or add to an existing one — ask a short clarifying question rather than guessing.
Use templates as reference
PostHog ships vetted dashboard templates for common topics, and orgs can share their own. Consult them before you build — they're a strong signal of which insights pair well on a topic.
dashboard-templates-list— browse templates (usesearchfor a topic,scopeto narrow to global / team / organization). This returns names, descriptions, and tags only.dashboard-templates-retrieve— open the closest template to see itstiles: which insights it groups together and how each is queried.
Treat templates as examples, not a spec. Take inspiration from the insights and their groupings, but tailor every insight to the user's own events, properties, and intent. Don't copy a template verbatim, and don't force a template onto a request it doesn't fit — a good bespoke dashboard beats a mismatched template every time.
Select the insights
Prefer reusing existing insights over recreating them.
- Search with
insights-listand read promising ones withinsight-getto check they match the user's intent and actually have data. Full-text search misses things named differently, so list broadly before concluding an insight doesn't exist. - For anything missing, create it with
insight-create(see the product-analytics insight skills for query shape). - Keep the set minimal — only the insights the request needs. A focused dashboard is more useful than an exhaustive one.
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.
- 7d ago First seen · 71 lines · 128 tokens per session scan A 504240dcfae4
building-a-dashboard is a skill published in the GitHub repository PostHog/posthog-foss (715 stars, last pushed today), licensed MIT. It adds 128 tokens to every session and 872 once invoked, about $0.0006 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 2026-09-03.
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