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/stefanthecode/dotnet-ai-toolkit/toolkit-dashboardnpx skills add StefanTheCode/dotnet-ai-toolkit --skill toolkit-dashboardgit clone --depth 1 https://github.com/StefanTheCode/dotnet-ai-toolkitWrote 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/stefanthecode/dotnet-ai-toolkit/toolkit-dashboard)<a href="https://agentmods.dev/skills/stefanthecode/dotnet-ai-toolkit/toolkit-dashboard"><img src="https://agentmods.dev/badge/skills/stefanthecode/dotnet-ai-toolkit/toolkit-dashboard.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 | $0.00129 | $0.01211 |
| Opus 5 | $0.00064 | $0.00606 |
| Sonnet 5 | $0.00026 | $0.00242 |
| Haiku 4.5 | $0.00013 | $0.00121 |
Grade A, and why
toolkit-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 yesterday.
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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Toolkit Dashboard
Generate a single, self-contained dashboard/index.html that gives a clear visual overview of the whole toolkit: every skill and agent (name, category, version, description, docs), plus a history of skill/agent runs and their findings. It runs on localhost with one command and has zero runtime dependencies.
When this runs
- First thing when someone opens the toolkit and wants to see what's inside.
- Whenever a skill or agent is added, updated, or run — regenerate so the dashboard stays current.
- When the user asks for an overview, a dashboard, run history, or "what do I have".
What it does
- Scans
skills/*/SKILL.md— parses YAML frontmatter (name,description, optionalcategory,version), and notes whether each skill has aUSAGE.mdand areferences/folder. - Scans
agents/*.md(excluding*.USAGE.md) — parses frontmatter (name,description,tools, optionalcategory,version). - Merges
catalog-meta.json(optional, at the toolkit root) — fills incategory/version/tagsfor any item that doesn't declare them in frontmatter. - Loads
runs/*.json— structured run records (see the schema below) and renders them as a searchable, filterable history with verdict badges and findings. - Writes
dashboard/index.html— one file, all data embedded, no external requests. Works overfile://or a local server.
How Claude runs it (no terminal for the user)
When this skill triggers, Claude builds and opens the dashboard for the user — they should never have to run Python themselves.
- Build it with the Bash tool. The generator auto-detects the toolkit root, so no arguments are needed:
(python3 "<toolkit>/skills/toolkit-dashboard/scripts/build_dashboard.py"--root <toolkit>also works if you want to be explicit.) - Open it for the user:
- Cowork: present
dashboard/index.htmlwith the file-presentation tool so they open it in one click. - Claude Code / terminal: give them the path and offer to serve it —
cd dashboard && python3 -m http.server 8080→http://localhost:8080.
- Cowork: present
- (Optional) Also build the case-study showcase:
→python3 "<toolkit>/skills/toolkit-dashboard/scripts/build_showcase.py" --target "Project Atlas"showcase/index.html(a branded, screenshot-ready results page).
What ships with it
6 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.
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.
- yesterday First seen · 83 lines · 129 tokens per session scan A 9b9b20147ab8
toolkit-dashboard is a skill published in the GitHub repository StefanTheCode/dotnet-ai-toolkit (19 stars, last pushed 26d ago), licensed MIT. It adds 129 tokens to every session and 1,211 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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