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/jpd44/mesh44-plugins/dashboardnpx skills add jpd44/mesh44-plugins --skill dashboardgit clone --depth 1 https://github.com/jpd44/mesh44-pluginsWhat 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 | $0.00046 | $0.00491 |
| Opus 5 | $0.00023 | $0.00246 |
| Sonnet 5 | $0.00009 | $0.00098 |
| Haiku 4.5 | $0.00005 | $0.00049 |
Grade A, and why
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 2d 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.
What it actually says
/cost:dashboard — launch the local spend dashboard
Bring up the mesh44-cost web dashboard on the user's machine. It reads AWS Cost Explorer with the user's own credentials and renders locally. Nothing is uploaded anywhere.
Where the app lives
The dashboard is a standalone Vite app in the jpd44/mesh44-cost repo.
- If the user already has a clone (check
~/Developer/mesh44-cost, or ask), use it. - Otherwise clone it:
git clone https://github.com/jpd44/mesh44-cost.git ~/Developer/mesh44-cost cdinto it and runnpm installifnode_modulesis missing.
Pick the AWS profile
Org-wide spend requires the management / payer account. Ask which profile to use (default mgt) and make sure the SSO session is live:
aws sts get-caller-identity --profile mgt >/dev/null 2>&1 || aws sso login --profile mgt
A child-account profile only shows that one account's spend — fine for scoping down, but tell the user that's what they'll see.
Launch
cd ~/Developer/mesh44-cost
AWS_PROFILE=mgt npm run dashboard # fetch real data + start the local server
This writes a local, gitignored public/data.json and serves the dashboard at http://127.0.0.1:5188. Open that URL for the user. The dashboard also has an in-app profile dropdown + refresh, so they can switch accounts without restarting.
Data only, no UI: AWS_PROFILE=mgt npm run fetch.
Privacy contract
- Runs only on the user's machine, with the user's credentials.
public/data.jsonstays local and gitignored — never commit it, never send it anywhere.- Read-only IAM:
ce:GetCostAndUsage,ce:GetCostForecast,organizations:ListAccounts. - Cost Explorer API calls cost ~$0.01 each; a refresh is a handful of calls.
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.
- 2d ago First seen · 47 lines · 46 tokens per session scan A 45ed99c2d947
dashboard is a skill published in the GitHub repository jpd44/mesh44-plugins (2 stars, last pushed 1mo ago), licensed MIT. It adds 46 tokens to every session and 491 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…