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/cliffren/swf/dashboardnpx skills add cliffren/swf --skill dashboardgit clone --depth 1 https://github.com/cliffren/swfWrote 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/cliffren/swf/dashboard)<a href="https://agentmods.dev/skills/cliffren/swf/dashboard"><img src="https://agentmods.dev/badge/skills/cliffren/swf/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 | $0.00019 | $0.00448 |
| Opus 5 | $0.00010 | $0.00224 |
| Sonnet 5 | $0.00004 | $0.00090 |
| Haiku 4.5 | $0.00002 | $0.00045 |
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 3d 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
Project Status Dashboard
Show a high-level overview of all research projects, or drill into a specific one.
Input
$ARGUMENTS — optional project name. If omitted, show all projects.
Workflow
All projects (no argument)
-
List all Linear projects (exclude Ideas project from main list)
-
For each project, show:
- Current phase (based on which milestone has In Progress issues)
- Issue counts: In Progress / Todo / Done
- Any blockers or overdue items
-
Show Ideas pipeline separately:
- Number of ideas being evaluated
- Any ready to promote
-
Output format:
## 项目总览 | 项目 | 当前阶段 | 进行中 | 待办 | 已完成 | |------|---------|--------|------|--------| | Project A | Phase 2 | 2 | 5 | 12 | | Project B | Phase 1 | 1 | 3 | 4 | ## Ideas 管道 - 3 个想法评估中 - 1 个评估完成，可 promote
Single project (with argument)
- Fetch project details from Linear
- Show by milestone:
## Project A — Phase 2: 验证与Benchmark ### Phase 1 — 数据准备与开发 (Done) ✓ 5/5 issues completed ### Phase 2 — 验证与Benchmark (Current) - [In Progress] PRJ-8: 真实数据 benchmark (agent:claude) - [In Progress] PRJ-9: 性能评估 (manual) - [Todo] PRJ-10: 子图整理 (figures) - [Todo] PRJ-11: 数据归档 (admin) ### Phase 3~8: 未开始
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.
- 3d ago First seen · 61 lines · 19 tokens per session scan A bd48e769bfc7
dashboard is a skill published in the GitHub repository cliffren/swf (5 stars, last pushed 4mo ago), licensed MIT. It adds 19 tokens to every session and 448 once invoked, about $0.0001 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…