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 cacheplane/dawnai --skill workspace-conventionsgit clone --depth 1 https://github.com/cacheplane/dawnaiWrote 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/cacheplane/dawnai/workspace-conventions)<a href="https://agentmods.dev/skills/cacheplane/dawnai/workspace-conventions"><img src="https://agentmods.dev/badge/skills/cacheplane/dawnai/workspace-conventions/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/cacheplane/dawnai/workspace-conventions"><img src="https://agentmods.dev/badge/skills/cacheplane/dawnai/workspace-conventions.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 | $0.00017 | $0.00212 |
| Opus 5.5 | $0.00007 | $0.00085 |
| Sonnet 5.5 | $0.00003 | $0.00042 |
| Haiku 4.5 | $0.00002 | $0.00021 |
Grade A, and why
workspace-conventions 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.
What it actually says
Workspace conventions
The four workspace tools (listDir, readFile, writeFile, runBash) all
operate inside <example>/workspace/. Reads and writes outside that directory
are rejected by the path-jail with a clear error.
- All paths are relative to the workspace root.
listDir({ path: "." })lists the workspace root.readFile({ path: "AGENTS.md" })reads the memory file you also see in your system prompt (so reading it again is redundant; prefer the version Dawn injected for you).runBashspawns inside the workspace with a hard timeout. Use it for one-shot shell tasks; don't try to start long-lived background processes.
If you get a "Path is outside workspace" error, the path needs to be relative
to the workspace root and must not contain .. segments.
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 · 21 lines · 17 tokens per session scan A 1bf788d3d0ab
workspace-conventions is a skill published in the GitHub repository cacheplane/dawnai (327 stars, last pushed 1mo ago), licensed MIT. It adds 17 tokens to every session and 212 once invoked, about $0.0001 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 skills, from other repositories
data-visualization
Use for creating publication-quality charts and multi-panel analysis summaries. Triggers when tasks involve visualizing data, plotting results, creating charts, or producing visual reports from analysis output.
cuml-machine-learning
Use for GPU-accelerated machine learning on tabular data using NVIDIA cuML. Triggers when tasks involve classification, regression, clustering, dimensionality reduction, or model training on datasets.
blog-post
Writes and structures long-form blog posts, creates tutorial outlines, and optimizes content for SEO with cover image generation. Use when the user asks to write a blog post, article, how-to guide, tutorial, technical writeup, thought leadership piece, or long-form content.
social-media
Drafts engaging social media posts, writes hooks, suggests hashtags, creates thread structures, and generates companion images. Use when the user asks to write a LinkedIn post, tweet, Twitter/X thread, social media caption, social post, or repurpose content for social platforms.
schema-exploration
Lists tables, describes columns and data types, identifies foreign key relationships, and maps entity relationships in a database. Use when the user asks about database schema, table structure, column types, what tables exist, ERD, foreign keys, or how entities relate.
deepagents-thread-inspector
Inspect and explain conversations in the local Deep Agents Code SQLite session store. Use to look up the current thread's title or name, as a fallback when LangSmith trace tooling is unavailable, for offline or untraced sessions, or when asked to identify or summarize a local dcode thread, inspect checkpoint metadata…