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 onsager-ai/dev-skills --skill plan-daggit clone --depth 1 https://github.com/onsager-ai/dev-skillsWrote 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/onsager-ai/dev-skills/plan-dag)<a href="https://agentmods.dev/skills/onsager-ai/dev-skills/plan-dag"><img src="https://agentmods.dev/badge/skills/onsager-ai/dev-skills/plan-dag/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/onsager-ai/dev-skills/plan-dag"><img src="https://agentmods.dev/badge/skills/onsager-ai/dev-skills/plan-dag.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00136 | $0.04081 |
| Opus 5.5 | $0.00054 | $0.01632 |
| Sonnet 5.5 | $0.00027 | $0.00816 |
| Haiku 4.5 | $0.00014 | $0.00408 |
Grade A, and why
plan-dag 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.
How it starts
The opening of the file, as written. The whole thing — 200 lines — stays where its author put it; the contents beside it link to each section on GitHub.
plan-dag
Render the current plan as a dependency DAG so sequencing, the critical path, and parallelizable work are visible at a glance. Output is a high-DPI PNG with status fills, an "available next" highlight, and a double-bordered close sentinel — rasterised from a styled graphviz layout through headless Chromium, then sent to the user via SendUserFile.
This skill is repo-agnostic. It assumes a GitHub-backed issue tracker with sub-issue links and dependency-language prose; it makes no assumptions about specific labels, area taxonomies, or repo-specific dev-process skills.
Why PNG and not HTML / ASCII? PNG is the only output that survives every chat surface the skill targets. ASCII / Unicode box-drawing loses column alignment when surfaces reflow whitespace or apply syntax highlighting, and it can't carry the color/status fills that make state legible at a glance. Self-contained HTML pages don't render inline in chat — they download as attachments, which defeats the point of an at-a-glance diagram. PNG renders inline, keeps color, and doesn't depend on the host's font or rendering quirks.
When to use
- After a
what's nextsurvey, to commit to a sequence. - When asked "what's left for #N" on an umbrella spec with sub-issues.
- Before picking the next branch — to see what unblocks the most downstream work.
- When a spec fans out into N sub-issues and the dependency edges aren't all linear.
Skip when:
- A single-PR spec — the plan is the Plan section, not a DAG.
- An unanswered design question — drawing a DAG before alignment is theater.
- The "graph" is one linear chain of three or fewer nodes — a sentence is shorter than a diagram.
Inputs
| Parameter | Default |
|---|---|
| Scope | Inferred — current branch's spec, the umbrella the user named, or the open issues just surveyed. |
| Granularity | Spec-level; drop to sub-issue / PR level for an umbrella that has fanned out. |
| Output | High-DPI PNG (only target). --out <path> is required; emoji status indicators are on by default and can be turned off with --emoji=off if the rendering system lacks a color emoji font. |
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.
- 1mo ago First seen · 200 lines · 136 tokens per session scan A a3f7e6ec4914
plan-dag is a skill published in the GitHub repository onsager-ai/dev-skills (7 stars, last pushed 3d ago), licensed MIT. It adds 136 tokens to every session and 4,081 once invoked, about $0.0005 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 2026-08-31.
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