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/aeonfun/aeon/auto-workflownpx skills add aeonfun/aeon --skill auto-workflowgit clone --depth 1 https://github.com/aeonfun/aeonWhat 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 | $0.00048 | $0.07380 |
| Opus 5 | $0.00024 | $0.03690 |
| Sonnet 5 | $0.00010 | $0.01476 |
| Haiku 4.5 | $0.00005 | $0.00738 |
Grade A, and why
auto-workflow 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- auto-workflow — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 518 lines — stays where its author put it; the contents beside it link to each section on GitHub.
${var} — selects the mode:
- Analyze (default): a URL to analyze (GitHub repo, X account, blog, project site, API docs, etc.). Multiple URLs comma-separated. Prefix a URL with
force:to re-analyze one already in the ledger. Produces a tiered recommendation article + anaeon.ymldiff — it does not mutateaeon.yml.- Enable:
enable:slug1,slug2,…— flip those skills'enabled: false → trueinaeon.yml, validate each againstskills/, then commit + open a PR.enable:dry-run:slug1,slug2validates and reports without editing, committing, or opening a PR.Example values:
https://example.com/blog·@vitalikbuterin, github.com/foundry-rs/foundry·force:https://mirror.xyz/somedao·enable:rss-digest,github-monitor·enable:dry-run:price-alert
Overview
One skill, two ends of the same loop: analyze decides what to enable for a new watch target; enable actually flips the switch. Dispatch enable: with the slugs the analyze run put in its MUST tier and you close the loop — recommendation to merged PR — without a second skill.
Analyze mode verifies every recommendation is backed by an observed signal on the URL, tiers output into MUST (2–3 max) / SHOULD / NICE with a one-line concrete "why", emits a delta against the current aeon.yml rather than a full config dump, stays silent when existing config already covers the URL, and anchors skill names in skills.json (authoritative), not a stale mapping table. It writes an article + updates a ledger; it never edits aeon.yml.
Enable mode does the mechanical part analyze deliberately leaves to the operator: a slug-scoped enabled: false → true substitution in aeon.yml, gated by directory presence / current-disabled-state / chain-conflict checks, committed on a fresh branch and shipped as a PR with per-skill rationale. Explicit opt-in only — the operator names the slugs; nothing flips on main until they click merge.
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 · 518 lines · 48 tokens per session scan A 36db1f59e238
auto-workflow is a skill published in the GitHub repository aeonfun/aeon (706 stars, last pushed 2d ago), licensed MIT. It adds 48 tokens to every session and 7,380 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 2026-08-30.
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