Agent skill · Audited from source

Article

skill · aaronjmars/aeonMIT licenceAudited 14 Oct 2026 · source 0448e87653f9

★ 774pushed today
✓SAFEGrade B · 89/100 · 14 Oct 2026 · 0448e87
774repo stars · whole aaronjmars/aeon

Is it safe? Yes — SAFE, grade B (89/100). We read this skill's source at commit 0448e87653f9 and found no filesystem, network or shell access and no hard-coded secrets. What it does: Write a publication-ready article in one of three angles - a trending long-form piece, a watched-repo thesis, or a project-through-a-lens essay. Optional Replicate hero image with --visual.

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Cite this page

ModelsAtlas. “Article (aaronjmars/aeon)”. Retrieved 14 Oct 2026. https://modelsatlas.com/skills/aaronjmars/article

3 skills are called “Article”. You are viewing aaronjmars/aeon.

Trust audit

Audit 0.4.1 · source read 14 Oct 2026

Trust score89/100✓SAFE B
0 critical0 high0 medium0 low0 info

SAFE means nothing in the source contradicts what the skill says it does. Grade B is shared by 13,985 of 14,816 audited skills.

What the source does

  • FilesystemNone observedNo reads or writes in the source
  • NetworkNone observedNo outbound calls in the source
  • ShellNone observedNo commands run in the source
  • DependenciesPinnedNothing floats
  • SecretsNone foundNo keys in source

Five audit layers

LayerWhat we checkResultFindings
L0 ProvenanceRepo owner, licence, archive status, activityPASS0
L1 Static sourceSecrets, path traversal, supply chain, hidden codeNA0
L2 InstructionsPrompt injection, authority framing, hidden directivesPASS0
L3 InventoryThe files and declarations match the sourcePASS0
L4 SandboxRun in isolation and watch behaviourSKIPPED why0

Gates applied: no behavioural pass.

Findings (0)

No findings at any severity. We re-audit when the source changes.

Audit 0.4.1 · source sha 0448e87653f9 · 14 Oct 2026Report an issue or request a re-scan

Provenance

Who published it, and what the verdict is pinned to

  • Publisheraaronjmars GitHub organizationOwner of the repository this skill is read from
  • Source folderaaronjmars/aeon/skills/articleThe exact folder we audited
  • LicenceMITAs the repository states it
  • Commit pinned for this verdict0448e87653f9A new audit runs when the source changes
  • Repository statusNot archivedPushed today
  • Sandboxed runNot runSkills are read, not executed; layer L4 is skipped

What it tells the agent

Full source on GitHub ↗

Its description: Write a publication-ready article in one of three angles - a trending long-form piece, a watched-repo thesis, or a project-through-a-lens essay. Optional Replicate hero image with --visual.

---
name: article
description: Write a publication-ready article in one of three angles - a trending long-form piece, a watched-repo thesis, or a project-through-a-lens essay. Optional Replicate hero image with --visual.
metadata:
  title: Article
  category: basics
  var: ""
  tags:
    - content
    - dev
  requires:
    - REPLICATE_API_TOKEN?
---
> **${var}** — Selector: `[angle:arg] [--visual]`. The **angle** prefix picks the article type; append **`--visual`** (or `visual`) anywhere to also generate a Replicate hero image.
>
> - **empty** → `standard` general long-form article on an auto-selected trending topic. If the resolved topic is a single explainable mechanism, it becomes a technical explainer instead.
> - **`<topic>`** (no recognized prefix) → `standard` article on that topic.
> - **`repo:<owner/repo>`** → `repo` thesis-driven article about that repo. `repo:<angle>` (e.g. `repo:architecture`) or bare `repo:` uses the repo from `memory/watched-repos.md` with that angle / an auto-selected angle — this preserves repo-article's original input.
> - **`lens:<topic>`** → `lens` project-through-a-lens essay framed by that lens (e.g. `lens:unix philosophy`). Bare `lens:` auto-selects the lens.
> - **`--visual`** appended to any of the above → after the body is written, generate a Replicate hero image (optional `REPLICATE_API_TOKEN`; ships text-only if absent).
>
> Examples: `""`, `"entropy trajectory reasoning --visual"`, `"repo:aeonfun/aeon"`, `"repo:roadmap"`, `"lens:regulation wave --visual"`.

Today is ${today}. Write a high-quality, publication-ready article. No placeholders.

## Shared preamble (every run)

1. Read `memory/MEMORY.md` for context on what topics/articles have been covered recently.
2. Read the last 3–7 days of `memory/logs/` for recent activity — and **don't re-report** something already covered.
3. **Parse `${var}` into `angle` + `visual`:**
   - Detect a standalone `--visual` or `visual` token anywhere in `${var}`; if present set **`visual = true`** and strip that token. Otherwise `visual = false`.
   - From what remains: if it starts with `repo:` → `angle = repo`, `arg =` the rest. If it starts with `lens:` → `angle = lens`, `arg =` the rest. Otherwise → `angle = standard`, `arg =` the whole remaining string (empty ⇒ auto-select).
4. Dispatch to the matching angle section below. If `visual = true`, run the **Visual add-on** after the article body is written, regardless of angle.

---

## Angle: standard — long-form article / technical explainer

A single long-form article. It takes one of two structures depending on the topic:

- **General article** — a broad trend, development, or event. 600–800 words.
- **Technical explainer** — a single explainable mechanism, technique, algorithm, or system. 600–1000 words, using the explainer structure below.

### Topic selection (standard)

- If `arg` (the topic) is set, use it verbatim. If it clearly names a single mechanism/technique/system → **technical explainer** structure; otherwise → **general article** structure.
- If `arg` is empty, pick deterministically — first hit wins:
  1. **Explainer candidate:** a single most non-obvious mechanism inside the newest file in `output/articles/` from the last 3 days; else the newest "Paper Pick" in `memory/logs/` from the last 7 days (its headline mechanism); else a specific technique/algorithm/system surfaced in the last 7 days of logs. If a strong single-mechanism candidate exists → **technical explainer** on it. Reject any candidate broader than a single mechanism (e.g. "AI agents" — too vague; "MCP tool-routing via vector search" — usable).
  2. **General candidate:** otherwise search the web for the most interesting recent development in AI, crypto/DeFi, or consciousness research — pick whichever has the most compelling story today (WebSearch) → **general article**.

### Voice (technical explainer)

If a `soul/` directory exists, read the soul files for voice calibration: `soul/SOUL.md` (identity, worldview, opinions), then `soul/STYLE.md` (writing style, sentence structure, anti-patterns). This is *you explaining a mechanism to a smart friend* — more precision than a general article, same voice. No textbook tone, no "let's explore." If `soul/` is empty, default to clear, direct, neutral.

### Research

**General article:** read 2–3 source articles with WebFetch to gather facts and quotes.

**Technical explainer:** run **three distinct WebSearch queries** so you triangulate rather than echo one source:
1. `"<topic>" how it works` — mechanism explanations
2. `"<topic>" benchmark OR results OR latency OR cost` — concrete numbers
3. `"<topic>" limits OR criticism OR fails OR doesn't work` — failure modes and pushback

If the topic is from a paper, also fetch the paper metadata and abstract:
```bash
curl -s "https://api.semanticscholar.org/graph/v1/paper/search?query=TOPIC&limit=5&fields=title,authors,abstract,url,publicationDate,openAccessPdf" \
  || echo "curl failed — use WebFetch on https://www.semanticscholar.org/search?q=TOPIC instead"
```
Use **WebFetch** to read the 2–3 best sources in depth. **At least one source must be primary**: a paper (arXiv / OpenReview / Semantic Scholar), official documentation, the project's own README, or a code repo. Blog summaries alone are not enough — they often mangle the mechanism.

Extract:
- The **single core mechanism** — the one move that, once you grok it, makes the rest fall into place.
- A **vivid analogy** for the mechanism, and the precise place where the analogy breaks down (the breakage is the interesting part).
- **3–5 specific numbers** — benchmarks, latencies, costs, error rates, training compute, parameter counts. Each number gets a source URL.
- **What would falsify this** — what result, if observed, would mean the mechanism doesn't work as claimed. If you can't name one, the explanation isn't sharp enough — keep digging.

### Write

**General article** — 600–800 words in Markdown. Include:
- A compelling title
- A sho

Excerpt, first 6,000 characters of SKILL.md, verbatim from the audited commit. It is text from someone else’s repository, quoted so you can judge it before your agent reads it.

Install

Pinned to the audited commit 0448e87

Download folder ↗
git clone https://github.com/aaronjmars/aeon
git -C aeon checkout 0448e87653f9

The author documents no install command, so this uses the repository directly. Our verdict covers commit 0448e87653f9 only.

Works in

The author has not said which agents this skill supports, and we have not tested it in any.

Audit history

Every audit, every source change

  1. ✓SAFE B 89 / 100

    first audit · source 0448e87653f9

Questions about Article

What does the Article skill do?
The most autonomous AI agent framework: runs unattended on GitHub Actions, self-healing skills, drives Claude Code, Grok, Codex & more. No approval loops. Configure once, forget forever.
Is Article safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Article access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (0448e87653f9), read on 2026-10-14. The repository is watched, and a new audit runs when it changes — this is the first audit.

Sources

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