argos-upload

A workflow for uploading screenshots, images, and screen recordings to Argos, a service for sharing visual test and review material. It returns a shareable link and Markdown, or can attach the media to a branch or pull request.

In plain words
What is it for?
Sharing before-and-after interface images, browser-test videos, and other visual evidence in pull requests, issues, changelogs, or chats.
Why use it?
It gives reviewers visual evidence for interface changes, bug reproductions, and rendering problems without requiring them to run the code locally.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/argos-ci/argos-javascript/argos-upload
Any agent
npx skills add argos-ci/argos-javascript --skill argos-upload
Clone the repo
git clone --depth 1 https://github.com/argos-ci/argos-javascript

Made for: Claude Code, Codex.

Per session 168 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,935 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00168 $0.02935
Opus 5 $0.00084 $0.01468
Sonnet 5 $0.00034 $0.00587
Haiku 4.5 $0.00017 $0.00294

Measured 2d ago against content hash a8ea9950e843, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

argos-upload 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.

skills/argos-upload/SKILL.md · 259 lines

How it starts

The opening of the file, as written. The whole thing — 259 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Argos media upload

argos media upload <files...> uploads standalone images and videos — not tied to a build or a test run — and prints a share URL and a Markdown embed for each.

argos media upload checkout-before.png checkout-after.png --branch feat/checkout

Run argos media --help for exact flags. This skill covers the parts --help cannot: when to upload, how the result reaches a human, and how to read back what they say about it.

When to upload

Upload when a change is visual and a human has to see it to judge it:

  • You changed UI and are working on a branch or a pull request. A before/after pair saves the reviewer from checking out your branch.
  • You recorded a Playwright video or a screen recording of a bug reproduction.
  • You are reporting a rendering problem that a code snippet cannot convey.

Do not upload when text does the job. A stack trace, a diff, a log excerpt and a list of failing test names are all better as text: searchable, quotable, and readable in a terminal. An unnecessary screenshot is noise in the review.

Do not upload build screenshots that Argos already has. If a visual test run produced them, they are already in the build and linked from the pull request — use argos build snapshots instead.

Getting it into a pull request

Name where the media belongs and Argos does the posting. It keeps one comment per pull request listing every media attached to it, edited in place rather than appended to.

argos media upload after.png --pr 1234              # the pull request exists
argos media upload after.png --branch feat/checkout # it does not, yet

--branch is the one to reach for while working. The media is staged: it has its share URL immediately, and the moment a pull request opens for that branch Argos attaches it and posts the comment on its own. You do not have to come back and connect the two. --pr publishes straight away.

Passing neither uploads a loose media: a share URL and nothing else. That is the right call for a chat message or an issue, where you paste the Markdown yourself. Neither flag is inferred from the environment, CI included — an upload does not post to a pull request unless you asked it to. Two consequences worth knowing before you leave them off: nothing will ever attach that media to a pull request, and since a loose media's identity is only its name, uploading shot.png from two different branches makes them versions of one media rather than two.

Read the full file on GitHub · 259 lines

Files

What ships with it

1 file 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.

Changes

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.

  1. 2d ago First seen · 259 lines · 168 tokens per session scan A a8ea9950e843

Subscribe to this mod's changes

argos-upload is a skill published in the GitHub repository argos-ci/argos-javascript (18 stars, last pushed 7d ago), licensed MIT. It adds 168 tokens to every session and 2,935 once invoked, about $0.0008 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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