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/currents-dev/currents-mcp/collect-evidencenpx skills add currents-dev/currents-mcp --skill collect-evidencegit clone --depth 1 https://github.com/currents-dev/currents-mcpWrote 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/currents-dev/currents-mcp/collect-evidence)<a href="https://agentmods.dev/skills/currents-dev/currents-mcp/collect-evidence"><img src="https://agentmods.dev/badge/skills/currents-dev/currents-mcp/collect-evidence.svg" alt="Measured on agentmods" 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 | $0.00117 | $0.01377 |
| Opus 5 | $0.00059 | $0.00688 |
| Sonnet 5 | $0.00023 | $0.00275 |
| Haiku 4.5 | $0.00012 | $0.00138 |
Grade A, and why
collect-evidence scanned grade A with 1 finding 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 4d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -sL -o after-order-summary.png "<signed url>" How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Collect Evidence
Show that a change you implemented works, or demo it, by capturing artifacts in CI tests and retrieving them from Currents. The output is a screenshot, video, trace, or attachment to put in a PR, ticket, or status update, plus a dashboard link that does not expire.
Use this when the work is done and someone needs to see it. To debug a test that is failing, use currents-get-context instead.
Do not capture evidence locally: CI runs in a clean, reproducible environment, artifacts are stored and shareable, and this works even without a local browser.
Evidence types and when to use each:
| Evidence | Use for | Captured by |
|---|---|---|
| Screenshot | Visual state, before/after UI comparison | page.screenshot() attached to the test |
| Text/JSON attachment | CLI output, API responses, computed values, diffs | testInfo.attach() |
| Video | Multi-step flows, interactions | Playwright/Cypress video recording |
| Trace | Full replay with DOM, network, console | Playwright tracing |
| GIF | Embedding a short demo in a PR/issue | Convert downloaded video with ffmpeg |
Requirements
- The project reports CI test results to Currents (a Currents reporter is configured; runs appear in the dashboard).
- Currents MCP server connected, or
CURRENTS_API_KEYfor REST calls tohttps://api.currents.dev/v1.
Workflow
1. Instrument a test to capture the evidence
Write or extend a test that exercises the change you implemented and captures the artifact at the moment it is visible. See references/instrumentation.md for Playwright and Cypress snippets and reporter configuration.
Rules that make retrieval and pairing work later:
- Name attachments deterministically (
evidence-order-summary.png, not timestamped names). Before/after pairing matches on test title + attachment name. - One test per piece of evidence where practical; give the test a distinct, searchable title (e.g. include the word
evidenceor the feature name). - Keep screenshots deterministic: fixed viewport, disable animations, mask dynamic regions.
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.
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.
- 4d ago First seen · 84 lines · 117 tokens per session scan A a082c4f6001e
collect-evidence is a skill published in the GitHub repository currents-dev/currents-mcp (20 stars, last pushed yesterday), licensed Apache-2.0. It adds 117 tokens to every session and 1,377 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
playwright-cli
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playwright-dev
Explains how to develop Playwright - add APIs, MCP tools, CLI commands, and vendor dependencies.
playwright-devops
DevOps workflows for Playwright - CI failure analysis, workflow debugging, and release operations.
ffmpeg
Video and audio processing with FFmpeg. Use for format conversion, resizing, compression, audio extraction, and preparing assets for Remotion. Triggers include converting GIF to MP4, resizing video, extracting audio, compressing files, or any media transformation task.
playwright-recording
Record browser interactions as video using Playwright. Use for capturing demo videos, app walkthroughs, and UI flows for Remotion videos. Triggers include recording a demo, capturing browser video, screen recording a website, or creating walkthrough footage.
elevenlabs
Generate AI voiceovers, sound effects, and music using ElevenLabs APIs. Use when creating audio content for videos, podcasts, or games. Triggers include generating voiceovers, narration, dialogue, sound effects from descriptions, background music, soundtrack generation, voice cloning, or any audio synthesis task.