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 gabrielmoreira/agent-skills-mirror --skill verificationgit clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirrorWrote 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/gabrielmoreira/agent-skills-mirror/verification)<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/verification"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/verification/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/gabrielmoreira/agent-skills-mirror/verification"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/verification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium MCP Rug Pull · line 12 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00019 | $0.01058 |
| Opus 5 | $0.00010 | $0.00529 |
| Sonnet 5 | $0.00004 | $0.00212 |
| Haiku 4.5 | $0.00002 | $0.00106 |
Grade A, and why
verification 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 10d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Verification
Use the lowest verification level that proves the requested result:
| Level | Required evidence |
|---|---|
| L0 | Static checks such as the focused verification script, npx tsc --noEmit, tests, and build. |
| L1 | A real Agent run against the editor at localhost:5199, followed by structural and rendered evidence. |
| L2 | The packaged desktop app completing the user scenario, including human visual review where automation is insufficient. |
Runtime behavior changes require L0 + L1. Release and desktop-only changes also require L2 when the packaged app is the behavior under test.
Prefer two signals:
read_projectfor structure: assets, tracks, items, frame placement, timeline duration.- A visual capture path for rendered evidence at exact frames.
Use view_timeline_frames for composed timeline proof. This verifies the edited OpenChatCut timeline: trims, layers, captions, effects,
markers, placeholders, crops, transitions, and layout.
For raw source-asset frame inspection, choose the cheapest path based on where the bytes live:
- The agent in this build has no local filesystem access; all source bytes live
in the project media store (
/media/uploads/). Useview_asset_frameswith the project asset id — the server takes an ffmpeg contact-sheet fast path automatically, so it is already the cheapest source-frame route. view_timeline_framesrenders the composed timeline (the editor-truth check);view_asset_framessamples raw source frames. Pick by what you are verifying.- There is no separate
get_contact_sheettool in this build — the contact sheet is whatview_asset_frames/view_timeline_framesalready return.
Use local/remote source-frame artifacts only for source understanding, moment selection, and rough trim decisions, not as edited output or timeline proof.
For local-only or upload-in-progress media, composed timeline proof may be
blocked until the asset has bytes available to the renderer. Source-frame
inspection via view_asset_frames still works as long as the asset's bytes are
on disk (/media/uploads/).
If both visual proof paths are blocked, ask the user to inspect the OpenChatCut editor directly and note the blocker explicitly.
Useful checks:
- After import:
read_project({ "view": "assets", "assetId": "<prefix>" }) - After move/trim:
read_project({ "view": "timeline" }) - After visual overlay or MG on any timeline media:
view_timeline_frames({ "frames": [30, 45, 75] }), then look at the returned frames. - For user-requested source selection or visual moment picking: sample stills with
view_asset_framesand inspect them. Use that only to choose source files, moments, and rough trims. Build the visible edit as OpenChatCut timeline items. Do not treat raw source inspection as timeline verification or as permission to produce the edited video elsewhere. - For source-frame inspection: call
view_asset_frames({"assetId":"...","sourceTimesMs":[...]})afterread_project({"view":"assets"})confirms the asset id/type. Prefer this over asking the user to reattach the file. - For local-only visual verification: upload/register cloud-readable media before relying on connector visual proof.
- For no-source validation: confirm the tool manifest exposed the parameters you used, then record the visible proof in the trace log.
When talking about seconds, verify the fps from read_project or use adapter tools that resolve fps internally.
When reporting a timeline item location, use only the latest read_project structure for track alias, item id, start, duration, and asset id. Do not report planned/default tracks or tool-call intent as verified placement.
Do not treat a command-line JSON response alone as sufficient when the user asks whether the editor reflects the result. Use the editor URL or visual proof when practical.
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.
- 10d ago First seen · 90 lines · 19 tokens per session scan A 11d6ef0a3e69
verification is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (17 stars, last pushed yesterday), licensed MIT. It adds 19 tokens to every session and 1,058 once invoked, about $0.0001 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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