verification

verification is a skill for Claude Code, Codex from gabrielmoreira/agent-skills-mirror. It costs 19 tokens per session (1,058 once invoked), scanned A, original, MIT.

A checklist for confirming that edits made by an agent actually appear in an OpenChatCut project and its editor.

In plain words
What is it for?
Use it to verify timeline edits, captions, effects, trims, layers, layout, and release or desktop workflows.
Why use it?
It replaces assumptions with evidence from the project structure, rendered timeline frames, or a real editor run. The required level depends on the risk of the change.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to verify timeline edits, captions, effects, trims, layers, layout, and release or desktop workflows.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gabrielmoreira/agent-skills-mirror/verification
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.

Any agent
npx skills add gabrielmoreira/agent-skills-mirror --skill verification
Clone the repo
git clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirror

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for verification

README.md
[![agentmods](https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/verification/github.svg)](https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/verification)
Your own site
<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.

agentmods 80×15 button for verification

Your own site · 80×15
<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>
Per session 19 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,058 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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]
How audits are shown
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 5.1 $0.00019 $0.01058
Opus 5 $0.00010 $0.00529
Sonnet 5 $0.00004 $0.00212
Haiku 4.5 $0.00002 $0.00106

Measured 10d ago against content hash 11d6ef0a3e69, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

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.

mirrors/repos/0xsline@OpenChatCut/src/agent/skills/verification/SKILL.md · 90 lines

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:

  1. read_project for structure: assets, tracks, items, frame placement, timeline duration.
  2. 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/). Use view_asset_frames with 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_frames renders the composed timeline (the editor-truth check); view_asset_frames samples raw source frames. Pick by what you are verifying.
  • There is no separate get_contact_sheet tool in this build — the contact sheet is what view_asset_frames / view_timeline_frames already 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_frames and 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":[...]}) after read_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.

Read the full file on GitHub · 90 lines

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. 10d ago First seen · 90 lines · 19 tokens per session scan A 11d6ef0a3e69

Subscribe to this mod's changes

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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