Loom is a delivery harness that guides coding agents through defining, planning, implementing, checking, repairing, previewing, and handing off software changes. It is used with Claude Code, Codex, OpenCode, and other coding agents when work must be continued or inspected across sessions. The catalogue skills, hooks, commands, instructions, and plugin extend or operate this workflow.
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 valkor-ai/loom --skill visual-qagit clone --depth 1 https://github.com/valkor-ai/loomWrote 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/valkor-ai/loom/visual-qa)<a href="https://agentmods.dev/skills/valkor-ai/loom/visual-qa"><img src="https://agentmods.dev/badge/skills/valkor-ai/loom/visual-qa/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/valkor-ai/loom/visual-qa"><img src="https://agentmods.dev/badge/skills/valkor-ai/loom/visual-qa.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00045 | $0.00371 |
| Opus 5.5 | $0.00018 | $0.00148 |
| Sonnet 5.5 | $0.00009 | $0.00074 |
| Haiku 4.5 | $0.00005 | $0.00037 |
Grade A, and why
visual-qa 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 1mo 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.
What it actually says
Godot Visual QA
Visual QA is evidence review, not a style contest. Compare the capture with the task's acceptance criteria and report only issues that affect the requested behavior, visibility, composition, or operation.
Capture first
Use the screenshot skill or the Godot MCP screenshot tool. Wait for the scene
to render before capturing. For motion, capture a reference frame followed by
several frames at a fixed interval so movement can be checked.
Review checklist
- The intended scene is running and the viewport is not black or empty.
- The camera shows the requested objects at a usable scale.
- Meshes, textures, lighting, and materials are present rather than placeholders when the task requires them.
- Objects that should move or interact visibly change state between frames.
- UI text and controls fit their containers and do not overlap the scene.
- Collision shapes, bodies, and navigation behave consistently with the visual geometry when debug overlays are enabled.
- Errors visible in the capture or reported by the runtime are recorded as evidence, not guessed away.
Result format
Record a short result in the Loom task evidence or handoff:
Verdict: pass | warning | fail
Evidence: <capture paths>
Observed: <what the frames show>
Issues: <file and location, or none>
Use fail for an acceptance-blocking issue, warning for a non-blocking
defect, and pass only when the supplied criteria are visible in the capture.
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.
- 1mo ago First seen · 47 lines · 45 tokens per session scan A fc3102c60e97
visual-qa is a skill published in the GitHub repository valkor-ai/loom (1,262 stars, last pushed today), licensed Apache-2.0. It adds 45 tokens to every session and 371 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
develop-web-game
Use when Codex is building or iterating on a web game (HTML/JS) and needs a reliable development + testing loop: implement small changes, run a Playwright-based test script with short input bursts and intentional pauses, inspect screenshots/text, and review console errors with rendergametotext.
test-playable-web-games
Test a playable browser game end to end with deterministic fixtures and real browser evidence. Use for gameplay QA, regression testing, controls, accessibility, responsive/mobile testing, save flows, console checks, performance smoke tests, and release verification.
threejs-qa-release
Verify and release Three.js browser games: playtest QA, automated bot playtests, mobile and responsive checks, production builds, static-hosting base paths, debug gating, bundle review, screenshots, visual regression baselines, canvas-pixel inspection with measured metrics, and release risk reports.
pie-testing
Start, stop, and query Play-In-Editor (PIE) sessions for runtime testing of Blueprints, gameplay logic, widgets, AI, and any in-game behavior. Use when the user asks you to "play", "test", "run", "PIE", "start/stop the game", or otherwise needs a live game world to validate changes.
web-game-performance-and-testing
Use when working on any browser game (Phaser, PixiJS, three.js, Babylon.js, PlayCanvas, Excalibur, KAPLAY) - requestAnimationFrame with clamped delta and visibility pause, zero-allocation frame loops, measuring in DevTools, bundle and asset size budgets, Vitest with seeded RNG and injected time, and a seeded…
smoke-check
Run the critical path smoke test gate before QA hand-off. Executes the automated test suite, verifies core functionality, and produces a PASS/FAIL report. Run after a sprint's stories are implemented and before manual QA begins. A failed smoke check means the build is not ready for QA.