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 heygen-com/liveavatar-agent-skills --skill liveavatar-feedbackgit clone --depth 1 https://github.com/heygen-com/liveavatar-agent-skillsWrote 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/heygen-com/liveavatar-agent-skills/liveavatar-feedback)<a href="https://agentmods.dev/skills/heygen-com/liveavatar-agent-skills/liveavatar-feedback"><img src="https://agentmods.dev/badge/skills/heygen-com/liveavatar-agent-skills/liveavatar-feedback/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/heygen-com/liveavatar-agent-skills/liveavatar-feedback"><img src="https://agentmods.dev/badge/skills/heygen-com/liveavatar-agent-skills/liveavatar-feedback.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk fail
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 | $0.00164 | $0.01957 |
| Opus 5 | $0.00082 | $0.00979 |
| Sonnet 5 | $0.00033 | $0.00391 |
| Haiku 4.5 | $0.00016 | $0.00196 |
Grade A, and why
liveavatar-feedback 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 11d 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 -X POST https://api.liveavatar.com/v1/feedback/agents \ How it starts
The opening of the file, as written. The whole thing — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LiveAvatar Feedback Collection
This skill collects integration feedback and sends it to the LiveAvatar team. It fires in three scenarios:
- Post-implementation — the user just finished an integration (Embed, FULL, or LITE)
- Frustration detected — repeated errors, explicit complaints, or visible friction
- Explicit request — the user asks to give feedback or report an issue
When to Trigger
Activate this skill when ANY of these are true:
- The user says they're done or the integration is working
- The user expresses frustration ("this is broken", "why doesn't this work", "I'm stuck")
- The user explicitly asks to give feedback, report a bug, or share a suggestion
- You've seen 3+ failed attempts at the same step during integration
- The user says they're giving up or abandoning the integration
Do NOT trigger unprompted in the middle of active implementation. Wait for a natural pause or completion point.
Step 1: Gather Context from the Conversation
Before prompting the user, review the conversation history and silently compile:
- Use case — what the user is building (e.g., "customer support avatar for a SaaS dashboard"). This comes from the discovery phase, the user's stated goal, or their codebase.
- Blockers — anything that caused friction during the integration. Look for: errors hit, steps that required retries, confusing API behavior, silent failures, missing docs, or anything the user explicitly complained about.
Compact both into short, factual summaries. These are telemetry the agent drafts — the user will review them before anything is sent.
Step 2: Ask the User for Permission and Additional Feedback
You must get explicit permission before sending anything. Present what you've gathered and ask the user to approve, edit, or decline.
Adapt tone to context — celebratory after success, empathetic if frustrated.
After successful implementation:
Your LiveAvatar integration is working! The LiveAvatar team collects anonymous integration feedback to improve the developer experience. Would you be okay with me sending a short summary?
Here's what I'd send:
- **Use case:** <your compacted summary>
- **Blockers:** <your compacted summary, or "None">
Want to add anything else in your own words? (Feature requests, suggestions, general thoughts — totally optional.)
**Nothing is sent until you say yes.** You can also edit or remove anything above.
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.
- 11d ago First seen · 167 lines · 164 tokens per session scan A 1c3e17c3c9e2
liveavatar-feedback is a skill published in the GitHub repository heygen-com/liveavatar-agent-skills (9 stars, last pushed today), licensed MIT. It adds 164 tokens to every session and 1,957 once invoked, about $0.0008 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 2026-08-31.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…