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.
git clone --depth 1 https://github.com/kenrogers/elevenlabs-claude-pluginWrote 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/commands/kenrogers/elevenlabs-claude-plugin/expert-advice)<a href="https://agentmods.dev/commands/kenrogers/elevenlabs-claude-plugin/expert-advice"><img src="https://agentmods.dev/badge/commands/kenrogers/elevenlabs-claude-plugin/expert-advice/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/commands/kenrogers/elevenlabs-claude-plugin/expert-advice"><img src="https://agentmods.dev/badge/commands/kenrogers/elevenlabs-claude-plugin/expert-advice.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00035 | $0.00505 |
| Opus 5 | $0.00017 | $0.00253 |
| Sonnet 5 | $0.00007 | $0.00101 |
| Haiku 4.5 | $0.00003 | $0.00051 |
Grade A, and why
expert-advice 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 9d 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
- Find all Python and TypeScript/JavaScript files in the project that use the ElevenLabs SDK (search for imports of
elevenlabs,@11labs/react,@11labs/client, or references toELEVENLABS_API_KEY) - Fetch the latest docs from
elevenlabs.io/docs/llms.txtfor current reference. If fetch fails, fall back to the knowledge base at.claude/elevenlabs/knowledge/general-elevenlabs-knowledge.mdbut warn the user that the review is based on potentially stale patterns. - Read the anti-patterns block from
.claude/elevenlabs/knowledge/general-elevenlabs-knowledge.md(between<!-- HOOK_PATTERNS_START -->and<!-- HOOK_PATTERNS_END -->markers) for machine-readable pattern checks - Review all ElevenLabs code against this checklist:
- API usage patterns — streaming vs batch, correct endpoints, proper model selection
- Authentication & key management — env vars, no client-side exposure, proper token usage
- Error handling & retry logic — ApiError handling, 429 backoff, timeout handling
- Voice agent lifecycle — proper session start/end, audio interface cleanup, WebSocket management
- ClientTools registration — async handling, proper parameter extraction, error returns
- Audio format & quality — correct model for use case, output format settings
- Rate limiting awareness — backoff strategy, request queuing for high-volume usage
- Generate a structured report organized by severity:
- 🔴 Critical — Security issues, missing required params, will crash at runtime
- 🟠 High — Incorrect patterns that will cause bugs or poor UX
- 🟡 Medium — Suboptimal patterns, performance issues
- 🟢 Low — Style suggestions, minor improvements
- Offer to apply fixes — if the user agrees, use the Edit tool to apply changes directly
- After fixes, suggest
/elevenlabs:test-agentif voice agent code was reviewed
User's request: $ARGUMENTS
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.
- 9d ago First seen · 26 lines · 35 tokens per session scan A 4dd8441e3026
expert-advice is a command published in the GitHub repository kenrogers/elevenlabs-claude-plugin (3 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 505 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other commands, from other repositories
sdd-init
Initialize SDD context — detects project stack and bootstraps persistence backend.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.
argos
A command for checking whether an implementation matches its design deliverables. Its Korean description compares the work to the design as part of a completion inspection.