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 simota/agent-skills --skill voicegit clone --depth 1 https://github.com/simota/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/simota/agent-skills/voice)<a href="https://agentmods.dev/skills/simota/agent-skills/voice"><img src="https://agentmods.dev/badge/skills/simota/agent-skills/voice/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/simota/agent-skills/voice"><img src="https://agentmods.dev/badge/skills/simota/agent-skills/voice.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
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 →
- high Prompt Injection · line 6 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- medium Excessive Agency · line 118 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00031 | $0.05173 |
| Opus 5 | $0.00015 | $0.02586 |
| Sonnet 5 | $0.00006 | $0.01035 |
| Haiku 4.5 | $0.00003 | $0.00517 |
Grade A, and why
voice 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 6d 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 — 257 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Voice
Customer-feedback collection and synthesis agent for surveys, reviews, sentiment analysis, feedback classification, and action-ready insight reports.
Trigger Guidance
Use Voice when the user needs:
- Design NPS, CSAT, CES, or exit surveys
- Classify and categorize user feedback
- Synthesize multi-channel feedback signals
- Analyze sentiment in reviews, tickets, or comments
- Write insight reports from feedback data
- Recommend owners and follow-up actions from feedback
- Establish or improve feedback loops
- Optimize survey response rates and reduce collection bias
- Design LLM-powered feedback classification pipelines
- Detect emotion beyond polarity (frustration, joy, anger, surprise) in feedback data
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _common 10 B
- reference/_common 13 B
- reference/autorun-schema.md 885 B
- reference/csat-ces-measurement.md 9.8 KB
- reference/csat-ces-surveys.md 3.4 KB
- reference/exit-survey.md 1.3 KB
- reference/feedback-widget-analysis.md 5.1 KB
- reference/kano-model.md 1.3 KB
- reference/multi-channel-synthesis.md 7.6 KB
- reference/nps-survey.md 1.3 KB
- reference/thematic-coding.md 10 KB
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.
- 6d ago First seen · 257 lines · 31 tokens per session scan A 905ac30a1344
voice is a skill published in the GitHub repository simota/agent-skills (76 stars, last pushed 7d ago), licensed MIT. It adds 31 tokens to every session and 5,173 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 2026-09-03.
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