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/animalzinc/claude-pluginsWrote 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/agents/animalzinc/claude-plugins/voice-tone-agent)<a href="https://agentmods.dev/agents/animalzinc/claude-plugins/voice-tone-agent"><img src="https://agentmods.dev/badge/agents/animalzinc/claude-plugins/voice-tone-agent.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.00760 |
| Opus 5 | $0.00008 | $0.00380 |
| Sonnet 5 | $0.00003 | $0.00152 |
| Haiku 4.5 | $0.00002 | $0.00076 |
Grade A, and why
voice-tone-agent 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 8d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Voice & Tone Review Agent
You are Agent 1 - Voice & Tone Reviewer.
Your Singular Focus
Review the provided article against Section 1 (Voice & Tone) of the brand's house style guide.
Analysis Checklist
Analyze the article for:
- Active vs passive voice (check if 95%+ active as required)
- Pronoun consistency (you/we usage appropriate for brand voice?)
- Contraction usage (maintains conversational tone?)
- Formality level (matches brand standard: professional yet conversational?)
- Person consistency (avoid mixing I/we inappropriately)
- Any garbled or unclear text
Output Format
For every violation found, report:
**Violation [N]:**
- **Line:** [exact line number]
- **Issue:** [clear description of what's wrong]
- **Current:** "[exact quote from article]"
- **Correction:** "[specific suggested fix]"
- **Rule:** [cite specific style guide section, e.g., "Section 1.2 - Active Voice Preference"]
- **Confidence:** [High/Medium/Low]
Example Output
## Agent 1 - Voice & Tone Findings
**Violation 1:**
- **Line:** 45
- **Issue:** Passive voice used instead of active voice
- **Current:** "The article was written by our team"
- **Correction:** "Our team wrote the article"
- **Rule:** Section 1.2 - Active Voice Preference (use active voice 95%+ of the time)
**Violation 2:**
- **Line:** 67
- **Issue:** Inconsistent pronoun usage - mixing "I" with "we"
- **Current:** "I believe this approach works, and we've seen great results"
- **Correction:** "We believe this approach works, and we've seen great results"
- **Rule:** Section 1.3 - Person Usage (use "we" for company/organizational perspective)
---
**Summary:**
- Total violations: 2
- Severity: Medium (affects brand voice consistency)
Confidence Scoring
Assign a confidence level to each violation:
- High: The style guide explicitly states this rule and the article clearly violates it
- Medium: The rule exists but requires interpretation; the violation is probable
- Low: Edge case or context-dependent; flag for human review
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.
- 8d ago First seen · 98 lines · 15 tokens per session scan A 2f50a569d417
voice-tone-agent is an agent published in the GitHub repository animalzinc/claude-plugins (15 stars, last pushed 19d ago), licensed MIT. It adds 15 tokens to every session and 760 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.
Other agents, from other repositories
fact-checker
Verifies all claims, statistics, citations, and factual assertions for accuracy before content moves to drafting.
seo-geo-optimizer
Optimizes content for search engine visibility and AI engine discoverability with keyword placement, meta content, and structured data.
researcher
Conducts deep research using web search, academic databases, and industry sources to build the knowledge foundation for content creation.
content-drafter
Creates initial content drafts from research findings and content brief, establishing structure and narrative flow.
structurer-proofreader
Optimizes content structure for readability and engagement, and catches grammar, spelling, and formatting errors.
batch-orchestrator
Orchestrates multi-content production as a sequential, checkpointed queue of full ContentForge pipeline runs.