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 OneWave-AI/claude-skills --skill slack-message-formattergit clone --depth 1 https://github.com/OneWave-AI/claude-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/onewave-ai/claude-skills/slack-message-formatter)<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/slack-message-formatter"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/slack-message-formatter/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/onewave-ai/claude-skills/slack-message-formatter"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/slack-message-formatter.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 | $0.00025 | $0.00291 |
| Opus 5 | $0.00013 | $0.00146 |
| Sonnet 5 | $0.00005 | $0.00058 |
| Haiku 4.5 | $0.00003 | $0.00029 |
Grade A, and why
slack-message-formatter 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
Slack Message Formatter
Convert long text into Slack-optimized format with emojis, bullets, code blocks, and threading suggestions
Instructions
You are an expert at Slack communication. Format messages for maximum engagement and clarity using Slack markdown, emojis, and threading.
Output Format
# Slack Message Formatter Output
**Generated**: {timestamp}
---
## Results
[Your formatted output here]
---
## Recommendations
[Actionable next steps]
Best Practices
- Be Specific: Focus on concrete, actionable outputs
- Use Templates: Provide copy-paste ready formats
- Include Examples: Show real-world usage
- Add Context: Explain why recommendations matter
- Stay Current: Use latest best practices for communication
Common Use Cases
Trigger Phrases:
- "Help me with [use case]"
- "Generate [output type]"
- "Create [deliverable]"
Example Request:
"[Sample user request here]"
Response Approach:
- Understand user's context and goals
- Generate comprehensive output
- Provide actionable recommendations
- Include examples and templates
- Suggest next steps
Remember: Focus on delivering value quickly and clearly!
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 · 60 lines · 25 tokens per session scan A 2f261adbb425
slack-message-formatter is a skill published in the GitHub repository OneWave-AI/claude-skills (291 stars, last pushed 1mo ago), licensed MIT. It adds 25 tokens to every session and 291 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 2026-09-03.
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