Borrowing it
Nothing to install: this file belongs to ThreeFish-AI/negentropy. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/ThreeFish-AI/negentropy/master/.agent/skills/heartfelt/SKILL.mdgit clone --depth 1 https://github.com/ThreeFish-AI/negentropyWrote 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/threefish-ai/negentropy/heartfelt)<a href="https://agentmods.dev/skills/threefish-ai/negentropy/heartfelt"><img src="https://agentmods.dev/badge/skills/threefish-ai/negentropy/heartfelt/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/threefish-ai/negentropy/heartfelt"><img src="https://agentmods.dev/badge/skills/threefish-ai/negentropy/heartfelt.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 | $0.00038 | $0.00649 |
| Opus 5 | $0.00019 | $0.00324 |
| Sonnet 5 | $0.00008 | $0.00130 |
| Haiku 4.5 | $0.00004 | $0.00065 |
Grade A, and why
heartfelt scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
愫读
分章节仔细阅读并深入理解每个章节的内容，以概括的方式提取每个章节的关键内容（可分主次要的内容），将每个章节概要依次输出到「愫读 - #$ARGUMENTS.md」，最终完成整篇文档内容的摘要。 分章节仔细阅读并深入理解每个章节的内容，仔细揣摩对每个章节关键内容的理解，并将之依次输出到「愫读 - #$ARGUMENTS.md」文档适当的位置，最终完成整篇文档关键内容的理解记录。 通过对全文关键内容的理解，仔细思考读后的感悟与所得，并将之输出到「愫读 - #$ARGUMENTS.md」文档适当位置。 仔细揣摩每个章节，不要丢失了任何章节的关键内容。
Instructions
- Read the target files using Read tool
- Search for patterns using Grep
- Find related files using Glob
- Provide detailed feedback on code quality
Review checklist
- Code organization and structure
- Error handling
- Performance considerations
- Security concerns
- Test coverage
特别注意：
- 按段落适当分批迭代式进行阅读、摘要、理解、感悟等任务，不要一次处理太多内容，确保对每一段内容细节的理解与处理的准确性和完整性；
- 保持目标「愫读 Markdown 文档」与「原全文 Markdown 文档」中关键内容的一致性；
- 必要时在「愫读 Markdown 文档」中择取全文文档原有的「图」、「表」、「公式」等特殊内容；
- 注意最后需回头对照「原全文 Markdown 文档」，检查「愫读 Markdown 文档」全文关键内容的完整性，保障输出内容的完整性与一致性；
- 注意检查「图」、「表」、「公式」等特殊内容显示的正确性。
- 图片理解：借助 MCP 工具理解图片内容；
「图」资源特别注意：
- 从原 Markdown 文档感知「图」资源的所在路径，并在需要在目标 Markdown 文档引用时直接使用该路径；
「表」资源特别注意：
- 使用 Markdown 语法重现 PDF 中的表内容；
「公式」资源特别注意：
- 使用 LateX 语法重现 PDF 中的数学公式内容；
路径特别注意：
- #$ARGUMENTS 中的「/」是目录层级分割符号，不是文件名称的一部分；
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 · 55 lines · 38 tokens per session scan A 50991ad975ac
heartfelt is a skill published in the GitHub repository ThreeFish-AI/negentropy (10 stars, last pushed today), licensed Apache-2.0. It adds 38 tokens to every session and 649 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.
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