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 agentmods add skills/rysh-ai/rysh-cli-code/softdev-loopnpx skills add rysh-ai/rysh-cli-code --skill softdev-loopgit clone --depth 1 https://github.com/rysh-ai/rysh-cli-codeWhat 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 | $0.00015 | $0.00406 |
| Opus 5 | $0.00008 | $0.00203 |
| Sonnet 5 | $0.00003 | $0.00081 |
| Haiku 4.5 | $0.00002 | $0.00041 |
Grade A, and why
softdev-loop 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 yesterday.
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
You run one pass of a Go software-development loop in {{workdir}}, working toward: {{goal}}
The pass
- Orient. Read the code the goal touches before writing any. Follow the project's existing conventions — file layout, error style, test style.
- Implement the smallest honest slice of the goal.
- Test. Every behaviour you add gets a test that fails without it. Run
go test ./...— the whole module, not just your package. - Vet. Run
go vet ./...and fix what it reports.
Rules
- Never weaken or delete an existing test to get green.
- Never commit or push — the loop produces a working tree; the human reviews and commits.
- If the goal is ambiguous, implement the narrow reading and say in your report which reading you chose and why.
- End every pass by reporting: what changed, what is verified green, and what (if anything) remains for the next pass.
What ships with it
3 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.
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.
- yesterday First seen · 46 lines · 15 tokens per session scan A 18c9f43448f0
softdev-loop is a skill published in the GitHub repository rysh-ai/rysh-cli-code (5 stars, last pushed 15d ago), licensed Apache-2.0. It adds 15 tokens to every session and 406 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 2026-08-31.
Other skills, from other repositories
openmaic-classroom
将 RAG 检索结果、文档块或知识图谱概念转换为 OpenMAIC 互动课程。当用户要求将知识库内容、检索到的文档片段、上传的文档、或知识图谱中的概念批量转换为教学课件/互动课堂时使用此技能。支持纯需求生成、基于 PDF 内容的课程生成、和基于概念图遍历的批量课堂生成。.
文档协作
引导用户通过结构化的文档共同编写工作流程。当用户想撰写文档、提案、技术规范、决策文档或类似结构化内容时使用。该工作流程帮助用户高效传递上下文,通过迭代优化内容,并验证文档对读者有效。当用户提到写文档、创建提案、起草规范或类似文档任务时触发。.
weknora-shared
Use when driving a WeKnora RAG server through the weknora CLI as an agent — authenticating, managing knowledge bases / documents / sessions / agents, running search or chat, or interpreting the CLI's JSON envelopes and exit codes. Read this before any other weknora- skill.
weknora-rag-search
Use when retrieving from or asking questions against a WeKnora knowledge base via the weknora CLI — and especially when unsure whether to use chat, session ask, or search chunks for a given goal.
数据处理器
数据处理与分析技能。当用户需要对知识库检索结果进行数据分析、统计计算、格式转换、数据提取或生成报告时使用此技能。支持 Python 脚本执行进行高级数据处理。.
文档分析器
深度分析文档结构和内容。当用户需要分析文档结构、提取关键信息、识别文档类型、进行内容质量评估、或理解文档组织方式时使用此技能。.