Chalk Labs
Need help deploying reasoning?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/sswym-reasoning
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/reasoning
What's inside
- Skill name
reasoning- Description
- 控制 oma 推理努力水平以平衡深度、严谨性、延迟和令牌成本。
- License
- MIT
- Instructions
- 39 lines in SKILL.md · view on GitHub
Files (1)
- SKILL.md
SKILL.md (first lines)
## 目的 使用此技能在规划、执行或重度验证轮次之前设置显式推理姿态。 ## 触发条件 - 用户要求更快或更深的推理 - 会话需要更严格的质量门控或更低的延迟 - 团队希望在各个阶段有可预测的规划/验证努力 ## 支持的努力水平 - `low` - `medium` - `high` - `xhigh` ## 工作流程 1. 识别请求的努力或推断 `medium` 作为默认值。 2. 解释对规划深度、验证严格性和成本/延迟的影响。 3. 当文件系统工具可用时,持久化/更新 `.oma/state/reasoning.json`。 4. 根据姿态推荐下一个命令(`/oma:mode`、`/oma:team` 或 `/oma:loop`)。 ## 输出模板 ```markdown ## 推理 - 请求: - 已应用: ## 配置文件 | 维度 | 值 | | --- | --- | ## 下一个命令 - ... ```
From sswym/oh-my-agent, MIT.
More from sswym/oh-my-agent
- 0.509score
team
sswym
在子智能体之间协调完整的 oma 阶段管道,用于复杂交付(plan -> prd -> exec -> verify -> fix)。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
memory
sswym
使用 MEMORY.md 索引、主题文件和模块化规则包管理持久化项目内存。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
mode
sswym
检查或切换 oma 操作模式/配置文件以调整速度、深度、自主性或严格质量门控。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
approval
sswym
设置 oma 批准姿态(`suggest`、`auto`、`full-auto`)并带有明确的风险护栏。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
prd
sswym
将请求转换为 PRD 级别的范围、可衡量的验收标准和交付约束。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
hud
sswym
控制 oma 可视化 HUD 配置文件,并在正常、紧凑或隐藏模式下保持状态输出可读。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
ralplan
sswym
创建严格的、质量优先的执行计划,具有明确的门控和可回滚的排序。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
rules
sswym
根据任务信号注入条件性规则包(测试、迁移、安全、文档、性能)。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
team-assemble
sswym
动态组装适合任务的智能体团队,请求批准,然后执行分阶段生命周期。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
doctor
sswym
运行 oma 就绪性诊断,检查命令、技能、状态文件和团队/钩子安全姿态。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
deep-init
sswym
使用深度仓库映射、验证钩子和风险热点初始化长时间会话上下文。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
hooks
sswym
操作 oma 的扩展原生钩子管道,具有确定性触发器、安全门控和效率预算。
SkillDFreshness: D★ 75Claude Code +9
Signals
- Stars
- 75
- Forks
- 13
- Open issues
- 1
- Last commit (this folder)
- Apr 12, 2026 (6 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/sswym/oh-my-agent
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from sswym
- 0.509score
team
sswym
在子智能体之间协调完整的 oma 阶段管道,用于复杂交付(plan -> prd -> exec -> verify -> fix)。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
hud
sswym
控制 oma 可视化 HUD 配置文件,并在正常、紧凑或隐藏模式下保持状态输出可读。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
deep-init
sswym
使用深度仓库映射、验证钩子和风险热点初始化长时间会话上下文。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
team-assemble
sswym
动态组装适合任务的智能体团队,请求批准,然后执行分阶段生命周期。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
approval
sswym
设置 oma 批准姿态(`suggest`、`auto`、`full-auto`)并带有明确的风险护栏。
SkillDFreshness: D★ 75Claude Code +9 - 0.506score
doctor
sswym
运行 oma 就绪性诊断,检查命令、技能、状态文件和团队/钩子安全姿态。
SkillDFreshness: D★ 75Claude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get reasoning running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
reasoning skill. Agent Mart. https://agentmart.dev/skills/sswym-reasoning (last updated 2026-10-24)