Show Me Your Work Decision Log
cursor/plugins
Keeps a TSV decision log for long or unattended agent runs, one row per decision with what, why, evidence and result, so a reviewer can check the work later.
A skill your agent uses when you need evidence-bounded loop state, plan/action/observation cycles, stop conditions, budgets, repetition, and trace evidence; triggers include Agent 循环 and Agent loop.
Install Agent Loop Testing
$ npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-loop-testing --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ai-llm/agent-loop-testing .claude/skills/agent-loop-testing && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "agent-loop-testing" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-llm/agent-loop-testing into .claude/skills/agent-loop-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-loop-testing", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-llm/agent-loop-testingType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-loop-testing --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ai-llm/agent-loop-testing .agents/skills/agent-loop-testing && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "agent-loop-testing" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-llm/agent-loop-testing into .agents/skills/agent-loop-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-loop-testing", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-loop-testing --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ai-llm/agent-loop-testing .cursor/skills/agent-loop-testing && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "agent-loop-testing" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-llm/agent-loop-testing into .cursor/skills/agent-loop-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-loop-testing", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/majiayu000/claude-skill-registry.git --path skills/ai-llm/agent-loop-testing--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-loop-testing --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ai-llm/agent-loop-testing .gemini/skills/agent-loop-testing && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "agent-loop-testing" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-llm/agent-loop-testing into .gemini/skills/agent-loop-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-loop-testing", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install majiayu000/claude-skill-registry agent-loop-testingInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ai-llm/agent-loop-testing .github/skills/agent-loop-testing && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "agent-loop-testing" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-llm/agent-loop-testing into .github/skills/agent-loop-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-loop-testing", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install majiayu000/claude-skill-registry agent-loop-testing --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/majiayu000/claude-skill-registry.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ai-llm/agent-loop-testing .opencode/skills/agent-loop-testing && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "agent-loop-testing" agent skill from https://github.com/majiayu000/claude-skill-registry/tree/main/skills/ai-llm/agent-loop-testing into .opencode/skills/agent-loop-testing/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agent-loop-testing", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
agent-loop-testing- GitHub stars
- 666
- Used in
- 1 other repo
- Token cost
- ~436 tokens
- SKILL.md length
- 86 words
- Files
- 2
- Skills in repo
- 1,273
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when you need evidence-bounded loop state, plan/action/observation cycles, stop conditions, budgets, repetition, and trace evidence; triggers include Agent 循环 and Agent loop.
- Works in 5 steps: 先阅读并遵循… → 提取范围、环境、版本、时间窗口、约束、成功标准和可用证据，重点检查循环状态、规划动… → 先区分已确认事实、证据支持的推断、候选建议和 Human… → …
- You need evidence-bounded loop state
- SKILL.md covers 何时使用, 输出格式选项, 如何使用 and 参考文件, plus 4 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Agent Loop Testing is an agent skill from majiayu000/claude-skill-registry. Use this skill when you need evidence-bounded loop state, plan/action/observation cycles, stop conditions, budgets, repetition, and trace evidence; triggers include Agent 循环 and Agent loop.
Its SKILL.md is about 440 tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file (for example `metadata.json`).
It sits in Agent Workflows, covering Autonomous loops. The repository describes itself as: Searchable Claude Code skills catalog with source-linked guides and generated registry artifacts. The licence is MIT.
When your agent uses it
- You need evidence-bounded loop state
- Plan/action/observation cycles
- Stop conditions
- Triggers include Agent 循环 and Agent loop
Example prompts
- “/agent-loop-testing”
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- 先阅读并遵循 prompts/agent-loop-testing.md，包括输入审计、领域覆盖和输出顺序。
- 提取范围、环境、版本、时间窗口、约束、成功标准和可用证据，重点检查循环状态、规划动作观察、停止条件、预算、重复行为。
- 先区分已确认事实、证据支持的推断、候选建议和 Human 决策，再按风险与证据强度排序。
- 把高风险项转成前置条件、步骤、预期结果或判断标准、所需证据和验证方法。
- 信息不足时交付受限初版，明确哪些结论不能成立，不把静态材料写成执行结果。
What it can do on your machine
Read from SKILL.md and the folder at commit 2d14a69. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Agent Loop Testing loads about 436 tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 86 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from majiayu000/claude-skill-registry at commit 2d14a69, republished under its MIT licence (© majiayu000). 86 words, ~436 tokens.
Download SKILL.mdSave it as
.claude/skills/agent-loop-testing/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.- name
- agent-loop-testing
- description
- Use this skill when you need evidence-bounded loop state, plan/action/observation cycles, stop conditions, budgets, repetition, and trace evidence; triggers include Agent 循环 and Agent loop.
Agent 循环测试（中文版）
何时使用
- 需要围绕循环状态、规划/动作/观察周期、停止条件、预算、重复行为与 trace 证据开展有证据的分析、设计或验证准备。
- 需要评审 Agent、RAG 或 LLM 方案、结果或证据，并形成可执行改进项。
- 输入不完整，但仍需交付带假设、信息缺口和人工决策边界的受限初版。
输出格式选项
- 默认输出 Markdown，按领域风险、证据状态、优先级和边界组织。
- 用户要求表格、CSV、JSON 或工单格式时，保留相同的发现字段、证据和决策边界。
- 输出进入自动化流程前，先确认 schema、枚举值、必填项和证据来源。
如何使用
- 先阅读并遵循
prompts/agent-loop-testing.md，包括输入审计、领域覆盖和输出顺序。 - 提取范围、环境、版本、时间窗口、约束、成功标准和可用证据，重点检查循环状态、规划动作观察、停止条件、预算、重复行为。
- 先区分已确认事实、证据支持的推断、候选建议和 Human 决策，再按风险与证据强度排序。
- 把高风险项转成前置条件、步骤、预期结果或判断标准、所需证据和验证方法。
- 信息不足时交付受限初版，明确哪些结论不能成立，不把静态材料写成执行结果。
参考文件
- 每次执行必须读取
prompts/agent-loop-testing.md；它是本 Skill 的完整执行规范。 - 需要评测时读取
evals/eval.yaml和evals/cases/下的匹配用例。 - 只有目录实际存在且任务需要时，才读取
references/、examples/、scripts/或output-formats.md，不要假设不存在的资产。
核心约束
- 只分析循环状态、规划/动作/观察周期、停止条件、预算、重复行为与 trace 证据，不替代业务负责人或 Human 的风险接受、例外批准和安全决定。
- 不编造系统行为、字段、模型输出、数据、阈值、根因、执行记录或通过结论。
- 静态设计、计划、文件存在或 dry-run 只能保留原证据状态，不能升级为真实执行证明。
- 证据不足时使用待确认、blocked、unassessed 或 NOT_SCORED，并给出最小验证方法。
- 涉及用户数据、生产或安全时采用最小权限、脱敏数据、mock、dry-run 或隔离环境。
交付前自检
- 已覆盖循环状态、规划动作观察、停止条件、预算、重复行为，并为每项记录来源、证据状态和验证方法。
- 已分开事实、推断、候选建议、信息缺口和 Human 决策。
- 高风险项有 P0/P1/P2/P3 或等价优先级、责任角色和关闭条件。
- 未把计划、静态检查或 dry-run 写成测试执行、全部通过或安全批准。
- 已说明剩余风险、停止/升级条件和下一步。
常见误区
- 只列检查点，不说明触发条件、预期关注点、责任角色、关闭条件和证据。
- 把相邻领域的测试或模型工具名当成Agent 循环的完整判断。
- 用未经说明的数字制造伪精确，或把相关性写成因果关系。
- 输入不完整时直接拒绝，或反过来假装结论已经确定。
最佳实践
- 从最可能造成用户伤害、业务损失或决策阻塞的路径开始。
- 使用最小可验证实验缩小不确定性，并记录条件、版本、来源和证据。
- 让另一位工程师能够独立安装、执行和复核本 Skill 的产出。
© majiayu000, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 1 other file in skills/ai-llm/agent-loop-testing of majiayu000/claude-skill-registry.
- SKILL.md
- metadata.json
Open the folder on GitHubat commit 2d14a69
Used in 1 other repository
We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in majiayu000/claude-skill-registry, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Agent Loop Testing next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Agent Loop Testing this skillmajiayu000/claude-skill-registry | 666 | 1 repos | ~436 | Automated safety check: Pass | MIT | |
| Show Me Your Work Decision Logcursor/plugins | 10k | 9 repos | ~1.6k | Automated safety check: Pass | None | |
| Autoresearch Iteration Loopuditgoenka/autoresearch | 6.5k | 1 repos | ~2k | Automated safety check: Pass | MIT | |
| PUA Looptanweai/pua | 20k | 1 repos | ~1.1k | Automated safety check: Pass | MIT | |
| AutopilotYeachan-Heo/oh-my-claudecode | 40k | 1 repos | ~4.4k | Automated safety check: Pass | MIT | |
| Install Loop Engineeringcobusgreyling/loop-engineering | 11k | 1 repos | ~648 | Automated safety check: Pass | MIT |
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uditgoenka/autoresearch
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PUA Loop
tanweai/pua
Runs an unattended iterate-until-verified loop in which a user-set verify command, not the agent's own claim, decides when the task is finished.
Autopilot
Yeachan-Heo/oh-my-claudecode
Takes a short product idea through requirements, design, planning, parallel implementation, QA cycles and multi-reviewer validation to produce working code.
Install Loop Engineering
cobusgreyling/loop-engineering
Installs Loop Engineering into a project through the single @cobusgreyling/loop CLI, scaffolding a report-only loop and a readiness score.
Loopy
Forward-Future/loopy
Discover, find, compare, audit, repair, adapt, craft, run, debrief, save, and prepare repeatable AI-agent loops for publication.
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Related
Categories
Questions about Agent Loop Testing
What does Agent Loop Testing do?
A skill your agent uses when you need evidence-bounded loop state, plan/action/observation cycles, stop conditions, budgets, repetition, and trace evidence; triggers include Agent 循环 and Agent loop. Agent Loop Testing is an agent skill from majiayu000/claude-skill-registry. Use this skill when you need evidence-bounded loop state, plan/action/observation cycles, stop conditions, budgets, repetition, and trace evidence; triggers include Agent 循环 and Agent loop.
When should I use Agent Loop Testing?
Agent Loop Testing fits situations like: you need evidence-bounded loop state; plan/action/observation cycles; stop conditions; triggers include Agent 循环 and Agent loop.
How do I install Agent Loop Testing in Claude Code?
Run `npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a claude-code`. Or copy the skill folder (skills/ai-llm/agent-loop-testing in majiayu000/claude-skill-registry) into .claude/skills/agent-loop-testing in your project. Claude Code loads it when a task matches its description.
How do I install Agent Loop Testing in Codex?
Run `npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a codex`. Or copy the skill folder (skills/ai-llm/agent-loop-testing in majiayu000/claude-skill-registry) into .agents/skills/agent-loop-testing in your project. Codex loads it when a task matches its description.
Can I use Agent Loop Testing in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add majiayu000/claude-skill-registry --skill agent-loop-testing -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agent-loop-testing, .gemini/skills/agent-loop-testing, .github/skills/agent-loop-testing and .opencode/skills/agent-loop-testing in your project.
What does Agent Loop Testing need to run?
SKILL.md names no scripts, command-line tools or credentials: Agent Loop Testing is instructions for the agent only.
Does Agent Loop Testing access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Agent Loop Testing safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Agent Loop Testing use?
Agent Loop Testing is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Agent Loop Testing use?
About 436 tokens (SKILL.md is roughly 1.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Agent Loop Testing?
Skills that share tags, products or a category with Agent Loop Testing: Show Me Your Work Decision Log (cursor/plugins, 10k stars), Autoresearch Iteration Loop (uditgoenka/autoresearch, 6.5k stars), PUA Loop (tanweai/pua, 20k stars) and Autopilot (Yeachan-Heo/oh-my-claudecode, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Agent Loop Testing?
majiayu000 (a GitHub user) maintains it in majiayu000/claude-skill-registry, which has 666 GitHub stars. The repository holds 1,273 skills in this directory. The repository was last updated on October 7, 2026.
Source: majiayu000/claude-skill-registry on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.