Execute
alirezarezvani/claude-skills
/cs:execute <decision — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision.
Execute a work unit end-to-end: sequence tasks by dependency, implement, test between tasks, commit, and track progress.
$ npx skills add hashgraph-online/awesome-codex-plugins --skill run-work -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins run-work --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/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/AgiFlow/ai-plugin/skills/run-work .claude/skills/run-work && 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 "run-work" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AgiFlow/ai-plugin/skills/run-work into .claude/skills/run-work/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-work", 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/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AgiFlow/ai-plugin/skills/run-workType 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 hashgraph-online/awesome-codex-plugins --skill run-work -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins run-work --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .agents/skills && cp -r skills-src/plugins/AgiFlow/ai-plugin/skills/run-work .agents/skills/run-work && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "run-work" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AgiFlow/ai-plugin/skills/run-work into .agents/skills/run-work/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-work", 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 hashgraph-online/awesome-codex-plugins --skill run-work -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins run-work --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/plugins/AgiFlow/ai-plugin/skills/run-work .cursor/skills/run-work && 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 "run-work" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AgiFlow/ai-plugin/skills/run-work into .cursor/skills/run-work/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-work", 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/hashgraph-online/awesome-codex-plugins.git --path plugins/AgiFlow/ai-plugin/skills/run-work--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 hashgraph-online/awesome-codex-plugins --skill run-work -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins run-work --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/plugins/AgiFlow/ai-plugin/skills/run-work .gemini/skills/run-work && 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 "run-work" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AgiFlow/ai-plugin/skills/run-work into .gemini/skills/run-work/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-work", 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 hashgraph-online/awesome-codex-plugins run-workInstalls 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 hashgraph-online/awesome-codex-plugins --skill run-work -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .github/skills && cp -r skills-src/plugins/AgiFlow/ai-plugin/skills/run-work .github/skills/run-work && 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 "run-work" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AgiFlow/ai-plugin/skills/run-work into .github/skills/run-work/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-work", 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 hashgraph-online/awesome-codex-plugins --skill run-work -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install hashgraph-online/awesome-codex-plugins run-work --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/hashgraph-online/awesome-codex-plugins.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/plugins/AgiFlow/ai-plugin/skills/run-work .opencode/skills/run-work && 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 "run-work" agent skill from https://github.com/hashgraph-online/awesome-codex-plugins/tree/main/plugins/AgiFlow/ai-plugin/skills/run-work into .opencode/skills/run-work/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "run-work", 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.
run-workExecute a work unit end-to-end: sequence tasks by dependency, implement, test between tasks, commit, and track progress.
Run Work is an agent skill from hashgraph-online/awesome-codex-plugins. Execute a work unit end-to-end: sequence tasks by dependency, implement, test between tasks, commit, and track progress. Use to deliver a complete feature in one session. Invoked as /agiflow:run-work <work-unit. Uses getworkunit, listtasks, updatetask, getworkunitprogress.
Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: A curated list of awesome OpenAI Codex / ChatGPT plugins, skills, and resources. The 1 Codex Marketplace. See live plugins at: https://hol.org/plugins/best-codex-plugins. The licence is Apache-2.0.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 78497e5. It shows what the files ask for, not the result of running them.
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.
No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Run Work loads about 2.6k tokens when it runs. Until then it costs about 73 tokens; SKILL.md has 1,264 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.
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.
The full file from hashgraph-online/awesome-codex-plugins at commit 78497e5, republished under its Apache-2.0 licence (© hashgraph-online). 1,264 words, ~2,613 tokens.
.claude/skills/run-work/SKILL.md (or your agent's skills folder).Invoked as
/agiflow:run-work. In hosts without slash-prompts, this skill is triggered by matching intent and drives AgiFlow via its MCP tools.
Usage:
/agiflow:run-work <work-unit-slug-or-id> - Execute specific work unit/agiflow:run-work - List and select from available work unitsExamples:
/agiflow:run-work DXX-WU-1 (using slug)/agiflow:run-work 01K8FABMNEJG1XTA9JGHSNFV40 (using ID)/agiflow:run-work (interactive selection)Guardrails
If a work unit slug/id is provided, load it with get_work_unit; otherwise list available work units with list_work_units for selection.
Follow the shared AgiFlow project-management guidelines in references/agiflow-agents.md — agent assignment, the task status workflow and transitions, work-unit best practices, and the tags strategy apply to this workflow.
Task Status Workflow (per task)
Each task moves individually through: Todo → In Progress → Testing → Review
The work unit stays in_progress until all tasks reach Review or Done.
If any task hits Blocked, consider setting the work unit to blocked too.
IMPORTANT: Planning Status Guard
This skill ONLY executes tasks in "Todo" or later status. Tasks in "Planning" have NOT been groomed and are NOT ready for execution. Use backlog-grooming to promote Planning tasks to Todo first.
Steps Track these steps as TODOs and complete them one by one.
If work unit slug/id NOT provided:
list_work_units MCP tool to show available work units:status: "in_progress" for active work, or work units with tasks in "Todo"If work unit slug/id IS provided: 4. Use get_work_unit MCP tool with the provided slug/id to retrieve:
get_work_unit returns tasks automatically - no separate list_tasks call needed5b. PLANNING STATUS GUARD (MANDATORY):
update_work_unit MCP tool to set status to "in_progress"backlog-groomingupdate_work_unit devInfo:devInfo: {
executionPlan: "Backend API → Frontend UI → Tests → Documentation",
sessionId: "<current-session-id>",
startedAt: "<timestamp>"
}For each task in the work unit (in dependency order from the tasks array):
update_task MCP tool to set status to "In Progress"architect MCP get_file_design_pattern (MANDATORY)architect MCP review_code_change (MANDATORY)devInfo with implementation notes:devInfo: {
filesChanged: ["path/to/file.ts:42"],
testResults: { passed: true, coverage: "85%" },
notes: "Implementation notes here"
}update_taskTesting phase for each task:
Use update_task to move status to "Testing"
Run unit tests, integration tests, type check and lint for affected code
If tests PASS: proceed to move task to "Review"
If tests FAIL:
retryCount in devInforetryCount >= maxRetries (default: 2): move task to "Blocked", set work unit to "blocked", stopretryCount < maxRetries: move task back to "Todo", document failure, continue to next task or stop sessionUse update_task to set status to "Review" when tests pass
Update your TODO list (mark task as completed)
Between tasks:
The work unit tasks array automatically updates as tasks are completed.
get_work_unit to check current state and task statusesin_progress until all tasks reach Review or DoneUpdate work unit devInfo as you progress via update_work_unit:
devInfo: {
executionPlan: "...",
sessionId: "<session-id>",
startedAt: "<timestamp>",
progress: {
completedTasks: 3,
totalTasks: 8,
lastTaskCompleted: "Implement cart API",
currentTask: "Add cart UI component"
},
testResults: {
unitTests: "passing",
integrationTests: "passing",
coverage: "85%"
},
blockers: [] // or list any blockers encountered
}When ALL tasks in work unit are in "Review" or "Done":
Draft a PR description for the work unit (DO NOT create the PR yet - just draft the text):
[WORK-UNIT-SLUG] Work unit title (e.g., [DXX-WU-1] Shopping cart feature)file.ts:42 format)Use update_work_unit to set status to "completed" and save draft PR text and commit message:
{
status: "completed",
completedAt: new Date(),
devInfo: {
...existing,
draftCommitMessage: "feat(cart): implement shopping cart feature\n\n- Add cart API endpoints\n- Add cart UI components\n- Add integration tests\n\nCloses: DXX-WU-1",
draftPr: {
title: "[DXX-WU-1] Shopping cart feature",
body: "## Summary\n\nImplemented shopping cart feature.\n\n## Tasks Completed\n\n- [DXX-1] Add cart API\n- [DXX-2] Add cart UI\n- [DXX-3] Add cart tests\n\n## Changes\n\n- Added cart endpoints\n- Added cart components\n- Added integration tests\n\n## Files Modified\n\n- src/api/cart.ts:42\n- src/components/Cart.tsx:15\n- tests/cart.test.ts:1\n\n## Test Results\n\nAll tests passing. Coverage: 85%"
},
finalNotes: "All tasks completed. Files changed: [...]. Tests passing.",
completedBy: "<member-id>",
totalDuration: "3.5 hours"
}
}Note on draftCommitMessage: Write a conventional commit message that will be used for the final git commit. Format: type(scope): description with optional body listing changes.
Create final summary comment documenting:
file.ts:42 format)If blocked on a task:
update_task to set task status to "Blocked"update_work_unit to set status to "blocked"create_task_comment on blocked task with details explaining what human intervention is neededIf scope changes during execution:
create_task to add new tasks to work unitCommon Mistakes to Avoid
backlog-grooming first)© hashgraph-online, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in plugins/AgiFlow/ai-plugin/skills/run-work of hashgraph-online/awesome-codex-plugins.
Open the folder on GitHubat commit 78497e5
Run Work 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 |
|---|---|---|---|---|---|---|
| Run Work this skillhashgraph-online/awesome-codex-plugins | 1.2k | — | ~2.6k | Automated safety check: Pass | Apache-2.0 | |
| Executealirezarezvani/claude-skills | 28k | — | ~831 | Automated safety check: Pass | MIT | |
| Dependency Scanningsickn33/agentic-awesome-skills | 47k | 1 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Dependency Checkruvnet/ruflo | 74k | — | ~258 | Automated safety check: Pass | MIT | |
| Debugging Executionsn8n-io/n8n | 207k | — | ~2.6k | Automated safety check: Pass | Custom licence | |
| Unit Teststhedaviddias/Front-End-Checklist | 74k | — | ~382 | Automated safety check: Pass | MIT |
alirezarezvani/claude-skills
/cs:execute <decision — Generate a 90-day execution plan with weekly milestones, DRIs, and check-in cadence from an approved decision.
sickn33/agentic-awesome-skills
Scan package dependencies for known vulnerabilities using Snyk, Dependabot, and OWASP Dependency-Check.
ruvnet/ruflo
Scan project dependencies for known vulnerabilities and CVEs.
n8n-io/n8n
Debug failed or wrong-output workflow executions using executions tools.
thedaviddias/Front-End-Checklist
A skill your agent uses when reviewing CI coverage, automated checks, or test strategy related to Write unit tests.
cursor/plugins
Apply to multi-step work (sweeps, migrations, runs of similar edits) and to how you stack commits and PRs.
hashgraph-online/awesome-codex-plugins
Create original anime-style reaction stickers as looping GIFs and MP4 previews, using generated character pose sheets and timed key poses.
hashgraph-online/awesome-codex-plugins
Manage and query Calibre libraries with the calibredb CLI (local paths or Calibre Content server URLs).
hashgraph-online/awesome-codex-plugins
A skill your agent uses when adding, changing, testing, or debugging Rust HTTP APIs and services, especially when Codex needs black-box integration tests, random-port app startup, real database test…
hashgraph-online/awesome-codex-plugins
Make a studio's game look like something at build time — a cover from a real frame of the game (free), painted covers, backdrops, textures and character plates from image models through the…
hashgraph-online/awesome-codex-plugins
Balance game difficulty, resources, rewards, probability, progression, economies, and dominant strategies.
hashgraph-online/awesome-codex-plugins
Analyze nonfiction manuscripts for reader engagement signals, including heading-level word counts, slow starts, long slogs, weak takeaway titles, value pacing, beta-reader comment dropoff, and…
Execute a work unit end-to-end: sequence tasks by dependency, implement, test between tasks, commit, and track progress. Run Work is an agent skill from hashgraph-online/awesome-codex-plugins. Execute a work unit end-to-end: sequence tasks by dependency, implement, test between tasks, commit, and track progress.
Run Work fits situations like: deliver a complete feature in one session.
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill run-work -a claude-code`. Or copy the skill folder (plugins/AgiFlow/ai-plugin/skills/run-work in hashgraph-online/awesome-codex-plugins) into .claude/skills/run-work in your project. Claude Code loads it when a task matches its description.
Run `npx skills add hashgraph-online/awesome-codex-plugins --skill run-work -a codex`. Or copy the skill folder (plugins/AgiFlow/ai-plugin/skills/run-work in hashgraph-online/awesome-codex-plugins) into .agents/skills/run-work in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add hashgraph-online/awesome-codex-plugins --skill run-work -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/run-work, .gemini/skills/run-work, .github/skills/run-work and .opencode/skills/run-work in your project.
SKILL.md names no scripts, command-line tools or credentials: Run Work is instructions for the agent only.
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.
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.
Run Work is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Run Work: Execute (alirezarezvani/claude-skills, 28k stars), Dependency Scanning (sickn33/agentic-awesome-skills, 47k stars), Dependency Check (ruvnet/ruflo, 74k stars) and Debugging Executions (n8n-io/n8n, 207k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
hashgraph-online (a GitHub organization) maintains it in hashgraph-online/awesome-codex-plugins, which has 1,242 GitHub stars. The repository holds 686 skills in this directory. The repository was last updated on October 8, 2026.
Source: hashgraph-online/awesome-codex-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.