Codex with ChatGPT Planning Loop
XiaoDuoYa/codex-with-chatgpt
Uses ChatGPT in the browser as the planning and review brain for a Codex session, with Codex keeping all execution and ChatGPT reading the workspace through a bridge.
Interactive onboarding for the MCP Task Orchestrator. An agent skill from jpicklyk/task-orchestrator.
$ npx skills add jpicklyk/task-orchestrator --skill quick-start -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jpicklyk/task-orchestrator quick-start --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/jpicklyk/task-orchestrator.git skills-src && mkdir -p .claude/skills && cp -r skills-src/claude-plugins/task-orchestrator/skills/quick-start .claude/skills/quick-start && 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 "quick-start" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/quick-start into .claude/skills/quick-start/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quick-start", 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/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/quick-startType 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 jpicklyk/task-orchestrator --skill quick-start -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jpicklyk/task-orchestrator quick-start --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .agents/skills && cp -r skills-src/claude-plugins/task-orchestrator/skills/quick-start .agents/skills/quick-start && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "quick-start" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/quick-start into .agents/skills/quick-start/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quick-start", 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 jpicklyk/task-orchestrator --skill quick-start -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jpicklyk/task-orchestrator quick-start --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/claude-plugins/task-orchestrator/skills/quick-start .cursor/skills/quick-start && 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 "quick-start" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/quick-start into .cursor/skills/quick-start/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quick-start", 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/jpicklyk/task-orchestrator.git --path claude-plugins/task-orchestrator/skills/quick-start--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 jpicklyk/task-orchestrator --skill quick-start -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jpicklyk/task-orchestrator quick-start --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/claude-plugins/task-orchestrator/skills/quick-start .gemini/skills/quick-start && 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 "quick-start" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/quick-start into .gemini/skills/quick-start/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quick-start", 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 jpicklyk/task-orchestrator quick-startInstalls 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 jpicklyk/task-orchestrator --skill quick-start -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .github/skills && cp -r skills-src/claude-plugins/task-orchestrator/skills/quick-start .github/skills/quick-start && 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 "quick-start" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/quick-start into .github/skills/quick-start/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quick-start", 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 jpicklyk/task-orchestrator --skill quick-start -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install jpicklyk/task-orchestrator quick-start --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/jpicklyk/task-orchestrator.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/claude-plugins/task-orchestrator/skills/quick-start .opencode/skills/quick-start && 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 "quick-start" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/quick-start into .opencode/skills/quick-start/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quick-start", 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.
quick-startInteractive onboarding for the MCP Task Orchestrator. An agent skill from jpicklyk/task-orchestrator.
Quick Start is an agent skill from jpicklyk/task-orchestrator. Interactive onboarding for the MCP Task Orchestrator. Detects empty or populated workspaces and walks through how plan mode, persistent tracking, and the MCP work together. Use when a user says "get started", "how do I use this", "quick start", "first time setup", "onboard me", "what can this MCP do", or "help me learn task orchestrator".
Its SKILL.md is about 4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering Planning and MCP servers. It works with Model Context Protocol. The repository describes itself as: Server-enforced workflow discipline for AI agents. An MCP server providing persistent work items, dependency graphs, quality gates, and actor attribution. Schemas define what… The licence is MIT.
9 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit b688ea0. 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.
Shell commands in SKILL.md call:
nodeFrom 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.
Quick Start loads about 4k tokens when it runs. Until then it costs about 88 tokens; SKILL.md has 1,831 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 jpicklyk/task-orchestrator at commit b688ea0, republished under its MIT licence (© jpicklyk). 1,831 words, ~4,022 tokens.
.claude/skills/quick-start/SKILL.md (or your agent's skills folder).Interactive onboarding that teaches by doing. Detects your workspace state and adapts.
Resolve the scope first. Check session context for the SessionStart hook's output: a ## Project Scope section carries a project rootId (it scopes reads and anchors new items); a ## Personal Scope section carries a personal root (it only anchors new items; reads stay unscoped).
Without session context, ask the config locator, not a cwd-relative file read. Resolve <plugin root> as init Step 0 does, then:
node --input-type=module -e "const m = await import('file:///<plugin root>/hooks/config-locator.mjs'); const l = m.locateConfig(); console.log(JSON.stringify({scope: l.scope, path: l.path, rootId: l.rootId, name: l.name}))"(forward slashes only; the drive-letter form on Windows). Scope project with a rootId is a project rootId; scope user with a rootId is the personal root.
Call the health check to determine which path to follow:
get_context()When a project rootId is known, pass it to scope the check to this project: get_context(ancestorId="<rootId>"). In personal scope, or when no rootId is known (a truly fresh workspace), call unscoped exactly as shown.
If no active or stalled items exist — follow the Fresh-Start Path (Steps 2-8). If active items exist — follow the Orientation Path (Steps A-C).
Before following either path, check whether this workspace has a project anchor yet. Use the scope resolved in Step 1: if either kind of root (project or personal) is known, the workspace is set up and nothing more is needed here.
If no root is known, offer setup via AskUserQuestion: "This workspace isn't set up for Task Orchestrator yet. Run /task-orchestrator:init to create a project anchor (or /task-orchestrator:init --user for a personal root that serves every unconfigured directory)?" /task-orchestrator:init owns the anchor, the config.yaml project: block, the server push and the bundled-rule seeding; this skill does none of that itself. If the user accepts, run it (or tell them to) and then continue here.
If the user declines, proceed unscoped. Nothing else in this skill requires an anchor.
Explain briefly:
Show how plan mode and the MCP work together. This is the workflow users will experience:
You describe what you want
│
▼
EnterPlanMode ← Claude explores the codebase
│
pre-plan hook fires ← Plugin sets the definition floor: existing work, schemas, gate requirements
│
▼
Plan written to disk ← Persistent markdown file — your design document
│
Plan approved (ExitPlanMode)
│
post-plan hook fires ← Plugin tells Claude to materialize before implementing
│
▼
Materialize ← Claude creates MCP items from the plan
│ Items, dependencies, notes — execution tracking
▼
Implement ← Subagents work, each transitioning their MCP item
│ advance_item(start) → work → advance_item(complete)
▼
Health check ← get_context() shows what completed and what didn'tReinforce to the user:
Now let's create some MCP items to see how the execution tracking works.
Determine the project topic:
$ARGUMENTS is provided, use it as the project topicAskUserQuestion with options like "A web app feature", "A bug fix workflow", "A documentation project", or OtherCreate a container with child items and dependencies in one atomic call:
create_work_tree(
root: {
title: "<Project Name> — Tutorial",
summary: "Quick-start tutorial project to learn MCP Task Orchestrator",
type: "container",
priority: "medium"
},
children: [
{ ref: "design", title: "Design <topic>", summary: "Define requirements and approach", type: "feature-task", priority: "high" },
{ ref: "implement", title: "Implement <topic>", summary: "Build the solution", type: "feature-task", priority: "high" },
{ ref: "test", title: "Test <topic>", summary: "Verify the implementation", type: "feature-task", priority: "medium" }
],
deps: [
{ from: "design", to: "implement", type: "BLOCKS" },
{ from: "implement", to: "test", type: "BLOCKS" }
]
)Explain to the user:
create_work_tree creates everything atomically — the container, three child items, and two dependency edgesBLOCKS dependency means: implement cannot start until design completes, test cannot start until implement completesref names ("design", "implement", "test") are local aliases used only within this callShow the structure:
<Project Name> — Tutorial (container)
├── Design <topic> ← actionable (no blockers)
├── Implement <topic> ← blocked by Design
└── Test <topic> ← blocked by ImplementThis is the project board side — these items track progress. The plan file (if this were a real feature) would contain the design decisions behind each of these tasks.
Fill required notes (gate prerequisite): feature-task items require a task-scope note (queue, required) before advance_item(trigger="start") will succeed, and a complete trigger checks ALL required notes across every phase the resolved schema declares — not just the current phase, and not just the base schema's own notes. Traits merge in too: a session-tracked default trait adds a required session-tracking work note, for example, while review-phase notes like review-checklist are typically opt-in per item via a trait (e.g. needs-task-review), not a base requirement. Call get_context(itemId="<design-UUID>") to see the exact resolved note list before filling — schemas vary per project. create_work_tree above created the children with no notes — its createNotes option only auto-fills blank bodies, which don't count as "filled" for gate purposes — so fill every required note the resolved schema lists on the design item now, before Step 5a, so both the start and complete calls succeed. For a feature-task schema with the common task-scope + implementation-notes base plus a session-tracked default trait:
manage_notes(
operation="upsert",
notes=[
{ itemId: "<design-UUID>", key: "task-scope", role: "queue", body: "Define requirements and approach for <topic>." },
{ itemId: "<design-UUID>", key: "implementation-notes", role: "work", body: "Design work completed for <topic>." },
{ itemId: "<design-UUID>", key: "session-tracking", role: "work", body: "Design phase completed this session." }
]
)Explain to the user: in a real workflow, subagents fill these notes as work actually happens, phase by phase. Here we're pre-filling all of them up front purely so the tutorial's Step 5b complete call isn't gate-blocked — note bodies don't need to match the item's current role to be saved, only to satisfy the gate check at advance time. If get_context shows additional required notes (e.g. a review-checklist from an opted-in review trait), fill those too before advancing.
Items move queue → work → review → terminal via advance_item triggers — see the advance_item tool description for full trigger semantics.
5a. Start the design task:
advance_item(transitions=[{ itemId: "<design-UUID>", trigger: "start" }])Point out in the response: cascadeEvents shows the container cascading queue → work (first child started). In a real workflow, each subagent calls this when it begins its assigned item.
5b. Complete the design task:
advance_item(transitions=[{ itemId: "<design-UUID>", trigger: "complete" }])Point out in the response: unblockedItems shows implement is now unblocked; the container stays in work because siblings are still active.
5c. Confirm what's next:
get_next_item(limit=3, includeDetails=true)Point out: the implement task is now recommended — it was unblocked when design completed. This is how the MCP answers "what should I work on next?" across sessions.
This is where the plan file and MCP complement each other most visibly. Explain:
get_context() or /work-summary to see exactly which items are in progress, which are blocked, and which are doneThis is the difference between having a plan document alone vs. having a plan document plus a live project board. The plan doesn't change as work progresses — the MCP does.
Briefly mention that MCP items can have required notes that act as documentation gates:
.taskorchestrator/config.yaml file defines schemas under work_item_schemas: — which notes must be filled before an item can advancetype field (e.g., type: "feature-implementation" activates that schema's notes and gates)feature-implementation schema requires a feature-summary note before work can start, and a review-checklist note before completionguidance field (authoring hints) and a skill field (structured evaluation framework to invoke before filling)traits: "needs-security-review" adds a security-assessment note at the review phase/manage-schemas to set one up interactively — it can also generate a companion lifecycle skill for your schemaPresent this capabilities table:
| Want to... | Skill | What it does |
|---|---|---|
| Track a feature with documentation gates | /manage-schemas | Create schemas with lifecycle gates, then use companion skills |
| Create items from conversation context | /create-item | Infers type, priority, and container placement |
| Build custom workflow schemas | /manage-schemas | Create, view, edit, delete, and validate note schemas |
| See project health dashboard | /work-summary | Active work, blockers, next actions at a glance |
| Advance an item through gates | /status-progression | Shows current role, gate status, correct trigger |
| Change how the server runs (HTTP, REST API, config-sync) | /configure-server | Transport, REST API mode, port publishing, config mount |
Offer cleanup: Ask via AskUserQuestion whether to keep the tutorial items for reference or delete them. If delete, use the container UUID returned in Step 4 above:
manage_items(operation="delete", itemIds=["<container-UUID>"], recursive=true)For users with an existing populated workspace.
Run two calls in parallel:
get_context()
query_items(operation="overview", includeChildren=true)Add ancestorId="<rootId>" to both when a project rootId is known (resolved in Step 1) — this keeps the orientation dashboard scoped to the current project in multi-project workspaces. Call unscoped exactly as shown in personal scope or when no rootId is known.
Present a condensed dashboard with these sections:
get_next_item(limit=3, includeDetails=true) — add ancestorId="<rootId>" when a project rootId is knownUse status symbols: ◉ in-progress, ⊘ blocked, ○ pending, ✓ completed
For each section of the dashboard, add a brief annotation:
work or review role — these are things being worked on right nowget_context(itemId=...) to see which notes are missing, then manage_notes(upsert) to fill themIf blocked items exist, explain: "Run /status-progression on a blocked item to see exactly what's needed to unblock it."
Explain the plan mode connection: These MCP items are the execution tracking side of your work. When Claude enters plan mode, it writes a persistent plan file (your design document). When the plan is approved, the plugin hooks tell Claude to create MCP items like these to track implementation progress. The plan file and MCP items are complementary — the plan captures what and how, the MCP tracks progress and status.
Based on the dashboard, recommend one concrete action:
| Situation | Recommendation |
|---|---|
| Stalled items with missing notes | Fill the required notes — show the exact manage_notes call |
| Blocked items with satisfied deps | Advance with advance_item(trigger="start") |
| No active work, queue items exist | Start the highest-priority queue item |
| Empty workspace | Switch to the Fresh-Start path (Step 2) |
| Everything terminal | Suggest creating new work with /create-item |
End with: "Run /work-summary anytime to see this dashboard. When you're ready to build something, just describe it — Claude will enter plan mode, write a plan file, and create MCP items to track the work automatically."
© jpicklyk, MIT. 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 claude-plugins/task-orchestrator/skills/quick-start of jpicklyk/task-orchestrator.
Open the folder on GitHubat commit b688ea0
Quick Start 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 |
|---|---|---|---|---|---|---|
| Quick Start this skilljpicklyk/task-orchestrator | 207 | — | ~4k | Automated safety check: Pass | MIT | |
| Codex with ChatGPT Planning LoopXiaoDuoYa/codex-with-chatgpt | 7.1k | — | ~11k | Automated safety check: Notes | MIT | |
| Agentic Tool Integrationsamugit83/redamon | 2.9k | — | ~1.3k | Automated safety check: Pass | MIT | |
| Upload Artifactclosedloop-ai/claude-plugins | 122 | — | ~1.4k | Automated safety check: Notes | Apache-2.0 | |
| Spring PlanningAmplicode/spring-skills | 126 | — | ~3.7k | Automated safety check: Pass | None | |
| MCP Server Builderanthropics/skills | 180k | 62 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 |
XiaoDuoYa/codex-with-chatgpt
Uses ChatGPT in the browser as the planning and review brain for a Codex session, with Codex keeping all execution and ChatGPT reading the workspace through a bridge.
samugit83/redamon
Wiring a new tool the AI agent can call (not the recon pipeline): the tool registry, the phase map, the hardcoded dispatch chokepoint, and the duplicated execution paths that make a tool work in…
closedloop-ai/claude-plugins
Upload a file as a ClosedLoop document (PRD, implementation plan, feature, or template).
Amplicode/spring-skills
Create structured implementation plan in docs/plans/. An agent skill from Amplicode/spring-skills.
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
shareAI-lab/learn-claude-code
Walks through building MCP servers in Python or TypeScript that expose tools, resources and prompts to Claude, with templates, registration and testing.
jpicklyk/task-orchestrator
Walks through how to launch and reach the MCP Task Orchestrator server container: transport, REST API, port publishing, config mounts and config-sync.
jpicklyk/task-orchestrator
Resolves ready MCP work items into a run plan, shows it to you, then executes it through the Workflow tool or direct subagent dispatch, with post-run verification.
jpicklyk/task-orchestrator
Migrates an existing unscoped Task Orchestrator database to the project-scoping convention in place, creating one project anchor root and re-parenting work trees under it after a mandatory dry run.
jpicklyk/task-orchestrator
Completes or cancels a whole feature subtree, a named list of items, or a batch of stale work items at once, previewing the impact and warning before force-completing anything active.
jpicklyk/task-orchestrator
Creates an MCP work item from conversation context, anchoring it under the right container, inferring type and priority and pre-filling the required notes.
jpicklyk/task-orchestrator
Views, creates, deletes and diagnoses BLOCKS, IS_BLOCKED_BY and RELATES_TO links between MCP work items, including why an item cannot start.
Works with
Categories
Interactive onboarding for the MCP Task Orchestrator. An agent skill from jpicklyk/task-orchestrator. Quick Start is an agent skill from jpicklyk/task-orchestrator. Interactive onboarding for the MCP Task Orchestrator.
Quick Start fits situations like: A user says get started; how do I use this; first time setup; what can this MCP do.
Run `npx skills add jpicklyk/task-orchestrator --skill quick-start -a claude-code`. Or copy the skill folder (claude-plugins/task-orchestrator/skills/quick-start in jpicklyk/task-orchestrator) into .claude/skills/quick-start in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jpicklyk/task-orchestrator --skill quick-start -a codex`. Or copy the skill folder (claude-plugins/task-orchestrator/skills/quick-start in jpicklyk/task-orchestrator) into .agents/skills/quick-start 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 jpicklyk/task-orchestrator --skill quick-start -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/quick-start, .gemini/skills/quick-start, .github/skills/quick-start and .opencode/skills/quick-start in your project.
Going by SKILL.md and its folder, Quick Start needs the command-line tools its instructions call (node).
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.
Quick Start is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4k tokens (SKILL.md is roughly 16k 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 Quick Start: Codex with ChatGPT Planning Loop (XiaoDuoYa/codex-with-chatgpt, 7.1k stars), Agentic Tool Integration (samugit83/redamon, 2.9k stars), Upload Artifact (closedloop-ai/claude-plugins, 122 stars) and Spring Planning (Amplicode/spring-skills, 126 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
jpicklyk (a GitHub user) maintains it in jpicklyk/task-orchestrator, which has 207 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on October 6, 2026.
Source: jpicklyk/task-orchestrator on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.