MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Internal, hook-triggered: materializes MCP items from the approved plan and dispatches implementation.
$ npx skills add jpicklyk/task-orchestrator --skill post-plan-workflow -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jpicklyk/task-orchestrator post-plan-workflow --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/post-plan-workflow .claude/skills/post-plan-workflow && 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 "post-plan-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/post-plan-workflow into .claude/skills/post-plan-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "post-plan-workflow", 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/post-plan-workflowType 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 post-plan-workflow -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jpicklyk/task-orchestrator post-plan-workflow --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/post-plan-workflow .agents/skills/post-plan-workflow && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "post-plan-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/post-plan-workflow into .agents/skills/post-plan-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "post-plan-workflow", 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 post-plan-workflow -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jpicklyk/task-orchestrator post-plan-workflow --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/post-plan-workflow .cursor/skills/post-plan-workflow && 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 "post-plan-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/post-plan-workflow into .cursor/skills/post-plan-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "post-plan-workflow", 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/post-plan-workflow--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 post-plan-workflow -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jpicklyk/task-orchestrator post-plan-workflow --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/post-plan-workflow .gemini/skills/post-plan-workflow && 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 "post-plan-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/post-plan-workflow into .gemini/skills/post-plan-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "post-plan-workflow", 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 post-plan-workflowInstalls 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 post-plan-workflow -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/post-plan-workflow .github/skills/post-plan-workflow && 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 "post-plan-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/post-plan-workflow into .github/skills/post-plan-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "post-plan-workflow", 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 post-plan-workflow -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 post-plan-workflow --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/post-plan-workflow .opencode/skills/post-plan-workflow && 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 "post-plan-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/post-plan-workflow into .opencode/skills/post-plan-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "post-plan-workflow", 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.
post-plan-workflowInternal, hook-triggered: materializes MCP items from the approved plan and dispatches implementation.
Post Plan Workflow is an agent skill from jpicklyk/task-orchestrator. Internal, hook-triggered: materializes MCP items from the approved plan and dispatches implementation.
Its SKILL.md is about 2k 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 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.
3 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.
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.
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.
Post Plan Workflow loads about 2k tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 1,042 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). 1,042 words, ~1,987 tokens.
.claude/skills/post-plan-workflow/SKILL.md (or your agent's skills folder).Plan approval is the green light for the full pipeline. Proceed through all three phases without stopping; the one expected stop is the turn that ends when a run-wave Method A launch hands control to the async notification (see Phase 2, Route).
Complete materialization before any implementation begins.
Prefer a stashed docRef over re-authoring note bodies. On HTTP+REST workspaces, the plan-capture hook stashes the just-approved plan as a plan document as ExitPlanMode fires, and reports the slug via additionalContext (Task Orchestrator: plan stashed as plan document '<slug>' (root <rootId>)). When that context is present, or manage_plan_documents(operation="list", rootId=..., status="pending") confirms a pending document for this root, use it as the source of truth for materialization — quote/reference its content instead of retyping the plan into note bodies. Fall back to the plan text already in context when no stashed doc exists (stdio setups, or the hook failed open).
create_work_tree (preferred for structured work with dependencies) or manage_items (for individual items). Apply appropriate schema tags based on the plan and the project's .taskorchestrator/config.yaml — this activates gate enforcement for each item. If the config defines separate schemas for containers vs. child tasks, apply the appropriate tag at each level..taskorchestrator/config.yaml's project.rootId. When known, set the new root item's parentId to that rootId (directly, or to the appropriate category container beneath it if one already exists) so materialized work lands inside the project's tree instead of at a bare depth 0. When no rootId is known, create at depth 0 as before.query_items(operation="search", query="<title key terms>", limit=5). Unscoped on purpose — depth-0 process-global items such as agent-observations sit outside any project ancestor, so an ancestorId-scoped search misses them. Show close matches as one FYI line (role + short id each) and keep materializing — the user decides whether to act; never auto-link, auto-skip or auto-cancel.BLOCKS for sequencing, fan-out/fan-in patterns for parallel workexpectedNotes in create responses — if the item's tags match a schema, the response includes the expected note keys and phases. Fill required queue-phase notes (feature-summary, task-scope, etc.) with content from the plan before advancing.feature-implementation root: keep its feature-summary note lean — goal (2-3 sentences), a findings→tasks table mapping plan findings to the child items just created, dependency edges between those children, and a pointer to non-goals (target under 2k chars). Put full alternatives/blast-radius/risk-flags/test-strategy detail in each child's task-scope note instead — that's where /spec-quality's full bar applies.If create_work_tree fails: Check partial state with query_items(operation='overview'). Delete partial items with manage_items(operation="delete", itemIds=["<uuid>"], recursive=true) and retry.
Do NOT dispatch implementation agents until materialization is complete. Agents need MCP item UUIDs to self-report progress.
Hand off to /task-orchestrator:run-wave only when ALL four conditions hold; each is a concrete probe:
get_blocked_items(ancestorId=<materialized root>).Active project: or Personal root: line), else project.rootId from the file on that context's Config: line, else .taskorchestrator/config.yaml.get_context(itemId) shows no missing queue notes) or is schema-free (the response has no noteSchema).query_rules(operation="list", rootId) lists protocol.entry-seat, protocol.in-phase-seat and protocol.read-only-agent. A seed made earlier this session (by init or the run-wave F3 repair) shows up in this list.If all four hold, invoke /task-orchestrator:run-wave <materialized root id> and follow it. Plan approval counts as run-wave's Checkpoint 1. When a degradation forces a human look (meta.excluded or meta.degradations non-empty, or an empty run), show the explain table and end the turn; never use AskUserQuestion. A Method A launch ending the turn is expected. run-wave's post-run replaces Phase 3 below, which then applies only to the hand-dispatch path.
If any condition fails, hand-dispatch as described below and add one line naming the failed condition(s); for conditions 2 and 4, point at /task-orchestrator:init.
Dispatch subagents to execute the plan:
guidance/skill via query_items(operation="schema", itemId=...) (expectedNotes itself is keys-only); embed guidance in the delegation prompt as authoring instructionsskill is set, include in the delegation prompt: "Before filling the <key> note, invoke /<skill> and follow its framework." This ensures subagents receive deterministic skill routing rather than relying on guidance proseadvance_item(trigger="start") once to enter work phase, fills work-phase notes, and returns. The orchestrator handles all further transitions (work→review or work→terminal depending on schema). Agents do NOT call advance_item a second timeimplementation-notes, session-tracking, etc.) as the agent worksget_blocked_items(ancestorId="<featureRootId>") to confirm upstream items completed — dependency gating implicitly verifies agents transitioned their items. ancestorId catches blockers anywhere in the feature's subtree (not just direct children, which parentId alone would miss). If downstream items are still blocked, investigate the upstream blockeradvance_item or complete_tree for terminal transitions on items delegated to agents — the orchestrator reviews and advances to terminal after agents returnDo NOT use AskUserQuestion between phases — proceed autonomously.
After all agents complete:
query_items(operation="search", parentId=..., role="work") — any results are items agents failed to transition. Use /status-progression to diagnose and manually advance stuck itemsget_context() health check to see what completed, what stalled, and what needs attentionget_context(itemId=...)The post-plan workflow is done. Report the final status to the user — what completed, what needs attention, and any items still in progress.
© 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/post-plan-workflow of jpicklyk/task-orchestrator.
Open the folder on GitHubat commit b688ea0
Post Plan Workflow 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 |
|---|---|---|---|---|---|---|
| Post Plan Workflow this skilljpicklyk/task-orchestrator | 207 | — | ~2k | Automated safety check: Pass | MIT | |
| MCP Server Builderanthropics/skills | 180k | 62 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 5 repos | ~1.2k | Automated safety check: Pass | MIT | |
| MCP Integration for Pluginsanthropics/claude-plugins-official | 37k | 11 repos | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Fastmcp Client CLIPrefectHQ/fastmcp | 28k | 1 repos | ~823 | Automated safety check: Pass | Apache-2.0 | |
| Crush Configurationcharmbracelet/crush | 29k | — | ~3.7k | Automated safety check: Pass | Custom licence |
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.
anthropics/claude-plugins-official
Explains how to bundle Model Context Protocol servers in a Claude Code plugin, covering config files, stdio, SSE, HTTP and WebSocket server types, and authentication.
PrefectHQ/fastmcp
Query and invoke tools on MCP servers using fastmcp list and fastmcp call.
charmbracelet/crush
Explains how to configure the Crush coding agent with crushrc or crush.json, covering providers, models, LSPs, MCP servers, hooks, permissions and config precedence.
mksglu/context-mode
Routes large command, file, API and browser output through context-mode tools so only the needed result enters the agent's context, instead of dumping it via Bash.
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
Internal, hook-triggered: materializes MCP items from the approved plan and dispatches implementation. Post Plan Workflow is an agent skill from jpicklyk/task-orchestrator. Internal, hook-triggered: materializes MCP items from the approved plan and dispatches implementation.
Post Plan Workflow fits situations like: tasks that involve MCP servers.
Run `npx skills add jpicklyk/task-orchestrator --skill post-plan-workflow -a claude-code`. Or copy the skill folder (claude-plugins/task-orchestrator/skills/post-plan-workflow in jpicklyk/task-orchestrator) into .claude/skills/post-plan-workflow in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jpicklyk/task-orchestrator --skill post-plan-workflow -a codex`. Or copy the skill folder (claude-plugins/task-orchestrator/skills/post-plan-workflow in jpicklyk/task-orchestrator) into .agents/skills/post-plan-workflow 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 post-plan-workflow -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/post-plan-workflow, .gemini/skills/post-plan-workflow, .github/skills/post-plan-workflow and .opencode/skills/post-plan-workflow in your project.
SKILL.md names no scripts, command-line tools or credentials: Post Plan Workflow 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.
Post Plan Workflow is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2k tokens (SKILL.md is roughly 7.9k 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 Post Plan Workflow: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 37k stars) and Fastmcp Client CLI (PrefectHQ/fastmcp, 28k 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.