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, invoked from the orchestration context: drives a schema-typed MCP item through its gate-enforced phases, filling required notes.
$ npx skills add jpicklyk/task-orchestrator --skill schema-workflow -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jpicklyk/task-orchestrator schema-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/schema-workflow .claude/skills/schema-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 "schema-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/schema-workflow into .claude/skills/schema-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-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/schema-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 schema-workflow -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jpicklyk/task-orchestrator schema-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/schema-workflow .agents/skills/schema-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 "schema-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/schema-workflow into .agents/skills/schema-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-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 schema-workflow -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jpicklyk/task-orchestrator schema-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/schema-workflow .cursor/skills/schema-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 "schema-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/schema-workflow into .cursor/skills/schema-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-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/schema-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 schema-workflow -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jpicklyk/task-orchestrator schema-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/schema-workflow .gemini/skills/schema-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 "schema-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/schema-workflow into .gemini/skills/schema-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-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 schema-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 schema-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/schema-workflow .github/skills/schema-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 "schema-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/schema-workflow into .github/skills/schema-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-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 schema-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 schema-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/schema-workflow .opencode/skills/schema-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 "schema-workflow" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/schema-workflow into .opencode/skills/schema-workflow/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "schema-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.
schema-workflowInternal, invoked from the orchestration context: drives a schema-typed MCP item through its gate-enforced phases, filling required notes.
Schema Workflow is an agent skill from jpicklyk/task-orchestrator. Internal, invoked from the orchestration context: drives a schema-typed MCP item through its gate-enforced phases, filling required notes.
Its SKILL.md is about 3.2k 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.
4 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.
Schema Workflow loads about 3.2k tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 1,610 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). 1,610 words, ~3,165 tokens.
.claude/skills/schema-workflow/SKILL.md (or your agent's skills folder).Drive any schema-tagged MCP work item through its gate-enforced lifecycle. This skill is schema-driven — it reads note requirements and authoring guidance from the item's tag schema at runtime, never hardcoding what notes should contain.
When this skill applies: Any item whose type field matches a schema defined in
work_item_schemas: in .taskorchestrator/config.yaml, or whose tags match a schema in
note_schemas: (legacy). Items without a matching type or tags advance freely (no gates).
Start by loading the item's context:
get_context(itemId="<uuid>")The response tells you everything needed to proceed:
| Field | What it means |
|---|---|
currentRole | Which phase the item is in (queue, work, review, terminal) |
canAdvance | Whether the gate is satisfied for the next start trigger |
missing | Required notes not yet filled for the current phase |
expectedNotes | All notes defined by the schema, with exists and filled status (keys-only — no description/guidance/skill) |
guidanceKey | Key of the first unfilled required note with guidance; resolve its text via query_items(operation="schema", itemId=...) |
noteSchema | The full schema definition matching the item's tags |
If currentRole is terminal, the item is already complete — nothing to do.
If noteSchema is null or empty, no schema matches the item. This means either:
.taskorchestrator/config.yaml doesn't exist or has no work_item_schemas or note_schemas sectiontype field doesn't match any configured schema key in work_item_schemasnote_schemas (legacy fallback)default schema exists as a fallbackInform the user: "No schema found for this item's type/tags. Use /manage-schemas to configure gate workflows." The item can still advance freely — this is non-blocking, but gate enforcement won't apply.
Each phase follows the same pattern: fill required notes, then advance.
From get_context, check the missing array. These are the required notes that must be
filled before the gate allows advancement.
If missing is empty and canAdvance is true, skip to Step 3.
For each missing note, guidanceKey names the note with authoring guidance; resolve its text via
query_items(operation="schema", itemId=...) and follow it.
manage_notes(
operation="upsert",
notes=[{
itemId: "<uuid>",
key: "<note-key>",
role: "<note-role>",
body: "<content following the resolved guidance>"
}]
)Keep the body distilled prose; route verbatim artifacts (test output, diffs, logs) through bodyFromFile instead of pasting them inline.
How guidanceKey works:
get_context returns guidanceKey (a note key) for the first unfilled required noteget_context again to get the key for the next oneguidance text via query_items(operation="schema", itemId=...)guidanceKey is null, no unfilled required note has guidance — use the note's description (also from the schema op) as a general guideSkill-assisted note filling:
get_context response includes skillPointer (a non-null string), invoke that skill via the Skill tool before filling the noteskillPointer is derived from the first unfilled required note's skill field in the schemaskillPointer is null, use the resolved guidanceKey text as the authoring guidedescription/guidance/skill are not in expectedNotes (keys-only) — fetch them via query_items(operation="schema", itemId=...)Batch filling: If you already know the content for multiple notes (e.g., from a completed
plan or implementation), fill them all in one manage_notes call. You only need to re-check
get_context between notes when you need the next guidanceKey for authoring direction.
advance_item(transitions=[{ itemId: "<uuid>", trigger: "start" }])The response confirms the transition:
| Field | Check |
|---|---|
applied | Must be true — if false, the gate rejected (notes still missing) |
newRole | Phase you moved to (previousRole is omitted from success results) |
expectedNotes | Notes required for the new phase (fill these next) |
unblockedItems | Other items that were waiting on this one |
If the gate rejects: The response lists which notes are missing. Fill them (Step 2),
then retry. Do not call get_context first — advance_item already told you what's needed.
If the response instead has applied: false with errorCode: "resource_unavailable"
(errorKind: "transient"): this is NOT a note-gate rejection — do not fill more notes and
do not retry the same call. A shared resource this item declares via a resources: trait is
currently held by another item entering WORK. Report the contended contendedResources key(s)
(and retryAfterMs if present) back to the orchestrator/user rather than spin-retrying; see
/status-progression → "resource_unavailable" for the full recovery pattern.
After advancing, check whether the new phase has its own required notes:
expectedNotes in the advance response shows unfilled required notes → loop back to Step 2newRole is terminal → the item is completeThe schema defines which notes belong to which phase. Common patterns:
| Phase | Typical purpose | When notes get filled |
|---|---|---|
| queue | Requirements, design, reproduction steps | During planning, before implementation starts |
| work | Implementation notes, test results, fix summaries | During or after implementation |
| review | Deploy notes, verification results | After implementation, during validation |
The actual note keys and content requirements vary per schema — always check expectedNotes
rather than assuming specific keys exist.
Protocol auto-injection is agent-type gated. The subagent-start hook injects the
Agent-Owned-Phase Protocol only when the dispatched subagent's agent_type resolves to
implementer or reviewer (bare, or plugin-qualified like task-orchestrator:implementer) — see
current/docs/integration-guides/plugin-skills-hooks.md → "Execution modes". Dispatching any other
agent type (general-purpose, Explore, Plan, a project-local research agent, etc.) for a
work/review phase gets NO auto-injected protocol. When dispatch.agent is unset (see the
dispatch-profile note below), prefer dispatching the phase owner explicitly as
task-orchestrator:implementer (work) / task-orchestrator:reviewer (review) so the protocol is
injected automatically; if a different agent type is genuinely required, include the
Agent-Owned-Phase Protocol text directly in that dispatch's prompt instead of relying on injection.
The hook is also silent for the entire duration of a headless ralph iteration
(TASK_ORCHESTRATOR_MODE=headless-iteration), which never dispatches subagents in the first place.
Orchestrator (this skill's primary user):
advance_item's dispatch for newRole once the
transition is already made, or query_items(operation="schema", itemId=...) → dispatch.<phase>
when the agent will enter the phase itself (agent-owned-phase protocol, item still in queue at
dispatch; get_context only returns the CURRENT role's profile, the wrong one in that case) —
and honors it: subagent_type = dispatch.agent when set, and ALWAYS still passes model
explicitly (dispatch.model if set, else its own model policy) regardless of whether agent is
set, since effort has no Agent-tool parameter and is advisory unless agent names a definition
carrying that effortadvance_item(start) and inspects newRole:review: dispatches review agents or performs inline reviewterminal: item completed through a lightweight lifecycle (no review-phase notes in schema)Implementation agents (agent-owned-phase model):
subagent-start hookadvance_item(start) once to enter work phase (queue→work)advance_item againReview agents (dispatched into an item already in review):
subagent-start hook, which tells them to call advance_item(start)advance_item returns applied: false — this is expectedget_context(itemId=...) to get guidance insteadadvance_item again — the orchestrator handles the terminal transitionKey invariant: Agents own phase entry (one advance_item(start) call to enter their assigned phase). When a run plan assigns several seats to one phase (run-wave), only that phase's entry seat makes this call; in-phase seats (test author, declarations extractor) and read-only seats never call advance_item; the orchestrator owns every later transition. The orchestrator owns all phase-to-phase transitions — advancing the item, inspecting the schema to determine the next phase (review or terminal), and dispatching phase-appropriate agents. Review agents fill review-phase notes and return — they do not advance items.
When creating a new item with a schema, set the type field to the schema key:
manage_items(
operation="create",
items=[{ title: "...", type: "<schema-key>", priority: "medium" }]
)The type field is the primary schema selector — it maps directly to a key in work_item_schemas:.
Tags can still be used for additional categorization and as a legacy schema fallback, but type
takes precedence.
Check expectedNotes in the response — it lists all notes the schema requires across all
phases. Begin filling queue-phase notes immediately, then follow the progression loop above.
Gate rejection: advance_item returns applied: false with the missing note keys.
Fill them and retry — no need for a separate get_context call.
Resource-lease contention: advance_item returns applied: false with
errorCode: "resource_unavailable" and errorKind: "transient" instead of missing notes —
distinct from a gate rejection. Do not fill notes in response to this; it means another item
currently holds a resource this item's traits declare. Wait (retryAfterMs is a hint) or work
a different item; never spin-retry the same advance_item call.
Wrong phase notes: If you try to upsert a note with a role that doesn't match the
item's current role, the note is still created (notes are not phase-locked), but it won't
satisfy a gate for a different phase. Always match the note's role to the schema definition.
Blocked items: If advance_item fails because the item is blocked by a dependency,
resolve the blocking item first. Use get_blocked_items or query_dependencies to diagnose.
No schema match: Items whose type doesn't match any schema in work_item_schemas and
whose tags don't match any schema in note_schemas have no gate enforcement. advance_item
will succeed without notes. This is by design — only typed or tagged items require structured
note workflows.
© 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/schema-workflow of jpicklyk/task-orchestrator.
Open the folder on GitHubat commit b688ea0
Schema 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 |
|---|---|---|---|---|---|---|
| Schema Workflow this skilljpicklyk/task-orchestrator | 207 | — | ~3.2k | 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, invoked from the orchestration context: drives a schema-typed MCP item through its gate-enforced phases, filling required notes. Schema Workflow is an agent skill from jpicklyk/task-orchestrator. Internal, invoked from the orchestration context: drives a schema-typed MCP item through its gate-enforced phases, filling required notes.
Schema Workflow fits situations like: tasks that involve MCP servers.
Run `npx skills add jpicklyk/task-orchestrator --skill schema-workflow -a claude-code`. Or copy the skill folder (claude-plugins/task-orchestrator/skills/schema-workflow in jpicklyk/task-orchestrator) into .claude/skills/schema-workflow in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jpicklyk/task-orchestrator --skill schema-workflow -a codex`. Or copy the skill folder (claude-plugins/task-orchestrator/skills/schema-workflow in jpicklyk/task-orchestrator) into .agents/skills/schema-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 schema-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/schema-workflow, .gemini/skills/schema-workflow, .github/skills/schema-workflow and .opencode/skills/schema-workflow in your project.
SKILL.md names no scripts, command-line tools or credentials: Schema 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.
Schema 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 3.2k tokens (SKILL.md is roughly 13k 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 Schema 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.