Frontmcp Deployment
agentfront/frontmcp
A skill your agent uses when deploying, building for production, packaging, or shipping a FrontMCP server.
Walks through how to launch and reach the MCP Task Orchestrator server container: transport, REST API, port publishing, config mounts and config-sync.
$ npx skills add jpicklyk/task-orchestrator --skill configure-server -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install jpicklyk/task-orchestrator configure-server --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/configure-server .claude/skills/configure-server && 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 "configure-server" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/configure-server into .claude/skills/configure-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "configure-server", 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/configure-serverType 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 configure-server -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install jpicklyk/task-orchestrator configure-server --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/configure-server .agents/skills/configure-server && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "configure-server" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/configure-server into .agents/skills/configure-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "configure-server", 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 configure-server -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install jpicklyk/task-orchestrator configure-server --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/configure-server .cursor/skills/configure-server && 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 "configure-server" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/configure-server into .cursor/skills/configure-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "configure-server", 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/configure-server--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 configure-server -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install jpicklyk/task-orchestrator configure-server --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/configure-server .gemini/skills/configure-server && 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 "configure-server" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/configure-server into .gemini/skills/configure-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "configure-server", 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 configure-serverInstalls 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 configure-server -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/configure-server .github/skills/configure-server && 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 "configure-server" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/configure-server into .github/skills/configure-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "configure-server", 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 configure-server -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 configure-server --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/configure-server .opencode/skills/configure-server && 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 "configure-server" agent skill from https://github.com/jpicklyk/task-orchestrator/tree/main/claude-plugins/task-orchestrator/skills/configure-server into .opencode/skills/configure-server/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "configure-server", 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.
configure-serverWalks through how to launch and reach the MCP Task Orchestrator server container: transport, REST API, port publishing, config mounts and config-sync.
The skill handles runtime and deployment choices for the MCP Task Orchestrator container, not onboarding or workflow rules. It opens by offering a recommended default through an `AskUserQuestion` prompt: HTTP transport with an unauthenticated REST API, no config mount and debug off, chosen because it suits a single developer who wants `config-sync` to hot-reload per-project config without restarts. Choosing to customize leads through the transport, REST mode and port questions.
STDIO and REST are treated as mutually exclusive: choosing STDIO skips the REST and port steps and renders a per-session `--rm -i` launch. A reference file, `references/runtime-config.md`, holds the exact environment settings, loopback and Windows/MSYS caveats and `.mcp.json` shapes, and is read before any command is rendered. Requests about schemas, gates or traits are sent to `/manage-schemas`. The excerpt also mentions an operator switch, `RESOURCE_LEASES_ENFORCED=false`, that turns off resource-lease gate enforcement server-wide.
6 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 3e83170. 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:
dockercurlFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use docker and curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
TASK_ORCHESTRATOR_API_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Task Orchestrator Server Setup loads about 3.1k tokens when it runs, and up to ~5.7k if it reads all its reference files. Until then it costs about 170 tokens; SKILL.md has 1,183 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 3e83170, republished under its MIT licence (© jpicklyk). 1,183 words, ~3,106 tokens.
.claude/skills/configure-server/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.Decides how the MCP Task Orchestrator container is launched and reached: transport, REST API mode,
port publishing, config mount, and config-sync. This is a runtime/deployment concern, distinct from
quick-start (first-time onboarding narrative) and manage-schemas (workflow gates/traits/
resources:/actor_authentication content inside .taskorchestrator/config.yaml). If the user wants
schema or gate changes — including resource-lease declarations — redirect to /manage-schemas instead
of proceeding here.
One operator escape hatch worth knowing when launching the container: RESOURCE_LEASES_ENFORCED=false
(env, default true) disables resource-lease gate enforcement server-wide — a kill switch for lease
contention incidents, same gate-policy category as DEGRADED_MODE_POLICY. Configuring which resources
exist and which traits declare them stays in /manage-schemas; this skill only knows the switch.
The full fragment catalog (exact env tuples, loopback caveat, Windows/MSYS caveat, .mcp.json shapes)
lives in references/runtime-config.md — this skill's job is the decision flow and rendering,
not re-deriving that catalog. Read it before rendering any command.
Before walking the full decision tree, offer the one-tap recommended path via AskUserQuestion:
AskUserQuestion(questions: [{
question: "How do you want to run the server?",
header: "Server setup",
multiSelect: false,
options: [
{ label: "Recommended default", description: "HTTP + REST API enabled, unauthenticated, loopback-bound (127.0.0.1). Enables config-sync out of the box. Best for a single developer working across multiple projects." },
{ label: "Customize", description: "Walk through transport, REST mode, config mount, and debug logging one at a time." }
]
}])Recommended default → skip straight to Step 5 (Render — HTTP) with: REST = unauthenticated, config mount = none, debug = off. Customize → Step 2.
Why this is the default: it is the majority deployment shape for a single developer who wants
config-sync (per-project config that hot-reloads without a restart) to just work across every
project they open, without hand-managing tokens. The image itself still ships conservative (STDIO,
REST off, 0.0.0.0 bind) — this posture is entirely rendered by this skill, never an image change.
AskUserQuestion(questions: [{
question: "Which transport?", header: "Transport", multiSelect: false,
options: [
{ label: "HTTP (Recommended)", description: "Detached daemon, serves /mcp on a published port. Required for REST API and config-sync." },
{ label: "STDIO", description: "Per-session process, no port, no REST API, no config-sync. Simpler, no persistent daemon." }
]
}])STDIO ⊥ REST — hard constraint: if the user picks STDIO, skip Steps 3-4 entirely (REST mode and
port are incoherent for a --rm -i per-session process) and go straight to Step 5 (Render — STDIO).
Tell the user plainly: "STDIO has no REST API and no config-sync — those require a persistent HTTP
daemon. If you want config-sync later, re-run this skill and choose HTTP."
HTTP → Step 3.
AskUserQuestion(questions: [{
question: "REST API mode?", header: "REST API", multiSelect: false,
options: [
{ label: "Unauthenticated (Recommended)", description: "No token needed. Loopback-bound only. Enables config-sync with zero extra setup." },
{ label: "Bearer token", description: "Token-authenticated. For shared/multi-user setups." },
{ label: "Off", description: "MCP only, no REST, no config-sync." }
]
}])references/runtime-config.md
("Loopback footgun") before the command, and force -p 127.0.0.1:3001:3001 in the render — never a
wider publish.~/.taskorchestrator-secrets/api-tokens.yaml. If the file doesn't exist yet, point at
current/docs/api-rest.md §1 for the token-generation snippet — this skill does not generate tokens.-e API_ENABLED=false; config-sync will no-op (tell the user).AskUserQuestion(questions: [{
question: "Mount this project's config as the server's global/fallback config?", header: "Config mount", multiSelect: false,
options: [
{ label: "This project (fallback)", description: "Mount ./.taskorchestrator read-only as AGENT_CONFIG_DIR — good for a single-project server." },
{ label: "None (multi-project)", description: "No mount. Per-project config flows in via config-sync into the DB per root — good for one server shared across projects." }
]
}])Then ask Yes/No for debug logging (LOG_LEVEL=DEBUG + DATABASE_SHOW_SQL=true).
Look up the exact fragments in references/runtime-config.md — do not improvise env values.
Render the .mcp.json args array shape (see reference doc, ".mcp.json shapes"):
{
"mcpServers": {
"mcp-task-orchestrator": {
"command": "docker",
"args": ["run", "--rm", "-i", "-v", "mcp-task-data:/app/data", "ghcr.io/jpicklyk/task-orchestrator:latest"]
}
}
}Add the config-mount fragment (as args entries, not env flags) if the user wants a project mount.
No REST, no port, no config-sync — say so.
The detached docker run command — compose the recommended-default tuple (or the customized
equivalent) from references/runtime-config.md:
docker run -d --name mcp-task-orchestrator-http --restart unless-stopped \
-v mcp-task-data:/app/data \
-e MCP_TRANSPORT=http -e API_ENABLED=true -e API_AUTH_MODE=none -e API_ALLOW_UNAUTHENTICATED=true \
-p 127.0.0.1:3001:3001 \
ghcr.io/jpicklyk/task-orchestrator:latest(Substitute the REST-off or bearer fragment, and add the config-mount / debug fragments, per the
user's Step 3-4 answers.) On Windows, run this via PowerShell with ${PWD} for volume paths —
see "Windows / MSYS path caveat" in the reference doc.
The .mcp.json HTTP entry (NOT an args array):
{
"mcpServers": {
"mcp-task-orchestrator": {
"type": "http",
"url": "http://localhost:3001/mcp"
}
}
}Client-side config-sync env — export in the user's own shell/profile, not the container:
TASK_ORCHESTRATOR_API_URL=http://localhost:3001A persistent alternative to this env var is a client.json (apiUrl only, never a token), written after checking /api/v1/health. The API URL resolves in this order: the env var, then a project-level client.json beside the located config (or in the main checkout for a linked worktree), then the user-level client.json. Project-mode /task-orchestrator:init writes the project-level file, but only for a loopback server reached at a bare origin (the hooks ignore a project-level URL on any other host, or with a path, query or fragment); /task-orchestrator:init --user writes the user-level file, which is unrestricted, so a non-loopback server needs that or the env var. The token still comes from the environment only.
Add TASK_ORCHESTRATOR_API_TOKEN=<token> only when the REST API requires authentication (bearer or jwks mode). Omitting this env var, with no
client.json supplying a URL either, is the single most common way config-sync silently no-ops (config-sync.mjs returns early when apiBaseUrl() in
hooks/api-client.mjs finds no URL) —
always render it, never treat it as optional polish.
If REST mode is unauthenticated, always print the SECURITY caveat (verbatim from
references/runtime-config.md → "Loopback footgun") immediately before or after the docker run block.
Non-loopback Host: if the user will reach the server by any name other than
localhost/127.0.0.1/[::1] — this includes a TASK_ORCHESTRATOR_API_URL or a .mcp.json url
using a compose service name, host.docker.internal, a LAN name, or a reverse-proxy hostname — add
the MCP_ALLOWED_HOSTS fragment from references/runtime-config.md → "Host allowlist
(MCP_ALLOWED_HOSTS)" to the docker run command, and point the user at that section for the format and
examples. Do not add a new AskUserQuestion step for this — infer it from the URL/hostname already in
play.
For any HTTP render, walk through:
docker ps --filter name=mcp-task-orchestrator-http --format "table {{.Names}}\t{{.Status}}\t{{.Ports}}"
docker logs --since 20s mcp-task-orchestrator-http.mcp.json (Step 5, piece 2) if not already in place, then run
/mcp in Claude Code — confirm mcp-task-orchestrator shows connected with all tools listed.curl http://localhost:3001/api/v1/health should return 200.host_not_allowed, or a JSON-RPC error (code -32000) on /mcp means the request's Host
header is not allowlisted — see references/runtime-config.md → "Host allowlist
(MCP_ALLOWED_HOSTS)".Next: run /task-orchestrator:init in each project (or /task-orchestrator:init --user once for a personal root).
New infrastructure features — config-sync, SSE events, the plan-capture hook, the SubagentStop
completion guard (phase-guard.mjs + phase-guard-record.mjs) — are HTTP-only, with a graceful
no-op on STDIO. Each checks for its own REST env var (TASK_ORCHESTRATOR_API_URL, etc.) and silently
skips when absent, rather than failing. STDIO remains fully supported for MCP tool calls themselves —
it is positioned as the local/evaluation mode: no persistent daemon, no REST surface, and
consequently none of these convenience features. When recommending a setup for ongoing project work
(not a one-off trial), prefer the HTTP render in Step 5 for this reason, in addition to config-sync's
per-project hot-reload benefit already covered in Step 1.
The completion guard reads GET /api/v1/items/{id}/gate, a READ-capability endpoint — under bearer
auth, the token rendered for TASK_ORCHESTRATOR_API_TOKEN needs read in addition to whatever
capability its other consumers need (config-sync's documented token is write-config only, which
does not imply read). A token scoped to write-config alone leaves the guard silently inert (every
gate GET returns 403, which the guard treats as fail-open, not an error) — call this out whenever
rendering a bearer-mode token for a workspace that also uses the guard.
Re-running this skill is safe — it always renders a fresh command from the current answers; it does
not read or depend on any previously-rendered state. To change an existing container's settings,
stop/remove it first (docker stop mcp-task-orchestrator-http && docker rm mcp-task-orchestrator-http),
then re-render and run the new command. (Maintainers building the image from source have a dedicated
detect-and-reuse flow in /deploy_to_docker — not needed for the published-image path this skill covers.)
© jpicklyk, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in claude-plugins/task-orchestrator/skills/configure-server of jpicklyk/task-orchestrator.
Open the folder on GitHubat commit 3e83170
Task Orchestrator Server Setup 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 |
|---|---|---|---|---|---|---|
| Task Orchestrator Server Setup this skilljpicklyk/task-orchestrator | 207 | — | ~3.1k | Automated safety check: Pass | MIT | |
| Frontmcp Deploymentagentfront/frontmcp | 146 | — | ~9.2k | Automated safety check: Notes | Apache-2.0 | |
| Generate Openenv Envadithya-s-k/FineEnvs | 443 | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Unraiddinglebear-ai/unraid | 135 | — | ~5.4k | Automated safety check: Notes | MIT | |
| Devsydevsy-org/devsy | 110 | — | ~1.7k | Automated safety check: Pass | MPL-2.0 | |
| Pluggedin Stack OpsVeriTeknik/pluggedin-app | 103 | — | ~1.3k | Automated safety check: Notes | MIT |
agentfront/frontmcp
A skill your agent uses when deploying, building for production, packaging, or shipping a FrontMCP server.
adithya-s-k/FineEnvs
Builds an OpenEnv (Hugging Face) variant of an RL environment.
dinglebear-ai/unraid
This skill should be used when the user mentions Unraid, asks to check server health, monitor array or disk status, list or restart Docker containers, start or stop VMs, read system logs, check…
devsy-org/devsy
Operate Devsy workspaces and providers for end users. An agent skill from devsy-org/devsy.
VeriTeknik/pluggedin-app
A skill your agent uses when deploying, restarting, verifying or rolling back the containerised plugged.in production stack, when the site returns 404 or 5xx after a deploy or git operation, or when…
github/gh-aw
Run and integrate Skillz MCP server with Docker for skill execution.
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.
jpicklyk/task-orchestrator
Guides the full lifecycle of a feature-implementation tagged MCP item (the feature container) — from queue through review.
Works with
Categories
Walks through how to launch and reach the MCP Task Orchestrator server container: transport, REST API, port publishing, config mounts and config-sync. The skill handles runtime and deployment choices for the MCP Task Orchestrator container, not onboarding or workflow rules. It opens by offering a recommended default through an `AskUserQuestion` prompt: HTTP transport with an unauthenticated REST API, no config mount and debug off, chosen because it suits a single developer who wants `config-sync` to hot-reload per-project config without restarts.
Task Orchestrator Server Setup fits situations like: registering or running the Task Orchestrator Docker image; enabling the REST API or exposing its port; switching between HTTP and STDIO transport; setting up config-sync for per-project configuration.
Run `npx skills add jpicklyk/task-orchestrator --skill configure-server -a claude-code`. Or copy the skill folder (claude-plugins/task-orchestrator/skills/configure-server in jpicklyk/task-orchestrator) into .claude/skills/configure-server in your project. Claude Code loads it when a task matches its description.
Run `npx skills add jpicklyk/task-orchestrator --skill configure-server -a codex`. Or copy the skill folder (claude-plugins/task-orchestrator/skills/configure-server in jpicklyk/task-orchestrator) into .agents/skills/configure-server 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 configure-server -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/configure-server, .gemini/skills/configure-server, .github/skills/configure-server and .opencode/skills/configure-server in your project.
Going by SKILL.md and its folder, Task Orchestrator Server Setup needs the command-line tools its instructions call (docker and curl) and credentials named TASK_ORCHESTRATOR_API_TOKEN. Our summary lists: Docker to run the Task Orchestrator container.
SKILL.md contains no URLs. Its commands use docker and curl, which can reach the network depending on how they are called. 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.
Task Orchestrator Server Setup is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.1k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.6k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Task Orchestrator Server Setup: Frontmcp Deployment (agentfront/frontmcp, 146 stars), Generate Openenv Env (adithya-s-k/FineEnvs, 443 stars), Unraid (dinglebear-ai/unraid, 135 stars) and Devsy (devsy-org/devsy, 110 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 8, 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.