How do I install the Agenthub Task Manager skill?

Run npx skillmds@latest add tomevault-io/agenthub-task-manager in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Agenthub Task Manager safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Agenthub Task Manager?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Agenthub Task Manager free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Agenthub Task Manager?

tomevault-io (@tomevault-io) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Agenthub Task Manager by tomevault-io

Name: Agenthub Task Manager
Author: tomevault-io

Agenthub Task Manager

User-invoked AgentHub workflow for planning a multi-part request and delegating its independent subtasks to parallel AgentHub agent sessions. Use only when the user explicitly invokes this skill to plan, create, list, or clean up AgentHub task sessions. Use when this capability is needed.

tomevault-io Updated Sep 17, 2026

File contents

AgentHub Task Manager

Use this workflow only because the user explicitly invoked this skill to plan and delegate work to parallel AgentHub agent sessions.

Plan And Create Task Sessions

Read the user's request and infer the independent subtasks yourself. Preserve explicit numbered or bulleted work streams as separate subtasks; do not split ordinary prose just because of punctuation, commas, semicolons, or conjunctions.
Call agent_hub_planning, passing the original prompt and the subtasks you inferred as subtasks. AgentHub does not split for you — with no subtasks it plans the whole prompt as a single task.
Review the returned assignments and the harnessCapabilities block — each harness's real installed skills and MCP servers. AgentHub launches a harness (Claude Code or Codex), not a model, so present only the harness, never a model name. When multiple harnesses are installed, each subtask comes with a suggested harness plus the matchedCapabilities that drove it. Confirm or override every suggestion by matching the subtask to the harness whose actual tools fit — e.g. a profiling subtask → the harness that has an xctrace/profiler tool; a SwiftUI subtask → the harness with a swiftui skill. Decide from the listed capabilities, never from a harness's general reputation, and cite the matching skill/tool in your rationale.
Present the final assignments (task, chosen harness + why, branch, launch prompt) and wait for explicit user approval.
Call agenthub_create_worktree_sessions only for approved assignments. Pass one task per assignment with explicit provider, branch, and prompt. Include startPath when the task belongs to a subdirectory; AgentHub uses nearby project markers to infer a sparse worktree and then launch the agent from that same relative path. Use sparseProfile only for extra required paths and fullCheckout: true only when the task genuinely needs the whole repository materialized.

For a single-task request, still call agent_hub_planning with one subtask so the agent and branch are explicit before approval.

List Or Delete Task Sessions

Use agenthub_list_worktrees before destructive cleanup when the target or session impact is unclear. Use agenthub_delete_worktree only after the user identifies the session to delete.

Boundaries

Do not use these AgentHub task tools for generic planning, fan-out, background work, or subagent requests unless the user explicitly invoked this skill. Preserve the current harness's native subagent and background-task capabilities.

Source: jamesrochabrun/AgentHub — distributed by TomeVault.

---name: agenthub-task-managerdescription: User-invoked AgentHub workflow for planning a multi-part request and delegating its independent subtasks to parallel AgentHub agent sessions. Use only when the user explicitly invokes this skill to plan, create, list, or clean up AgentHub task sessions. Use when this capability is needed.---# AgentHub Task ManagerUse this workflow only because the user explicitly invoked this skill to plan and delegate work to parallel AgentHub agent sessions.## Plan And Create Task Sessions1. Read the user's request and infer the independent subtasks yourself. Preserve explicit numbered or bulleted work streams as separate subtasks; do not split ordinary prose just because of punctuation, commas, semicolons, or conjunctions.2. Call `agent_hub_planning`, passing the original prompt and the subtasks you inferred as `subtasks`. AgentHub does not split for you — with no `subtasks` it plans the whole prompt as a single task.3. Review the returned assignments and the `harnessCapabilities` block — each harness's **real installed skills and MCP servers**. AgentHub launches a **harness** (Claude Code or Codex), not a model, so present only the harness, never a model name. When multiple harnesses are installed, each subtask comes with a *suggested* harness plus the `matchedCapabilities` that drove it. Confirm or override every suggestion by matching the subtask to the harness whose **actual tools** fit — e.g. a profiling subtask → the harness that has an xctrace/profiler tool; a SwiftUI subtask → the harness with a swiftui skill. Decide from the listed capabilities, never from a harness's general reputation, and cite the matching skill/tool in your rationale.4. Present the final assignments (task, chosen harness + why, branch, launch prompt) and wait for explicit user approval.5. Call `agenthub_create_worktree_sessions` only for approved assignments. Pass one task per assignment with explicit `provider`, `branch`, and `prompt`. Include `startPath` when the task belongs to a subdirectory; AgentHub uses nearby project markers to infer a sparse worktree and then launch the agent from that same relative path. Use `sparseProfile` only for extra required paths and `fullCheckout: true` only when the task genuinely needs the whole repository materialized.For a single-task request, still call `agent_hub_planning` with one subtask so the agent and branch are explicit before approval.## List Or Delete Task SessionsUse `agenthub_list_worktrees` before destructive cleanup when the target or session impact is unclear. Use `agenthub_delete_worktree` only after the user identifies the session to delete.## BoundariesDo not use these AgentHub task tools for generic planning, fan-out, background work, or subagent requests unless the user explicitly invoked this skill. Preserve the current harness's native subagent and background-task capabilities.---> Source: [jamesrochabrun/AgentHub](https://github.com/jamesrochabrun/AgentHub) — distributed by [TomeVault](https://tomevault.io).

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