Agent skill

Manage Taskboard

by chuspeeism in chuspeeism/dashi-taskboard

Manage Codex Taskboard issues and taskctl setup when the request names Codex Taskboard, e-taskboard, or taskctl, or the conversation already establishes that board as the target.

Apache-2.0Auto-check passed

Install Manage Taskboard

skills CLI
$ npx skills add chuspeeism/dashi-taskboard --skill manage-taskboard -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install chuspeeism/dashi-taskboard manage-taskboard --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/chuspeeism/dashi-taskboard.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/manage-taskboard .claude/skills/manage-taskboard && rm -rf skills-src

Use ~/.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/

Facts

Skill name
manage-taskboard
GitHub stars
3.3k
Token cost
~2.2k tokens
SKILL.md length
1,236 words
Files
3 (incl. references)
Skills in repo
1
Repo updated
First seen
Licence
Apache-2.0

At a glance

Manage Codex Taskboard issues and taskctl setup when the request names Codex Taskboard, e-taskboard, or taskctl, or the conversation already establishes that board as the target.

  • Works in 7 steps: For an existing issue, first run issue… → Treat backlog as not approved for… → If the move conflicts because the… → …
  • SKILL.md covers Select the CLI and active…, Terminology: local companion, Core workflow and Other operations
  • Calls codex

What it does

Manage Taskboard is an agent skill from chuspeeism/dashi-taskboard. Manage Codex Taskboard issues and taskctl setup when the request names Codex Taskboard, e-taskboard, or taskctl, or the conversation already establishes that board as the target. Not for GitHub, Phabricator, other external trackers, or unrelated product docs.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `agents/openai.yaml` and `references/cli.md`).

It works with GitHub. The repository describes itself as: 现代化可灵活嵌入的任务面板,支持 Codex、DeepSeek Harness. The licence is Apache-2.0.

Example prompts

  • “/manage-taskboard”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. For an existing issue, first run issue get and comment list. Also run attachment list --task. On the first handoff, omit --after and read…
  2. Treat backlog as not approved for execution. Unless the user explicitly authorizes that issue, do not claim it, move it to another status…
  3. If the move conflicts because the version is stale, run issue get and comment list again. Retry once with the latest version only when the…
  4. For a new durable requirement, run context current. Treat its project as a workspace match only when project.workspacePath is the current…
  5. Execute only the requested work in the issue's branch or worktree when one is bound.
  6. Verify the requested operation path. Add a comment with the changes, verification result, outcome, and remaining risks. Read the issue…
  7. Move an issue to done only after the user explicitly accepts it or asks to complete it. Use blocked when work cannot continue and canceled…

What it can do on your machine

Read from SKILL.md and the folder at commit 6a79ef5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Shell commands in SKILL.md call:

    • codex

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Manage Taskboard loads about 2.2k tokens when it runs, and up to ~6.3k if it reads all its reference files. Until then it costs about 69 tokens; SKILL.md has 1,236 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~69
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.3k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from chuspeeism/dashi-taskboard at commit 6a79ef5, republished under its Apache-2.0 licence (© chuspeeism). 1,236 words, ~2,162 tokens.

Download SKILL.mdSave it as .claude/skills/manage-taskboard/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
manage-taskboard
description
Manage Codex Taskboard issues and taskctl setup when the request names Codex Taskboard, e-taskboard, or taskctl, or the conversation already establishes that board as the target. Not for GitHub, Phabricator, other external trackers, or unrelated product docs.

Manage Taskboard

This skill serves the local-first Codex Taskboard product, including its configured LAN and cloud services.

Apply the workflow below only to work explicitly targeting Codex Taskboard or already established as belonging to it in the conversation. An issue identifier, repository, or generic request to manage tasks, sync status, or add comments does not establish that scope. For GitHub, Phabricator, or another external tracker, use that system's tools and workflow; do not query, claim, or mirror its issues in Taskboard unless the user asks for that board operation. When the target is unclear, clarify it before running taskctl.

Within that scope, use taskctl for every project, issue, relation, and comment operation. Consume its JSON output. Use the exact issue identifier returned by the taskboard or supplied in the prompt. Never assume, derive, or rewrite an identifier prefix.

Open only the relevant section of references/cli.md when command syntax is needed.

Select the CLI and active service

  • Use the exact taskctl binary and Taskboard URL supplied by the task or injected runtime. Do not replace them with a global CLI, the default port, or another board.
  • On Windows, when no binary is injected and the desktop app is installed, use & "$env:LOCALAPPDATA\Codex Taskboard\bin\taskctl.cmd" issue get ID --json in PowerShell. The packaged wrapper reads the active launcher runtime. If this packaged path is absent, stop and ask for the exact installed taskctl.cmd path; do not switch to a global CLI or guess the service URL.
  • On macOS, when no binary is injected and the desktop app is installed, use '/Applications/Codex Taskboard.app/Contents/Resources/bin/taskctl' issue get ID --json. Keep the single quotes because the path contains a space. The packaged wrapper reads the active launcher runtime; do not search the filesystem for another CLI or reconstruct the tokenized URL.
  • On Linux, when no binary is injected and Codex was started by the desktop app, use taskctl issue get ID --json. The desktop app adds its packaged wrapper to the managed Codex PATH; do not search the filesystem for another CLI or reconstruct the tokenized URL.
  • If that exact command reaches a sandbox restriction on the loopback service, retry the same command with the required permission. Do not switch binaries or endpoints.

Terminology: local companion

In this product, companion means the device-local loopback service used for cloud mode (Codex/Git/Skill/MCP, path mapping, Basic Auth proxy). Related names: local companion, loopback companion, CODEX_TASKBOARD_COMPANION_URL, cloud-companion.json, LOCAL_COMPANION_REQUIRED.

When writing Chinese, keep the English word or use 本地 companion / 本地配套服务 / 环回代理. Never translate as 伴侣 or invent 伴侣 API. Ordinary task/comment/attachment HTTP routes (/api/tasks, /api/comments, /api/attachments, …) are the Taskboard HTTP API (or local server API)—not “companion API”.

Core workflow

  1. For an existing issue, first run issue get and comment list. Also run attachment list --task. On the first handoff, omit --after and read the full results. Keep the separate nextCursor from each list. When the same task resumes, run issue get again, then pass each saved cursor to its matching list with --after so only new or modified entries are returned. Comment lists include the attachments on returned comments; use attachment list --comment with its own cursor when a known comment attachment list can grow. Read the description and latest comments before deciding whether to start. Treat comments as current requirements, including returned work. If they say to wait, not execute, or not start now, stop and report without changing the status.
  2. Treat backlog as not approved for execution. Unless the user explicitly authorizes that issue, do not claim it, move it to another status, or perform task work; its assignee alone is not authorization. If work may start, claim it before reading code, downloading attachments, analyzing the implementation, or doing any other task work. Move a claimable todo to in_progress with its current version; do not continue until the move succeeds. If it is already in_progress, continue only when it is bound to the current conversation. Never move an issue claimed by another conversation.
  3. If the move conflicts because the version is stale, run issue get and comment list again. Retry once with the latest version only when the issue is still a claimable todo, is not bound to another conversation, is not archived, and its description and latest comments are unchanged. If it was claimed, its status or requirements changed, it is archived, the service is unavailable, a permanent API error occurs, or the retry fails, stop and report. Never loop or take over another agent's claim.
  4. For a new durable requirement, run context current. Treat its project as a workspace match only when project.workspacePath is the current directory or one of its ancestors. An unmatched local project is the documented fallback, not proof that the requirement belongs in the global project. If the user named a target project or the working directory identifies one, run project list, select that exact project by id or name, and stop to ask if the result is ambiguous. Search existing project issues before creating one in that confirmed project, then pass its explicit id to issue create. Update a matching issue instead of creating a duplicate. Use the fallback only when the user explicitly wants the global project. Do not track trivial requests.
  5. Execute only the requested work in the issue's branch or worktree when one is bound.
  6. Verify the requested operation path. Add a comment with the changes, verification result, outcome, and remaining risks. Read the issue again, then move it to in_review with its current version.
  7. Move an issue to done only after the user explicitly accepts it or asks to complete it. Use blocked when work cannot continue and canceled when it will not continue.
Show full SKILL.md (294 more words)Show less

Other operations

  • Run taskctl project readme get [PROJECT_ID] to inspect project architecture, constraints, and conventions before planning or executing complex tasks.
  • Keep the project README focused on root overview and conventions; store detailed multi-page documentation in the local repository's docs/ folder.
  • Preserve existing issue scope when adding requirements or acceptance details.
  • Add only relations that the work requires. Use parent for contained work, blocks or blocked_by for dependencies, and related for close association.
  • For Codex controller attribution, let taskctl read CODEX_THREAD_ID or pass the exact Codex conversation ID with --thread-id. This value alone is not a complete task binding. For Claude Code, Pi, AGY, or Grok session traceability, pass --agent-platform claude|pi|agy|grok --session-id ID instead; see CLI session traceability. External metadata is not a Codex ownership binding and never substitutes for the five fields below.
  • Any issue that the current conversation claims or continues must store a complete threadBinding: threadId, codexProjectId, codexProjectKind, codexHostId, and workspacePath. For an unbound local issue launched with injected Taskboard context, use the current CODEX_THREAD_ID, the injected project id and workspace path, local project kind, and local host id. Pass all five explicit --binding-* options on the claim and every later issue move that retains ownership. If any identity field is unavailable, stop before moving the issue to in_progress; never create a legacy binding containing only threadId.
  • When an issue already has a complete threadBinding, preserve its exact five saved values on every status write. Do not rebuild or replace it from the current context, and never take over a binding owned by another conversation.
  • Use the latest returned version with --if-version for concurrent updates. On conflict, read the issue again and reconcile before retrying.
  • Download and inspect an inline ![alt](api/attachments/<id>/content) image only when it is needed to understand the requirement.

© chuspeeism, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/manage-taskboard of chuspeeism/dashi-taskboard.

  • SKILL.md
  • agents/openai.yaml
  • references/cli.md

Open the folder on GitHubat commit 6a79ef5

Compare with similar skills

Manage Taskboard 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.

Manage Taskboard compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Manage Taskboard this skillchuspeeism/dashi-taskboard3.3k—~2.2kAutomated safety check: PassApache-2.0
PR Babysitteropeninterpreter/openinterpreter69k3 repos~4.2kAutomated safety check: PassApache-2.0
Diagnosing Superpowers Sessionsobra/superpowers297k3 repos~1.7kAutomated safety check: PassMIT
Greplooponyx-dot-app/onyx32k4 repos~3.3kAutomated safety check: PassMIT
GitHub Deep Researchbytedance/deer-flow84k4 repos~1.3kAutomated safety check: PassMIT
Update V8 Versionopeninterpreter/openinterpreter69k2 repos~845Automated safety check: PassApache-2.0

Similar skills

  • PR Babysitter

    openinterpreter/openinterpreter

    Watches an open GitHub pull request until it merges, handling review comments, diagnosing CI failures and retrying flaky checks along the way.

    69k GitHub starsUsed in 3 repos~4.2k tokens
    DevelopmentAuto-check passed
  • Investigates a session where Superpowers went wrong, reads the transcripts on disk and produces an evidence-cited report, optionally prepared as a bug report for the maintainers.

    297k GitHub starsUsed in 3 repos~1.7k tokens
    Agent WorkflowsAuto-check passed
  • Greploop

    onyx-dot-app/onyx

    Iteratively improves a PR (GitHub), MR (GitLab), or shelved changelist (Perforce) until Greptile gives it a 5/5 confidence score with zero unresolved comments.

    32k GitHub starsUsed in 4 repos~3.3k tokens
    DevelopmentAuto-check passed
  • GitHub Deep Research

    bytedance/deer-flow

    Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.

    84k GitHub starsUsed in 4 repos~1.3k tokens
    Research & ScienceAuto-check passed
  • Update V8 Version

    openinterpreter/openinterpreter

    Bumps the pinned v8 and rusty_v8 versions in Codex, validates the release-candidate path with the v8-canary check, and traces failures to upstream build changes.

    69k GitHub starsUsed in 2 repos~845 tokens
    DevOps & CloudAuto-check passed
  • Last30days

    mvanhorn/last30days-skill

    Research what people actually say about any topic in the last 30 days.

    64k GitHub stars~7.9k tokensUpdated today
    Research & ScienceAuto-check: notes

Works with

Questions about Manage Taskboard

What does Manage Taskboard do?

Manage Codex Taskboard issues and taskctl setup when the request names Codex Taskboard, e-taskboard, or taskctl, or the conversation already establishes that board as the target. Manage Taskboard is an agent skill from chuspeeism/dashi-taskboard. Manage Codex Taskboard issues and taskctl setup when the request names Codex Taskboard, e-taskboard, or taskctl, or the conversation already establishes that board as the target.

How do I install Manage Taskboard in Claude Code?

Run `npx skills add chuspeeism/dashi-taskboard --skill manage-taskboard -a claude-code`. Or copy the skill folder (skills/manage-taskboard in chuspeeism/dashi-taskboard) into .claude/skills/manage-taskboard in your project. Claude Code loads it when a task matches its description.

How do I install Manage Taskboard in Codex?

Run `npx skills add chuspeeism/dashi-taskboard --skill manage-taskboard -a codex`. Or copy the skill folder (skills/manage-taskboard in chuspeeism/dashi-taskboard) into .agents/skills/manage-taskboard in your project. Codex loads it when a task matches its description.

Can I use Manage Taskboard in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add chuspeeism/dashi-taskboard --skill manage-taskboard -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/manage-taskboard, .gemini/skills/manage-taskboard, .github/skills/manage-taskboard and .opencode/skills/manage-taskboard in your project.

What does Manage Taskboard need to run?

Going by SKILL.md and its folder, Manage Taskboard needs the command-line tools its instructions call (codex).

Does Manage Taskboard access the network?

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.

Is Manage Taskboard safe to install?

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.

What licence does Manage Taskboard use?

Manage Taskboard is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Manage Taskboard use?

About 2.2k tokens (SKILL.md is roughly 8.6k 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 4.1k tokens, read only when the agent opens those files.

What are the alternatives to Manage Taskboard?

Skills that share tags, products or a category with Manage Taskboard: PR Babysitter (openinterpreter/openinterpreter, 69k stars), Diagnosing Superpowers Sessions (obra/superpowers, 297k stars), Greploop (onyx-dot-app/onyx, 32k stars) and GitHub Deep Research (bytedance/deer-flow, 84k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Manage Taskboard?

chuspeeism (a GitHub user) maintains it in chuspeeism/dashi-taskboard, which has 3,309 GitHub stars. The repository was last updated on September 29, 2026.

Source: chuspeeism/dashi-taskboard on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.