Agent skill

Td Task Management

by marcus in marcus/td

Task management for AI agents across context windows. An agent skill from marcus/td.

MITAuto-check passedProductivity & Automation

Install Td Task Management

skills CLI
$ npx skills add marcus/td --skill td-task-management -a claude-code

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

GitHub CLI
$ gh skill install marcus/td td-task-management --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/marcus/td.git skills-src && mkdir -p .claude/skills && cp -r skills-src/td-task-management .claude/skills/td-task-management && 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
td-task-management
GitHub stars
251
Token cost
~2k tokens
SKILL.md length
720 words
Files
3 (incl. references)
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

Task management for AI agents across context windows. An agent skill from marcus/td.

  • Works in 6 steps: Single focused issue → Use single-issue… → Multiple related issues → Use td ws… → Work will continue elsewhere → Use td… → …
  • Agents need to track work
  • SKILL.md covers Overview, Quick Start, Key Workflows and Commands by Category, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Td Task Management is an agent skill from marcus/td. Task management for AI agents across context windows. Use when agents need to track work, log progress, hand off state, and maintain context across sessions. Includes workflows for single-issue focus, multi-issue work sessions, and structured handoffs. Essential for AI-assisted development where context windows reset between sessions.

Its SKILL.md is about 2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/ai_agent_workflows.md` and `references/quick_reference.md`).

It sits in Productivity & Automation, covering Task management and Context engineering. The repository describes itself as: A minimalist CLI for tracking tasks across AI coding sessions. The licence is MIT.

When your agent uses it

  • Agents need to track work
  • Maintain context across sessions

Example prompts

  • “/td-task-management”

Workflow steps

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

  1. Single focused issue → Use single-issue workflow
  2. Multiple related issues → Use td ws start for work sessions
  3. Work will continue elsewhere → Use td handoff or td ws handoff
  4. A decision aids continuity → Log it with --decision
  5. An uncertainty matters → Record it with --uncertain
  6. Track files → Use td link so future sessions know what changed

What it can do on your machine

Read from SKILL.md and the folder at commit b206bbf. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).

    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

Td Task Management loads about 2k tokens when it runs, and up to ~3.5k if it reads all its reference files. Until then it costs about 89 tokens; SKILL.md has 720 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~89
When it runs · the whole SKILL.md, loaded when a task matches
~2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.5k

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 marcus/td at commit b206bbf, republished under its MIT licence (© marcus). 720 words, ~1,993 tokens.

Download SKILL.mdSave it as .claude/skills/td-task-management/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
td-task-management
description
Task management for AI agents across context windows. Use when agents need to track work, log progress, hand off state, and maintain context across sessions. Includes workflows for single-issue focus, multi-issue work sessions, and structured handoffs. Essential for AI-assisted development where context windows reset between sessions.

td - Task Management for AI Agents

Overview

td is a minimalist CLI for tracking tasks and maintaining agent memory across context windows. When your AI session ends, td captures what was done, what remains, and what decisions were made—so the next session picks up exactly where the last one left off.

Core capability: Run td usage and get everything needed for the next action—current focus, pending reviews, open issues, recent decisions.

Quick Start

Starting a New Agent Context
bash
td usage --new-session -q  # Auto-rotate and show compact current state

Use td usage without -q when workflow guidance would be useful. Status output includes:

  • Active work sessions and recent decisions
  • What issues are pending review (you can review these)
  • Highest priority open issues
  • Recent handoffs from previous sessions
Single-Issue Workflow

For focused work on one issue:

bash
td start <issue-id>                    # Begin work
td log "OAuth callback implemented"    # Track progress
td log --decision "Using JWT tokens"   # Log decisions
td handoff <id> --done "..." --remaining "..."  # Capture state
td review <id>                         # Submit for review
Multi-Issue Workflow

For agents handling related issues:

bash
td ws start "Auth implementation"      # Start work session
td ws tag td-a1b2 td-c3d4             # Associate issues (auto-starts them)
td ws tag --no-start td-e5f6          # Associate without starting
td ws log "Shared token storage"       # Log to all tagged issues
td ws handoff                          # Capture state, end session

Key Workflows

Workflow 1: Starting New Work
bash
# 1. Check what to work on
td usage          # See current state
td next           # Highest priority open issue
td critical-path  # What unblocks most work

# 2. Start work
td start <id>

# 3. Begin logging
td log "Started implementation"
Workflow 2: Handing Off Work

Use a structured handoff when work will continue in another context:

bash
td handoff <id> \
  --done "OAuth flow, token storage" \
  --remaining "Refresh token rotation, error handling" \
  --decision "Using JWT for stateless auth" \
  --uncertain "Should tokens expire on password change?"

Keys:

  • --done - What is complete
  • --remaining - What remains
  • --decision - Why you chose approach X
  • --uncertain - What you're unsure about

Next session will see all this context with td usage or td context <id>.

Workflow 3: Reviewing Code
bash
# 1. See reviewable issues
td reviewable

# 2. Check details
td show <id>
td context <id>

# 3. Approve or reject
# Independent review:
td approve <id> --reason "Reviewed diff, looks good"
# Or, in trusted mode, when you implemented it yourself:
#   a sub-agent reviewed it — name them (no --reason needed):
td approve <id> --reviewed-by "code-reviewer sub-agent"
#   you reviewed it yourself — say so:
td approve <id> --self-review --reason "Reviewed own diff, tests pass"
# Or:
td reject <id> --reason "Missing error handling"

Independent review is preferred when practical. The default trusted mode also lets an involved session approve by saying who reviewed the work: --reviewed-by "<who>" credits someone else, --self-review --reason owns it. Both are recorded and neither is verifiable by td, so never name a reviewer who did not review — that reads as independent in the audit trail, which is worse than an honest self-review. In delegated and strict an involved session cannot approve at all.

Workflow 4: Handling Blockers
bash
# 1. Log the blocker
td log --blocker "Waiting on API spec from backend team"

# 2. Work on something else
td next              # Get another issue
td ws tag td-e5f6   # Add to work session

# 3. Come back to blocked issue later
td context td-a1b2  # Refresh context when blocker resolves

Commands by Category

Checking Status
  • td usage - Current state, reviews, next steps
  • td usage -q - Compact current state
  • td current - What you're working on
  • td ws current - Current work session state
  • td next - Highest priority open
  • td critical-path - What unblocks most work
Working on Issues
  • td start <id> - Begin work
  • td unstart <id> - Revert to open (undo accidental start)
  • td log "msg" - Track progress
  • td log --decision "..." - Log decision
  • td log --blocker "..." - Log blocker
  • td show <id> - View details
  • td context <id> - Full context for resuming
Handing Off
  • td handoff <id> --done "..." --remaining "..." - Single issue
  • td ws handoff - Multi-issue work session
Reviews
  • td review <id> - Submit for review
  • td reviewable - Issues you can review
  • td approve <id> --reason "..." - Approve an independent review
  • td approve <id> --reviewed-by "<who>" - Record who reviewed it when that is not you (trusted mode)
  • td approve <id> --self-review --reason "..." - Acknowledge and record a trusted-mode self-review
  • td approve <id> --record-only --reason "..." - Attest without closing; any session closes after
  • td reject <id> --reason "..." - Reject
Show full SKILL.md (284 more words)Show less
Creating/Managing Issues
  • td create "title" --type feature --priority P1 - Create
  • td create "title" --description-file body.md --acceptance-file acceptance.md - Agent-safe rich text
  • cat body.md | td update <id> --append --description-file - - Append rich text from stdin
  • td list - List all
  • td list --status in_progress - Filter by status
  • td block <id> - Mark as blocked
  • td delete <id> - Delete
File Tracking
  • td link <id> <files...> - Track files with issue
  • td files <id> - Show file changes
Other
  • td monitor - Live dashboard
  • td session --new "name" - Force new session
  • td undo - Undo last action

See quick_reference.md for full command listing.

Resources

quick_reference.md

Complete command reference organized by task type.

ai_agent_workflows.md

Detailed workflows for common AI agent scenarios:

  • Single-issue focus
  • Multi-issue work sessions
  • Handling blockers
  • Resuming work
  • Code review process
  • Tips for AI agents

Issue Lifecycle

open → in_progress → in_review → closed
         |              |
         v              | (reject)
     blocked -----------+

Key Principles

Session Isolation: Every terminal/context gets a session ID for continuity and audit. Independent review is preferred; trusted mode also lets an involved session approve by recording who actually reviewed the work.

Structured Handoffs: Record done/remaining/decisions/uncertain when another context will need to continue the work.

Minimal: Does one thing. Single binary, SQLite local storage (.todos/), no server, works with any AI tool.

For AI Agents

At the start of a new agent context:

bash
td usage --new-session -q

This auto-rotates sessions and gives you compact current state. Use judgment about how much tracking detail each task needs:

  1. Single focused issue → Use single-issue workflow
  2. Multiple related issues → Use td ws start for work sessions
  3. Work will continue elsewhere → Use td handoff or td ws handoff
  4. A decision aids continuity → Log it with --decision
  5. An uncertainty matters → Record it with --uncertain
  6. Track files → Use td link so future sessions know what changed

See ai_agent_workflows.md for detailed examples.

© marcus, MIT. 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 td-task-management of marcus/td.

  • SKILL.md
  • references/ai_agent_workflows.md
  • references/quick_reference.md

Open the folder on GitHubat commit b206bbf

Compare with similar skills

Td Task Management 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.

Td Task Management compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Td Task Management this skillmarcus/td251—~2kAutomated safety check: PassMIT
Memory Tasksbasicmachines-co/basic-memory4.1k1 repos~1.4kAutomated safety check: PassAGPL-3.0
Superset Agent Standupsuperset-sh/superset15k—~712Automated safety check: PassCustom licence
AgentRQ Workspace Agentagentrq/agentrq1.1k—~1.9kAutomated safety check: PassAGPL-3.0
Pi Messenger Crewnicobailon/pi-messenger720—~3.7kAutomated safety check: PassNone
AgentRQ Supervisoragentrq/agentrq1.1k—~2.7kAutomated safety check: PassAGPL-3.0

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Questions about Td Task Management

What does Td Task Management do?

Task management for AI agents across context windows. An agent skill from marcus/td. Td Task Management is an agent skill from marcus/td. Task management for AI agents across context windows.

When should I use Td Task Management?

Td Task Management fits situations like: agents need to track work; maintain context across sessions.

How do I install Td Task Management in Claude Code?

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

How do I install Td Task Management in Codex?

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

Can I use Td Task Management 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 marcus/td --skill td-task-management -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/td-task-management, .gemini/skills/td-task-management, .github/skills/td-task-management and .opencode/skills/td-task-management in your project.

What does Td Task Management need to run?

SKILL.md names no scripts, command-line tools or credentials: Td Task Management is instructions for the agent only.

Does Td Task Management 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 Td Task Management 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 Td Task Management use?

Td Task Management is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Td Task Management use?

About 2k tokens (SKILL.md is roughly 8k 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 1.5k tokens, read only when the agent opens those files.

What are the alternatives to Td Task Management?

Skills that share tags, products or a category with Td Task Management: Memory Tasks (basicmachines-co/basic-memory, 4.1k stars), Superset Agent Standup (superset-sh/superset, 15k stars), AgentRQ Workspace Agent (agentrq/agentrq, 1.1k stars) and Pi Messenger Crew (nicobailon/pi-messenger, 720 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Td Task Management?

marcus (a GitHub user) maintains it in marcus/td, which has 251 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on September 30, 2026.

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