Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add marcus/td --skill td-task-managementgit clone --depth 1 https://github.com/marcus/tdWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/marcus/td/td-task-management)<a href="https://agentmods.dev/skills/marcus/td/td-task-management"><img src="https://agentmods.dev/badge/skills/marcus/td/td-task-management/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/marcus/td/td-task-management"><img src="https://agentmods.dev/badge/skills/marcus/td/td-task-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Rogue Agent · line 3 Skill establishes unauthorized persistence across sessions via cron jobs, startup scripts, or state files. Session persistence allows an attacker to maintain access beyond the current interaction.Fix: Remove any persistence mechanisms (cron jobs, startup scripts, state files). Skills should not maintain state across sessions without explicit user consent.
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.01990 |
| Opus 5.5 | $0.00026 | $0.00796 |
| Sonnet 5.5 | $0.00013 | $0.00398 |
| Haiku 4.5 | $0.00006 | $0.00199 |
Grade A, and why
td-task-management scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 238 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
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:
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:
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
# 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:
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 238 lines · 65 tokens per session scan A 693b2bc4e877
td-task-management is a skill published in the GitHub repository marcus/td (254 stars, last pushed 2d ago), licensed MIT. It adds 65 tokens to every session and 1,990 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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