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 agentmods add skills/adampoit/ai/taskwarriornpx skills add adampoit/ai --skill taskwarriorgit clone --depth 1 https://github.com/adampoit/aiWhat 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 | $0.00050 | $0.00842 |
| Opus 5 | $0.00025 | $0.00421 |
| Sonnet 5 | $0.00010 | $0.00168 |
| Haiku 4.5 | $0.00005 | $0.00084 |
Grade A, and why
taskwarrior scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Taskwarrior
Inspect and manage tasks with task.
task +PENDING export
List Tasks
Preferred command (JSON output):
task +PENDING export
With custom filters:
task project:work due:today +PENDING export
For tasks that fall between two dates (entry, completion, due, or modified time), use Bash variables:
start_date="<start-date>"
end_date="<end-date>"
task "((entry.after:${start_date} and entry.before:${end_date}) or (end.after:${start_date} and end.before:${end_date}) or (due.after:${start_date} and due.before:${end_date}) or (modified.after:${start_date} and modified.before:${end_date}))" export
Use task rc.verbose=nothing ... for concise text output when not using export.
Task Summary
Build summary counts with these commands:
task +PENDING export
task +OVERDUE export
task due:today +PENDING export
task due:tomorrow +PENDING export
task priority:H +PENDING export
Summarize counts plus notable tasks (for example overdue or high priority).
Task Details
Get one task by ID or UUID:
task <task-id-or-uuid> export
Add Task
Create a task (mutating):
task add "Write Q1 planning notes" project:planning due:tomorrow priority:M +work +writing
Attach Notes
task-note is an external Taskwarrior helper, not a built-in task command. Confirm it is installed before using it:
command -v task-note
It takes exactly one argument. It ensures the task has a Notes file: <notes-dir>/<uuid>.md (read this file for full content) annotation, then opens the note in an interactive editor via taskopen:
task-note <task-id-or-uuid>
Notes live in $XDG_DATA_HOME/tasknotes/<uuid>.md (default ~/.local/share/tasknotes/<uuid>.md).
Non-interactive (agents)
task-note <task> with no subcommand opens an editor, so agents should use the subcommands instead:
task-note <task-id-or-uuid> set <<'EOF'
# Note title
Note body...
EOF
task-note <task-id-or-uuid> append <<'EOF'
More details...
EOF
task-note <task-id-or-uuid> show # print the note contents
task-note <task-id-or-uuid> path # print the note file path
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.
- yesterday First seen · 126 lines · 50 tokens per session scan A 8c33b9ab1084
taskwarrior is a skill published in the GitHub repository adampoit/ai (2 stars, last pushed 7d ago), licensed MIT. It adds 50 tokens to every session and 842 once invoked, about $0.0003 per session on Opus 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 2026-08-31.
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