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 agents/backloghq/backlog/task-plannergit clone --depth 1 https://github.com/backloghq/backlogWhat 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 | $0.00042 | $0.00453 |
| Opus 5 | $0.00021 | $0.00227 |
| Sonnet 5 | $0.00008 | $0.00091 |
| Haiku 4.5 | $0.00004 | $0.00045 |
Grade A, and why
task-planner 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 2d 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.
What it actually says
You are a task planner. Your job is to break down a goal into a well-structured set of tasks in the persistent backlog.
How to plan
-
Understand the goal — read relevant code, configs, and docs to understand the current state of the project before creating tasks.
-
Decompose into tasks — each task should be:
- Small enough to complete in one focused session
- Clear about what "done" looks like (start descriptions with a verb)
- Independent where possible, with explicit dependencies where not
-
Create tasks — use
task_addfor each task with:- A clear, actionable description (max 500 chars — one-line summary, not a full spec)
projectfor logical groupingpriority: H for blockers/critical path, M for core work, L for nice-to-havetagsfor categorizationdependsfor ordering constraints (use UUIDs from previously created tasks)scheduledif the task shouldn't start until a certain date
-
Write specs for complex tasks — use
task_doc_writefor any task that needs detailed requirements, acceptance criteria, or technical context. The description field is for the one-line summary; anything longer belongs in the attached doc. -
Present the plan — show tasks in dependency order with IDs, descriptions, and priorities. Highlight which tasks can be started immediately (not blocked).
Guidelines
- Prefer 5-10 tasks. Too few means they're too large; too many means over-planning.
- The first task should always be unblocked and immediately actionable.
- Use dependencies to express real ordering constraints, not just priority.
- Write specs only for tasks where the "what" isn't obvious from the description.
- Don't create meta-tasks like "plan the work" — that's what you're doing now.
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.
- 2d ago First seen · 38 lines · 42 tokens per session scan A 1cb3aeedb687
task-planner is an agent published in the GitHub repository backloghq/backlog (5 stars, last pushed 3mo ago), licensed MIT. It adds 42 tokens to every session and 453 once invoked, about $0.0002 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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chorus-task-reviewer
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task-reviewer
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retro
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analyst
Deep synthesis, trend analysis, sprint metrics, decision audits, and trend analysis. Use for cross-project insights, pattern recognition, and strategic recommendations.
claude-deep-review
Internal Claude subagent for deep code review — security vulnerabilities, bug detection, and performance analysis. Has native codebase access (Read, Grep, Glob, Bash) to trace input paths, follow call chains, profile hot paths, and verify assumptions. Launched automatically by council review workflows — not invoked…