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 commands/julianromli/droid-factory-template/generate-tasksgit clone --depth 1 https://github.com/julianromli/droid-factory-templateWrote 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/commands/julianromli/droid-factory-template/generate-tasks)<a href="https://agentmods.dev/commands/julianromli/droid-factory-template/generate-tasks"><img src="https://agentmods.dev/badge/commands/julianromli/droid-factory-template/generate-tasks.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00012 | $0.01069 |
| Opus 5 | $0.00006 | $0.00535 |
| Sonnet 5 | $0.00002 | $0.00214 |
| Haiku 4.5 | $0.00001 | $0.00107 |
Grade A, and why
generate-tasks 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 5d 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 — 76 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rule: Generating a Task List from User Requirements
Goal
To guide an AI assistant in creating a detailed, step-by-step task list in Markdown format based on user requirements, feature requests, or existing documentation. The task list should guide a developer through implementation.
Output
- Format: Markdown (
.md) - Location:
/tasks/ - Filename:
tasks-[feature-name].md(e.g.,tasks-user-profile-editing.md)
Process
- Receive Requirements: The user provides a feature request, task description, or points to existing documentation
- Analyze Requirements: The AI analyzes the functional requirements, user needs, and implementation scope from the provided information
- Phase 1: Generate Parent Tasks: Based on the requirements analysis, create the file and generate the main, high-level tasks required to implement the feature. IMPORTANT: Always include task 0.0 "Create feature branch" as the first task, unless the user specifically requests not to create a branch. Use your judgement on how many additional high-level tasks to use. It's likely to be about 5. Present these tasks to the user in the specified format (without sub-tasks yet). Inform the user: "I have generated the high-level tasks based on your requirements. Ready to generate the sub-tasks? Respond with 'Go' to proceed."
- Wait for Confirmation: Pause and wait for the user to respond with "Go".
- Phase 2: Generate Sub-Tasks: Once the user confirms, break down each parent task into smaller, actionable sub-tasks necessary to complete the parent task. Ensure sub-tasks logically follow from the parent task and cover the implementation details implied by the requirements.
- Identify Relevant Files: Based on the tasks and requirements, identify potential files that will need to be created or modified. List these under the
Relevant Filessection, including corresponding test files if applicable. - Generate Final Output: Combine the parent tasks, sub-tasks, relevant files, and notes into the final Markdown structure.
- Save Task List: Save the generated document in the
/tasks/directory with the filenametasks-[feature-name].md, where[feature-name]describes the main feature or task being implemented (e.g., if the request was about user profile editing, the output istasks-user-profile-editing.md).
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.
- 5d ago First seen · 76 lines · 12 tokens per session scan A 1067a8f9aac7
generate-tasks is a command published in the GitHub repository julianromli/droid-factory-template (52 stars, last pushed 8mo ago), licensed MIT. It adds 12 tokens to every session and 1,069 once invoked, about $0.0001 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 2026-08-30.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.