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/mhawthorne/gza/gza-task-draftnpx skills add mhawthorne/gza --skill gza-task-draftgit clone --depth 1 https://github.com/mhawthorne/gzaWrote 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/mhawthorne/gza/gza-task-draft)<a href="https://agentmods.dev/skills/mhawthorne/gza/gza-task-draft"><img src="https://agentmods.dev/badge/skills/mhawthorne/gza/gza-task-draft.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 | $0.00021 | $0.01197 |
| Opus 5 | $0.00010 | $0.00598 |
| Sonnet 5 | $0.00004 | $0.00239 |
| Haiku 4.5 | $0.00002 | $0.00120 |
Grade A, and why
gza-task-draft 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 — 116 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Draft Gza Task
Guide the user through a deliberate task creation process: clarify scope, surface risks, draft a prompt, get approval, then run uv run gza add.
Step 1: Read conventions
Read /workspace/AGENTS.md — specifically the "Creating Tasks from Conversations" section — to understand task types, flags, and prompt conventions.
Step 2: Assess description detail
Evaluate how detailed the user's description already is:
If vague or missing key context (objective unclear, scope undefined, approach unspecified): ask clarifying questions using AskUserQuestion (max 4 questions per call, 2–4 options each).
Focus on what matters most:
- What is the core objective / what problem does this solve?
- What type of work is this? (explore/plan/implement/review/task)
- Are there constraints, dependencies, or related tasks?
- What does "done" look like?
If already detailed (clear objective, known scope, specific requirements): skip to Step 3 directly.
Step 3: Draft the prompt + surface concerns
Draft a task prompt that:
- States the objective clearly and specifically
- References file paths, modules, or components when known
- Sets scope (what's in and out)
- Includes acceptance criteria for implement tasks
- Includes non-goals for implement tasks so the agent does not expand scope silently
- Names required tests or concrete failure modes to cover when known
- Calls out docs/help/config updates when operator-facing behavior changes
- Is appropriately sized (one task, one objective)
For implement tasks, push toward a prompt shape like:
- Objective
- Acceptance criteria
- Non-goals
- Relevant files/modules or affected subsystem
- Required tests
- Required docs/help/config updates, if applicable
If too many of those fields are unknown, ambiguous, or cross-cutting, recommend splitting the work or creating a plan task first rather than drafting a vague implement prompt.
Also identify and surface:
- Risks: What could go wrong or cause rework?
- Ambiguities: Unclear requirements that could derail the task
- Alternatives: Different approaches worth considering
- Sequencing: Should this be split (plan first, then implement)? Does it need
--depends-onor--based-on?
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 · 116 lines · 21 tokens per session scan A 8d3a5c8ef4b6
gza-task-draft is a skill published in the GitHub repository mhawthorne/gza (12 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 1,197 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.
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