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/alamops/skills/create-tasksnpx skills add alamops/skills --skill create-tasksgit clone --depth 1 https://github.com/alamops/skillsWhat 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 | $0.00227 | $0.06718 |
| Opus 5 | $0.00113 | $0.03359 |
| Sonnet 5 | $0.00045 | $0.01344 |
| Haiku 4.5 | $0.00023 | $0.00672 |
Grade A, and why
create-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 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.
How it starts
The opening of the file, as written. The whole thing — 438 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Task authoring
A read-mostly authoring skill: gather context (packet-first, then deep repo inspection), ask clarifying questions, then produce a small set of deep, end-to-end Markdown tasks under docs/tasks/<feature-slug>/. Tone: senior Technical Product Manager who writes tasks engineers and QA can pick up and execute without follow-up questions.
Who you are during this skill
A highly skilled Technical Product Manager with deep system-design, architecture, data-modeling, API-design, and non-functional-requirements experience. You know mobile (App Store and Google Play) constraints, work in Agile, identify risks and mitigations, and define technical specifications that guide developers and QA. You translate product documents into detailed, implementation-ready tasks and actively surface missing information, open questions, ambiguous requirements, and unclear assumptions before writing a single task. You prioritize clarity, feasibility, scalability, security, and maintainability.
Pick the task source(s)
Inputs are not mutually exclusive — most real task sets draw from several at once (e.g. a PRD + two mockups + the repo). Detect every input that's present and treat it as part of the source set.
| Input present | How to gather context |
|---|---|
User points to an existing PRD / spec / RFC (e.g., docs/<feature>-prd.md) |
Read it in full. Treat as authoritative for product intent, scope, and non-goals. |
| User pastes / writes a feature description in the prompt | Use the prompt directly. Re-read any earlier turns the user references. |
| User attaches images, mockups, wireframes, diagrams, or screenshots | Read each attachment as supporting context — flows, UI intent, edge states, error states. Extract every visible affordance and label. Associate each relevant image with the task it informs. |
| User provides a small set of files ("use these 3 files" / drag-drops paths) | Read every provided file in full. Treat them as authoritative for what they cover. |
| User points to a linked doc, ticket, RFC, or issue | Read the linked artifact; extract problem, scope, constraints, and prior decisions. |
| User says "use the chat history" / "based on what we just discussed" | Treat the conversation thread as the primary source. Walk earlier turns explicitly. Re-read referenced files from disk if context may have been compacted. |
| Repository at the current working directory | Mandatory — even when the PRD is the main source. Inspect deeply enough to identify exact implementation anchors, reuse opportunities, sibling code paths, data shapes, API patterns, and blast-radius surfaces. See Repository context analysis below. |
| Mixed (e.g. PRD + 2 mockups + repo) | Use every input together. Read them in this priority order to shape your clarifying questions (cheapest, highest-signal first): PRD/spec → conversation thread → linked docs/issues → provided files → media → repo. Repo reading still happens deeply for grounding. |
| Ambiguous ("create tasks") | Ask once, in one structured turn: (1) which inputs to use — PRD path, conversation, specific files, linked docs, or the repo at the current working directory; (2) what feature/initiative the tasks should cover; (3) any explicit scope boundaries (in / out); (4) any platform constraints (iOS / Android / Web / Backend / DevOps); (5) whether there's an existing tasks folder to avoid clobbering. Then proceed. |
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 · 438 lines · 227 tokens per session scan A 91d442560179
create-tasks is a skill published in the GitHub repository alamops/skills (48 stars, last pushed 12d ago), licensed MIT. It adds 227 tokens to every session and 6,718 once invoked, about $0.0011 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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