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 skills add onatm/agent-skills --skill linear-task-planninggit clone --depth 1 https://github.com/onatm/agent-skillsWrote 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/onatm/agent-skills/linear-task-planning)<a href="https://agentmods.dev/skills/onatm/agent-skills/linear-task-planning"><img src="https://agentmods.dev/badge/skills/onatm/agent-skills/linear-task-planning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/onatm/agent-skills/linear-task-planning"><img src="https://agentmods.dev/badge/skills/onatm/agent-skills/linear-task-planning.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00034 | $0.00716 |
| Opus 5.5 | $0.00014 | $0.00286 |
| Sonnet 5.5 | $0.00007 | $0.00143 |
| Haiku 4.5 | $0.00003 | $0.00072 |
Grade A, and why
linear-task-planning 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 2mo 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 — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Linear Task Planning
Turn approved engineering plans into clear, self-contained Linear issues. Use the official Linear MCP for discovery and mutations. Do not implement code or edit project files.
Source Authority
Read only the project material needed for the requested scope. Resolve conflicts in this order unless the project says otherwise:
- Accepted architecture decisions.
- Architecture and component designs.
- Roadmap phase gates and phase plans.
- The user's current instruction.
Do not generate implementation work that depends on an unresolved decision. Create a decision or research issue only when the source plan explicitly allows it or the user approves it.
Discover Linear Context
Use Linear MCP read tools before proposing work:
- Identify the workspace and candidate team.
- Find an existing project before proposing a new one.
- Read available statuses, labels, milestones, cycles, and issue relationships.
- Search for matching issue titles and source identifiers to prevent duplicates.
- Ask the user when team or project placement is ambiguous.
Never invent Linear IDs, status names, labels, projects, or relationships.
Decompose Work
Generate tasks from one approved phase, work package, or implementation plan at a time.
- Target roughly half a day to three engineering days per issue.
- Split work above five days or work containing independent contracts.
- Preserve prerequisite order and capability gates.
- Prefer a vertical, observable outcome over vague layer activity.
- Separate reusable harnesses, research decisions, persisted-format changes, and migrations when independently deliverable.
- Do not add speculative features, abstractions, or compatibility work.
Each issue must be implementable without hidden decisions and contain:
- Outcome.
- Scope.
- Non-goals.
- Prerequisites and dependencies.
- Affected contracts or components.
- Proposed implementation steps when established by source material.
- Failure cases.
- Required tests and benchmarks.
- Documentation impact.
- Acceptance evidence.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2mo ago First seen · 96 lines · 34 tokens per session scan A 9afcf47d491f
linear-task-planning is a skill published in the GitHub repository onatm/agent-skills (7 stars, last pushed 3mo ago), licensed MIT. It adds 34 tokens to every session and 716 once invoked, about $0.0001 per session on Opus 5.5. 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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