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 joshukraine/dotfiles --skill plan-phasegit clone --depth 1 https://github.com/joshukraine/dotfilesWrote 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/joshukraine/dotfiles/plan-phase)<a href="https://agentmods.dev/skills/joshukraine/dotfiles/plan-phase"><img src="https://agentmods.dev/badge/skills/joshukraine/dotfiles/plan-phase/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/joshukraine/dotfiles/plan-phase"><img src="https://agentmods.dev/badge/skills/joshukraine/dotfiles/plan-phase.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00024 | $0.00927 |
| Opus 5.5 | $0.00010 | $0.00371 |
| Sonnet 5.5 | $0.00005 | $0.00185 |
| Haiku 4.5 | $0.00002 | $0.00093 |
Grade A, and why
plan-phase 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plan Phase
Plan the next phase of development from the PRD, create GitHub issues, and prepare for implementation. This skill bridges planning and building — it creates the structure but writes no application code.
Your task
Work through the steps below in order. Each step has a hard stop — do not proceed past a CHECKPOINT without explicit user approval.
Tip for the user: You can activate Claude Code's plan mode (shift+tab) during Steps 1-2 for an extra guardrail against premature code changes. Toggle out of plan mode before Step 3 so that Claude Code can run
gh issue createcommands.
Step 1: Orient
- Read
docs/prd/ROADMAP.mdto identify the current phase and what comes next - Read the PRD overview file (
docs/prd/*-overview.md) for project context - Read the specific PRD document(s) relevant to the upcoming phase
- Read the project's
CLAUDE.md - Review recent git history and merged PRs to understand current state
- Check for any open GitHub issues that may already cover upcoming work
Step 2: Draft the plan
Present a clear, concise plan for the next phase:
- Phase name and PRD reference (e.g., "Phase 2: Auth & Onboarding — see
02-auth-and-onboarding.md") - Scope summary: What this phase accomplishes in 2-3 sentences
- Proposed issues: A numbered list of discrete, implementable issues. Each issue should include:
- A clear title following the pattern:
feat: ...orfix: ...orchore: ... - A one-line description of what the issue covers
- Estimated complexity (small / medium / large)
- A clear title following the pattern:
- Implementation order: Which issues depend on others and the recommended sequence
- Out of scope: Anything explicitly deferred to a later phase
Keep the number of issues manageable — typically 3-7 per phase. If the phase is larger, break it into sub-phases.
CHECKPOINT 1: Present the plan and wait for user approval. The user may adjust scope, reorder issues, split or combine items, or request changes. Do not proceed until the user explicitly approves.
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 · 91 lines · 24 tokens per session scan A 14813cc8111e
plan-phase is a skill published in the GitHub repository joshukraine/dotfiles (429 stars, last pushed 3d ago), licensed MIT. It adds 24 tokens to every session and 927 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 2026-08-30.
Other skills, from other repositories
morning-coffee
Open or refresh the all-day Morning Coffee engineering workspace with reviews, calendar, incidents, RFCs, chosen work, local tasks and project tags. Use for morning check-ins, daily planning, intraday refreshes or an engineering overview.
factory-mcp
Use the Warp Factory MCP to hand work to a software factory and collaborate with it — bundle local work and send it to the cloud, find factory tasks from a Slack thread / Linear ticket / description, and pull a task down to test or iterate locally and hand it back.
oz-notify-user
Send a progress notification to the user who triggered this Oz task (e.g., via Slack or Linear).
oz-finish-task
Report task completion or failure back to the Oz platform when done with a task.
mbo-plan
Plan a new objective end-to-end in this repo's docs/mbo Management-By-Objective system — turn a GitHub issue or a gss draft-PR worktree into consistent design/spec/plan artifacts and track it in docs/mbo/index.md. Use this whenever the user wants to START planning or designing a new feature, skill, CLI, or service…
issue-grooming
Use when the user wants to groom, triage, prioritize, or clean up the GitHub issue backlog of a repo: "groom the issues", "triage the backlog", "which issues are already done", "prioritize the open issues", "close stale issues", "label issues 1-5", "refactor old issues to match the repo", or a periodic backlog review…