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 Pixel-Process-UG/superkit-agents --skill planninggit clone --depth 1 https://github.com/Pixel-Process-UG/superkit-agentsWrote 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/pixel-process-ug/superkit-agents/planning)<a href="https://agentmods.dev/skills/pixel-process-ug/superkit-agents/planning"><img src="https://agentmods.dev/badge/skills/pixel-process-ug/superkit-agents/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/pixel-process-ug/superkit-agents/planning"><img src="https://agentmods.dev/badge/skills/pixel-process-ug/superkit-agents/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 | $0.00062 | $0.02589 |
| Opus 5.5 | $0.00025 | $0.01036 |
| Sonnet 5.5 | $0.00012 | $0.00518 |
| Haiku 4.5 | $0.00006 | $0.00259 |
Grade A, and why
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 1mo 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 — 300 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Structured Planning
Overview
Structured planning converts vague requirements into approved, documented implementation plans before any code is written. It forces clarifying questions, approach comparison with trade-offs, and explicit user approval — preventing the most common cause of wasted effort: building the wrong thing. Every task, regardless of perceived simplicity, goes through this process.
Announce at start: "I'm using the planning skill to create a structured implementation plan."
Trigger Conditions
- User requests a new feature, enhancement, or change
- A bug fix requires more than a one-line change
- Refactoring work spanning multiple files
- Any task where the approach is not already documented and approved
- Transition from brainstorming skill with an approved design
/plancommand invoked
Phase 1: Context Gathering
Goal: Understand the codebase and existing patterns before asking questions.
- Read relevant files, docs, recent commits, and CLAUDE.md
- Check memory files for known project context, stack, and conventions
- Review existing plans in
docs/plans/for related work - Identify existing patterns the new work should follow
- Note technical constraints discovered during exploration
STOP — Do NOT proceed to Phase 2 until:
- You have explored the relevant parts of the codebase
- You understand the existing architecture and patterns
- You have checked memory files for prior decisions
Phase 2: Clarifying Questions
Goal: Eliminate ambiguity by asking targeted questions one at a time.
- Ask ONE question per message — never overwhelm with multiple questions
- Prefer multiple choice questions when possible
- Study the codebase before asking — do not ask what you can discover
- Convert vague requirements into specific, testable criteria
Question Category Priority
| Priority | Category | Example Question |
|---|---|---|
| 1 | Purpose | "What problem does this solve? Who is it for?" |
| 2 | Success criteria | "How will we know it works? What does 'done' look like?" |
| 3 | Constraints | "Are there performance, compatibility, or timeline constraints?" |
| 4 | Non-goals | "What should we explicitly NOT build?" |
| 5 | Existing patterns | "Should we follow the pattern used in X, or is a new approach needed?" |
| 6 | Edge cases | "What should happen when [boundary condition]?" |
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.
- 1mo ago First seen · 300 lines · 62 tokens per session scan A be963faaea1c
planning is a skill published in the GitHub repository Pixel-Process-UG/superkit-agents (3 stars, last pushed 7mo ago), licensed MIT. It adds 62 tokens to every session and 2,589 once invoked, about $0.0002 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 2026-09-03.
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