context-surfing
Monitors context window health during large, long-running, multi-session, or explicitly…
Ensures alignment between user and Claude during feature/spec planning through a structured interview process. Use this skill when the user invokes /plan-interview before implementing a new feature, refactoring, or any non-trivial implementation task. The skill runs an upfront
$ npx -y skills add pskoett/pskoett-ai-skills --skill plan-interview --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/plan-interviewContext preview
The summary Claude sees to decide when to auto-load this skill.
Ensures alignment between user and Claude during feature/spec planning through a structured interview process. Use this skill when the user invokes /plan-interview before implementing a new feature, refactoring, or any non-trivial implementation task. The skill runs an upfront
name: plan-interview description: | Ensures alignment between user and Claude during feature/spec planning through a structured interview process. Use this skill when the user invokes /plan-interview before implementing a new feature, refactoring, or any non-trivial implementation task. The skill runs an upfront interview to gather requirements across technical constraints, scope boundaries, risk tolerance, and success criteria before any codebase exploration. Do NOT use this skill for: pure research/exploration tasks, simple bug fixes, or when the user just wants standard planning without the interview process.
gh skill install pskoett/pskoett-skills plan-interview
Fallback using the Agent Skills CLI:
npx skills add pskoett/pskoett-skills/skills/plan-interview
Every skill in this collection is built around a core philosophy — a principle that agents struggle to internalize on their own.
This skill's philosophy: **"Make the change easy, then make the change."**
Agents default to plowing straight through implementation, no matter how tangled the path. They rarely pause to ask: "Would a preparatory refactor make this change simple instead of hard?" Planning is where that question gets asked. During codebase exploration and plan generation, actively look for structural friction — code that makes the target change awkward, brittle, or overly complex. When you find it, the plan should propose a preparatory step: make the change easy first, then make the change itself. Two clean steps beat one heroic slog.
Run a structured requirements interview before planning implementation. This ensures alignment between you and the user by gathering explicit requirements rather than making assumptions.
User calls `/plan-interview <task description>`.
**Skip this skill** if the task is purely research/exploration (not implementation).
Check for the host's structured question tool (`ask_user`, `AskUserQuestion`, or an equivalent). Use it for focused questions that the user can answer before the next planning step. In hosts without a structured question tool, ask the same question directly in chat and pause for the response. Do not fall back to plain chat merely because the host uses a different tool name. Respect the host schema: if the tool accepts only one question per call, ask the domains sequentially rather than bundling them.
Cover ALL four domains before proceeding:
1. **Technical Constraints**
2. **Scope Boundaries**
3. **Risk Tolerance**
4. **Success Criteria**
Before leaving the interview phase, classify the task and choose a planning depth:
Let the user override this (`fast` vs `deep`) if they have a clear preference.
| Scenario | Action | |----------|--------| | Contradictory requirements | Make a recommendation with rationale, ask for confirmation | | User pivots requirements | Restart interview fresh with new direction | | Interrupted session | Ask user: continue where we left off or restart? |
After interview completes, explore the codebase to understand:
For complex or unfamiliar projects, do a brief context refresh before deep planning:
Before writing the plan, explicitly ask: **"Does the knowledge needed to complete this task exist somewhere I can reach?"**
For each significant implementation step, classify where the required knowledge lives:
A collection of skills for AI agents. Follows the Agent Skills specification and ships an Agent Plugins 1.0 portable package. This repository is my personal skill testing ground.
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