ワンクリックで
gather-context
Research codebase — surface patterns, find prior art, prepare for brainstorm. Spawns subagents if available.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
メニュー
Research codebase — surface patterns, find prior art, prepare for brainstorm. Spawns subagents if available.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
Long-running iterative development loops. Run arbitrarily-long tasks without diluting model attention. Triggers: ralph, ralph loop, iterative loop, long-running task, development loop.
Full compactor reference — tool parameters, anti-patterns, sandbox languages, context budget, workflows.
Diagnostics — validate config, session DB, runtimes, and troubleshoot compactor issues.
Context management — compact session, recall history, run code, search content.
Stats display — context savings, session metrics, compactions, sandbox and recall/search counters.
Helps you use the /unipi:btw side-conversation workflow effectively. Use when you want to think in parallel, ask side questions without interrupting ongoing work, or inject a side thread back into the main agent.
| name | gather-context |
| description | Research codebase — surface patterns, find prior art, prepare for brainstorm. Spawns subagents if available. |
Research the codebase thoroughly to prepare for brainstorming. Find patterns, prior art, and relevant context.
This skill MAY: read codebase, run read-only commands (find, grep, ls), spawn subagents, write findings. This skill MAY NOT: edit code, implement features, run tests that modify state.
/unipi:gather-context <string(greedy)>
string(greedy) — what to research (e.g., "authentication patterns", "how we handle errors", "database layer")@unipi/subagents extension is installedExit: Research plan ready.
If subagents available:
If no subagents:
Research areas:
Code structure:
Patterns & conventions:
Prior art:
Dependencies:
Exit: Context gathered from all areas.
Organize findings into clear categories:
## Key Findings
### Structure
- {Finding about project structure}
### Patterns
- {Finding about patterns used}
### Prior Art
- {Finding about existing similar work}
### Gaps
- {Finding about what's missing}
### Recommendations
- {Suggestion for brainstorm based on findings}
Present findings to user.
If the user already specified whether to save (e.g., "save findings to memory" or "just show me"), skip this gate and follow their preference. Otherwise, ask:
ask_user({
question: "Save this context?",
context: "Context gathered from {N} files across {areas}. Summary includes structure, patterns, prior art, and recommendations.",
options: [
{ label: "Save to memory", description: "Store findings in .unipi/memory/ for future sessions", value: "save" },
{ label: "Save to file", description: "Write findings to .unipi/docs/research/<topic>.md", value: "file" },
{ label: "Don't save", description: "Discard — context was just for this session", value: "discard" }
],
allowFreeform: false
})
.unipi/memory/ following the consolidate skill's memory file format..unipi/docs/research/<topic>.md using the synthesis output format from Phase 3.After the save decision, hand off:
"Context gathered. Ready to brainstorm solutions?"
/unipi:brainstorm <topic>
The brainstorm will start with this context already available — no need to re-research.