reflect-skills-from-me…
This skill should be used when the user asks to "reflect on skills from memory", "audit marketplace skills against memory",…
Run STORM phase 2 — outline generation. This skill should be used when the user asks to "generate an outline for a storm article", "draft a wikipedia-style outline", or invokes /storm:outline. Produces a draft outline from parametric knowledge then refines it using the research
$ npx -y skills add FradSer/dotclaude --skill outline --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/outlineContext preview
The summary Claude sees to decide when to auto-load this skill.
Run STORM phase 2 — outline generation. This skill should be used when the user asks to "generate an outline for a storm article", "draft a wikipedia-style outline", or invokes /storm:outline. Produces a draft outline from parametric knowledge then refines it using the research
name: storm-outline description: Run STORM phase 2 — outline generation. This skill should be used when the user asks to "generate an outline for a storm article", "draft a wikipedia-style outline", or invokes /storm:outline. Produces a draft outline from parametric knowledge then refines it using the research information table. user-invocable: true argument-hint: "<topic> [--output-dir PATH | --save] [--force]" allowed-tools: ["Read", "Write", "Edit", "Glob", "Grep", "Bash(mktemp:*)", "Bash(mkdir:*)", "Bash(date:*)", "Skill"]
Phase 2 of the STORM pipeline. Drafts an outline from the model's parametric knowledge, then refines it using the research conversations to reflect what was actually learned.
This phase is complete iff `outline.md` exists and has ≥2 sections. If `--force` is not set and it exists, skip and exit early.
1. Resolve output dir. 2. Read `research/conversations.jsonl` and `research/sources.json`. Concatenate the conversation histories as the refinement input. 3. **Draft** — generate `outline-draft.md` from parametric knowledge alone. This is the model's prior structure for the topic. Use markdown `## Section` headings. 4. **Refine** — reorganize the draft using the conversation history: merge redundant sections, add sections for material the research surfaced that the draft missed, drop sections the research did not support. Write the result to `outline.md`. 5. Mark "Introduction", "Conclusion", "Summary" sections as placeholders if present — they are filled in the `polish` phase, not here. 6. Verify `outline.md` has ≥2 sections. Update `run-config.json`: `phases.outline = "completed"`, section count.
Report: number of draft sections, number of refined sections, sections added/removed during refinement, and the path to `outline.md`.
A curated collection of 22 plugins for Claude Code, providing specialized agents, skills, and automation tools for development and productivity workflows.
This skill should be used when the user asks to "reflect on skills from memory", "audit marketplace skills against memory",…
Use acpx as a headless ACP CLI for agent-to-agent communication, always inside an isolated SubAgent. Use when running coding…
Delegates a self-contained task to a Google Gemini Managed Agent (Antigravity) running in a remote sandbox with code execution,…
Runs a deep-research query on Google Gemini's deep-research managed agent and returns a cited report. This skill should be used…
This skill should be used when the user asks to "understand a codebase", "get code context", "research a library", "explore a…
Execute this when the user requests code context for a repository, library, or any natural-language code/technology question…