competitive-research
Systematic competitive intelligence with parallel agent analysis. Analyzes competitors thoroughly and synthesizes into actionable insights.
What this skill does
# Competitive Research
Conduct systematic competitive research using the **competitor-researcher** agent. Analyzes each competitor thoroughly and synthesizes findings into actionable insights.
**Inspired by Teresa Torres' workflow for systematic competitive intelligence.**
## Entry Point
When this skill is invoked, start with:
```
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
COMPETITIVE RESEARCH
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Systematic competitive intelligence that compounds over time.
What competitors do you want to analyze?
(Names or URLs)
What's your focus?
• Pricing
• AI features
• UX/product experience
• Go-to-market
• All of the above
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
```
## Usage
```
/competitive-research
```
Then provide:
- Competitors to analyze (names or URLs)
- Focus areas (pricing, AI features, UX, etc.)
## What Happens
1. **Gathers input** - Which competitors? What focus?
2. **Researches sequentially** - Each competitor analyzed thoroughly (10-15 min each)
3. **Saves individual files** - One markdown file per competitor
4. **Synthesizes findings** - Comparison tables and strategic recommendations
5. **Creates Linear issue** (optional) - Track insights in your workflow
## First-Time Setup
On first run, you'll be asked where to save research:
```
Where should I save competitive research files?
Recommendation: Create a directory OUTSIDE your company codebase, like:
- ~/Documents/pm-work/competitive-research
- ~/pm-research
- ~/competitive-intel
This keeps sensitive competitive analysis separate from your company's git repos.
```
## The Compound Effect
This is your FIRST analysis - thorough and time-consuming.
Next time you update this research? Minutes, not hours.
That's how systems compound.
| Analysis Round | Time | What Happens |
|----------------|------|--------------|
| First | 1 hour | Thorough, structured research |
| Second | 15 min | Update existing files |
| Third | 15 min | Compare to previous versions |
## Output Structure
```
[research-dir]/
└── YYYY-MM-DD-[topic]/
├── competitor-1.md # Individual analysis
├── competitor-2.md # Individual analysis
├── competitor-3.md # Individual analysis
└── synthesis.md # Comparison & recommendations
```
## Synthesis Contents
The synthesis file includes:
- **Executive Summary** - What did you learn?
- **Strategic Positioning Comparison** - How competitors position
- **Feature/Capability Comparison** - Side-by-side table
- **Pricing Comparison** - Models and tiers
- **Strategic Gaps & Opportunities** - Where can we win?
- **Recommended Actions** - Now, next, later
## Linear Integration (Optional)
If Linear MCP is configured:
- Creates issue with executive summary
- Links to research files
- Highlights top 3 recommended actions
- Labels with "competitive-intel"
## Related Commands
- `/strategy-session "competitive positioning"` - Discuss findings strategically
---
**Philosophy (Teresa Torres):**
- Sequential reliability - Process one competitor at a time
- Compounding system - First analysis is thorough, updates are fast
- Data ownership - Everything stored locally
- Synthesis matters - Raw research isn't useful without insights
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.