Agent skill

competitor-analysis

Deep competitive analysis + ongoing monitoring. Checks user research for competitor mentions, sales notes, existing analysis. Integrates with retention-analysis and user-research-synthesis.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill competitor-analysis-timothynguyen04-pmos --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 19 KB
Bundled scripts: none
Path: skills/analysis/competitor-analysis-timothynguyen04-pmos/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

Review
written from the skill's own SKILL.md · Aug 5, 2026

What it does

The skill provides two modes: Deep Analysis (a comprehensive one-time research) and Ongoing Monitoring (regular, periodic tracking). It scans internal workspace data (user research, meetings, PRDs, strategy, metrics) to surface existing intelligence, identify gaps, and fill them with web research. It outputs a strategic report detailing defensive, offensive, and innovative plays, with a format path shown for outputs. It also integrates with other skills (retention-analysis, user-research-synthesis) and supports cross-skill workflow, including linking to battlecards and roadmap updates.

How it works

  1. It prompts for competitor names and mode selection (Deep Analysis or Ongoing Monitoring).
  2. It checks internal sources: context-library/research/, context-library/research/competitive-*.md, context-library/meetings/, context-library/prds/, context-library/strategy/, and context-library/metrics/ for relevant intelligence.
  3. If analytics MCP is connected, it may query churn data from Amplitude/Mixpanel.
  4. It aggregates internal intelligence, highlights gaps, then conducts web research to fill gaps.
  5. It produces outputs such as a comprehensive report (Deep Analysis) or monthly competitive intel updates (Ongoing Monitoring) and saves them to paths like outputs/research-synthesis/competitor-analysis-[date].md or outputs/research-synthesis/competitive-intel-[month].md.
  6. It suggests cross-skill references and how the findings should inform PRDs, product strategy, retention, and user research.

When to use it

Use Deep Analysis when entering a new market, launching major features, or preparing strategic decisions (roadmap, pricing, positioning). Use Ongoing Monitoring when you already have baseline intel and want regular updates (monthly check-ins).

What it can touch

The skill integrates with other workstreams and outputs, including:

  • Cross-Skill Integration: informs /prd-draft, /write-prod-strategy, /retention-analysis, /user-research-synthesis.
  • Output files: outputs/research-synthesis/competitor-analysis-[name]-[date].md (Deep Analysis) or outputs/research-synthesis/competitive-intel-[month].md (Ongoing Monitoring).

Caveats

The skill relies on internal context first; web research is intended only to fill gaps not covered by internal data. It requires precise competitor names and mode choice to function properly. No outcomes are promised beyond the stated outputs and process; internal intelligence must exist or be generated via the described steps. License and provenance notes are not part of the operational review.

From the SKILL.md

# /competitor-analysis - Strategic Competitive Intelligence Two modes: **Deep Analysis** (comprehensive one-time research) + **Ongoing Monitoring** (weekly/monthly tracking) ## Quick Start 1. Name the competitor(s) you want to analyze 2. Choose mode: **Deep Analysis** (full research) or **Ongoing Monitoring** (monthly check-in) 3. I check your workspace first -- user research, meeting notes, churn data, past analysis 4. I show what we already know, identify gaps, then fill gaps with web research 5. I deliver a strategic report with defensive, offensive, and innovative plays **Example:** "Analyze Competitor X -- we're losing enterprise deals to them" **Output:** `outputs/research-synthesis/competitor-analysis-[name]-[date].md` **Time:** Deep Analysis: 2-4 hours | Monitoring: 30 min/month ## Context Routing Logic (Internal - for Claude) **Automatic Context Checks:** When this skill is invoked, immediately check: | Source | Files/Folders | Search Terms | What to Extract | |--------|---------------|--------------|-----------------| | User Research | `context-library/research/*.md` | competitor name, "switched to", "chose", "vs [competitor]", "competitor" | Customer quotes, pain points,

What's inside
Steps it walks through
  1. Quick Start
  2. Context Routing Logic (Internal - for Claude)
  3. Step 0: Understanding What We Already Know
  4. Internal Intelligence Summary
  5. Gaps in Knowledge
  6. Step 1: Choose Your Analysis Mode
  7. Deep Analysis Mode
  8. Ongoing Monitoring Mode
  9. Deep Analysis Mode: PM-Specific Questions
  10. Question 1: Competitive Context
  11. Question 2: Customer Segment
  12. Question 3: Churn Reasons
  13. Question 4: Distribution Advantage
  14. Question 5: Lost Segments
Ships with 1 file
  • metadata.json
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About this skill
What does the competitor-analysis skill do?

Deep competitive analysis + ongoing monitoring. Checks user research for competitor mentions, sales notes, existing analysis. Integrates with retention-analysis and user-research-synthesis.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill competitor-analysis-timothynguyen04-pmos --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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