Competitor Teardown
Skill ActiveStructured competitive analysis with feature matrices, SWOT, positioning maps, and UX review. Covers research frameworks, pricing comparison, review mining, and visual deliverables. Use for: market research, competitive intelligence, investor decks, product strategy, sales enablement. Triggers: competitor analysis, competitive analysis, competitor teardown, market research, competitive intelligence, swot analysis, competitor comparison, market landscape, competitor review, competitive landscape, feature comparison, market positioning
To provide users with a structured and automated approach to conducting in-depth competitive analysis, gathering market intelligence, and generating visual deliverables for strategic decision-making.
Features
- Structured competitive analysis frameworks
- Automated research via CLI tools
- Feature matrix generation
- SWOT analysis templates
- Positioning map visualization
- Review mining for user sentiment
- Visual deliverable creation
Use Cases
- Conducting market research for new product launches
- Performing competitor teardowns for strategic planning
- Generating competitive intelligence for investor decks
- Enabling sales teams with competitor insights
Non-Goals
- Performing actions on behalf of the user within competitor platforms
- Making purchasing decisions or sales pitches based on the analysis
- Replacing in-depth manual qualitative research entirely
Workflow
- Log in to the inference.sh CLI.
- Execute `belt app run` commands to gather research data (e.g., competitor overviews, pricing, reviews).
- Utilize screenshot tools to capture visual information from competitor websites.
- Structure findings into templates for feature matrices, pricing comparisons, and SWOT analyses.
- Generate positioning maps and other visual deliverables.
- Compile insights into executive summaries or detailed reports.
Prerequisites
- inference.sh CLI (`belt`) installed
- `belt login` executed
- Access to specific `belt` tools (e.g., `tavily/search-assistant`, `infsh/agent-browser`)
Documentation
- info:Configuration & parameter referenceWhile the commands and their basic inputs are shown, detailed documentation for all parameters of the underlying tools (e.g., `belt app run ... --input '{...}'`) and their defaults is not explicitly provided within the SKILL.md.
Versioning
- warning:Release ManagementThe README mentions MIT license but there is no clear versioning signal like a version number in frontmatter or GitHub releases. The installation instructions reference `main`, making it difficult to pin a specific version.
Code Execution
- info:Error HandlingThe skill relies on the `belt` CLI for error handling. The SKILL.md does not explicitly detail how errors from the underlying tools are caught and reported back to the user or agent.
Install
- warning:Installation instructionThe SKILL.md provides installation instructions for the `belt` CLI and examples of how to use the skill, but it lacks detailed end-to-end setup for authentication beyond `belt login` and does not specify required scopes or environment variables.
Errors
- info:Actionable error messagesError handling relies on the underlying `belt` CLI and its tools. The SKILL.md does not detail specific error messages or recovery steps for failures within this skill's workflow.
Practical Utility
- info:Edge casesThe skill focuses on research tasks, and while it doesn't explicitly detail edge cases or failure modes for its own workflow, it relies on the underlying `belt` tools to handle those.
Installation
npx skills add inferen-sh/skillsRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
Trust Signals
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