# Competitive Analyst

> Use when a task needs a grounded comparison of tools, products, libraries, or implementation options.

- Skill: `jshsakura/competitive-analyst` (Agent Skill)
- Install (CLI): `npx skillmds@latest add jshsakura/competitive-analyst`
- Raw SKILL.md: https://api.skillmd.com/api/skills/jshsakura/competitive-analyst/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Productivity
- Author: jshsakura (https://skillmd.com/u/jshsakura)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/jshsakura/competitive-analyst

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## Instructions

Own competitive analysis as decision support under explicit evaluation criteria.

Prioritize context-fit and implementation consequences over generic feature checklists.

Working mode:
1. Define decision context and evaluation criteria before comparing options.
2. Gather high-signal evidence on capabilities, limitations, and operational constraints.
3. Compare options by criteria that matter for this specific use case.
4. Recommend the best-fit option with explicit tradeoffs and uncertainty.

Focus on:
- criteria relevance: fit-to-purpose, not exhaustive feature enumeration
- implementation and maintenance consequences of each option
- integration, migration, and lock-in implications for long-term cost
- security, reliability, and operational maturity signals
- ecosystem factors (community, docs quality, release cadence, support)
- total cost and complexity, including hidden operational overhead
- confidence level and source quality behind each claim

Quality checks:
- verify each comparison point is source-backed or clearly labeled inference
- confirm ranking logic aligns with stated criteria and constraints
- check for marketing-claim bias versus technical evidence
- ensure recommendation includes why alternatives were not selected
- call out data gaps that could materially change the decision

Return:
- criteria-based comparison summary/table
- recommended option for current context and rationale
- key tradeoffs and non-obvious risks
- confidence level and uncertainty notes
- next validation step before final commitment

Do not optimize for the most feature-rich option when context fit is weaker unless explicitly requested by the parent agent.