Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Full-spectrum product research pipeline. Runs competitive analysis, technology trend scouting, user feedback analysis, and feature ideation. Triggers: on: research, competitive research, market research, feature discovery, what should we build next.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
You are an autonomous research-to-ideation agent. Do NOT ask the user questions. Run the full pipeline below without pausing between phases.
TARGET: $ARGUMENTS
PARALLEL EXECUTION: Use the Agent tool to run competitive analysis and feature discovery concurrently when both are independent.
Follow the instructions defined in the /compete skill exactly.
Produce the full Competitive Gap Analysis output including all sections
(Product Identity, Competitive Landscape, Feature Matrix, Critical Gaps,
Strategic Gaps, Differentiators, Our Edges, Industry Trends, Recommended Roadmap, Summary).
Save the report to docs/competitive-gap-analysis.md
as specified by the /compete skill (create the docs/ directory if it doesn't exist).
Do NOT stop here. Continue immediately to Phase 2.
Research current technology trends relevant to this project's domain. Use web search to find:
For each trend, note:
Save to docs/technology-trends.md.
Do NOT stop here. Continue immediately to Phase 3.
Gather and analyze real user feedback from available sources:
Produce a summary with:
Save to docs/user-feedback-analysis.md.
Do NOT stop here. Continue immediately to Phase 4.
Now follow the instructions defined in the /new-features skill exactly.
Read ALL .md files in the docs/ directory — this includes:
docs/competitive-gap-analysis.md from Phase 1docs/technology-trends.md from Phase 2docs/user-feedback-analysis.md from Phase 3Extract learnings from every file, synthesize feature ideas, and write
the report to docs/NewFeatures-X.md (where X is a 3-word kebab-case theme).
IMPORTANT: Features should heavily draw from ALL prior phases:
After completing all phases, validate the combined output:
STOP when:
IF STILL FAILING after 3 iterations:
When all phases are complete, print a summary:
Files generated:
docs/competitive-gap-analysis.md — Full competitive landscape + gap analysisdocs/technology-trends.md — Technology trends and opportunitiesdocs/user-feedback-analysis.md — User feedback from reviews, issues, and communitydocs/NewFeatures-[X].md — Actionable feature ideas derived from all findingsKey stats:
Next steps:
/spec [feature name] to generate implementation stories/iterate to start building a feature/arch-review to assess architecture readiness for the proposed featuresAfter producing output, record execution metadata for the /evolve pipeline.
Check if a project memory directory exists:
~/.claude/projects/skill-telemetry.md in that memory directoryEntry format:
### /research — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}
Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.
STRICT RULES:
/compete and /new-features apply to their respective phases.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Run a full Section 508 + WCAG 2.2 Level AA accessibility audit on a federal / .gov / public-sector website or ICT product. Triggers: "Section 508", "508 audit", "WCAG", "VPAT", "ACR".
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes actuarial modeling systems for loss reserving accuracy, premium pricing methodology, mortality/morbidity tables, stochastic modeling, and capital adequacy per SOA and Solvency II standards..
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes advertising yield across programmatic and direct-sold inventory including CPM/CPC/CPA performance, header bidding efficiency, fill rate optimization, inventory monetization strategies, and compliance with IAB standards and OpenRTB protocols..
日本語の概要は準備中です。原文の説明を表示しています。
Create and manage Architecture Decision Records using the Michael Nygard format. Triggers: you need to document architecture decisions, record technical choices, explain why a technology was chosen.
日本語の概要は準備中です。原文の説明を表示しています。
Analyzes affordable housing management software for unit allocation algorithms, waitlist management, income verification workflows, Fair Housing compliance, LIHTC and Section 8 program tracking, inspection scheduling, and tenant reporting..
日本語の概要は準備中です。原文の説明を表示しています。
Rewrites existing landing pages, blog posts, and documentation so AI search engines (Google AI Overviews, ChatGPT, Perplexity, Claude, Gemini) cite them. Triggers: an existing page underperforms in AI answers despite ranking well in classic SERPs.
日本語の概要は準備中です。原文の説明を表示しています。