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Feedback Roadmap

by LeroyCreates · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install feedback-roadmap
Description
Convert customer feedback, review themes, and complaint clusters into product improvement priorities with clear rationale and urgency ranking.
README (SKILL.md)

Feedback Roadmap

Ecommerce teams receive customer feedback across a dozen touchpoints — product reviews, post-purchase surveys, chat transcripts, return reason codes, and social DMs — but rarely have a structured process to turn that raw signal into an actionable product improvement plan. This skill synthesizes feedback clusters into a prioritized roadmap with clear rationale, urgency scores, and suggested owner assignments so product and operations teams know exactly what to fix next and why.

Use when

  • You have collected 20 or more customer reviews or survey responses and want to identify which product complaints appear most frequently so you can prioritize fixing them before next month's restock decision.
  • A new product has launched on TikTok Shop or Amazon and you are seeing 1-star reviews pile up around a specific feature or packaging issue and need to escalate a fix recommendation to your sourcing team within 48 hours.
  • You are preparing a quarterly product review and want to present stakeholders with a data-grounded list of the top 5–10 improvement opportunities ranked by customer impact, complaint volume, and estimated revenue risk.
  • Your customer service team has logged a batch of recurring complaint tags (e.g., "size runs small", "lid leaks", "charging cable too short") and you want to convert those tags into a formal product backlog with severity tiers.

What this skill does

This skill ingests raw feedback text, structured complaint logs, or theme summaries and applies a systematic clustering and prioritization process. It groups related complaints into named issue categories, counts occurrence frequency, estimates customer sentiment severity on a 1–5 scale, and cross-references the issue against revenue risk factors such as return rate impact and repeat-purchase suppression. The output is a ranked improvement roadmap table with an executive summary, urgency tiers (Critical / High / Medium / Low), suggested resolution owner (Product, Ops, Content, Sourcing), and a one-sentence rationale for each priority decision.

Inputs required

  • Feedback data (required): Raw review text, complaint log exports, survey open-ends, or pre-summarized theme lists. Paste directly or describe the top themes if you do not have raw text. The more specific the input, the more actionable the output.
  • Product context (required): Product name, category, and selling platform (e.g., "silicone baby bottle set, TikTok Shop US"). This helps calibrate urgency based on platform-specific return and review policies.
  • Business constraints (optional): Known limitations such as "supplier lead time is 90 days" or "we cannot change packaging before Q3" so the roadmap can mark certain fixes as deferred rather than immediate.

Output format

The output contains three sections. First, an Executive Summary (3–5 sentences) describing the dominant feedback themes and the single highest-priority fix. Second, a Prioritized Issue Table listing each issue cluster with columns for Issue Name, Complaint Volume (approximate), Severity Score (1–5), Urgency Tier, Suggested Owner, and a one-line Rationale. Third, a Next Steps section with three to five concrete action items formatted as owner-tagged tasks (e.g., "[Sourcing] Request updated sample with reinforced seam by April 15") to move the top-priority items forward immediately.

Scope

  • Designed for: ecommerce operators, DTC brand teams, TikTok Shop sellers, Amazon private label sellers
  • Platform context: TikTok Shop, Amazon, Shopee, Shopify, platform-agnostic
  • Language: English

Limitations

  • This skill does not connect to live review APIs or fetch data from Amazon, TikTok Shop, or Trustpilot in real time — all feedback must be pasted or summarized by the user.
  • Urgency scores are qualitative estimates based on the input provided and should be validated against your actual return rate and refund data before making major sourcing decisions.
  • This skill does not replace a dedicated product management process or customer research function — it is a structured first-pass analysis to accelerate prioritization, not a substitute for user interviews or VOC programs.
Usage Guidance
This skill appears coherent and low-risk because it only requires you to paste feedback and product context and it installs nothing. Before using it: (1) Do not paste personally identifiable information (names, order IDs, emails, payment data) — redact or summarize PII. (2) Provide representative sample sizes (the SKILL.md recommends 20+ responses) and include platform context so urgency estimates are meaningful. (3) Treat outputs as a structured first-pass: validate urgency and revenue-risk estimates against your real return/refund metrics and consult stakeholders before committing changes. (4) If you are concerned about the agent invoking the skill autonomously, check your platform's skill invocation settings or require explicit user invocation. If you plan to integrate this into an automated pipeline, consider adding safeguards to prevent accidental transmission of sensitive data.
Capability Analysis
Type: OpenClaw Skill Name: feedback-roadmap Version: 1.0.0 The skill bundle consists only of metadata and a markdown instruction file (SKILL.md) designed to guide an AI agent in analyzing customer feedback. There is no executable code, no network requests, and no instructions that attempt to exfiltrate data or manipulate the agent's core behavior beyond the stated purpose of feedback synthesis.
Capability Assessment
Purpose & Capability
Name, description, and required inputs (feedback text, product context, optional constraints) match the described output (clustered issues, severity, urgency, owners). There are no unrelated environment variables, binaries, or install steps requested.
Instruction Scope
SKILL.md instructs the agent to ingest user-pasted feedback and produce summaries and prioritized tables only. It explicitly states it does not fetch live review APIs. Minor caveat: because inputs are free-text pasted by users, the output quality depends entirely on what the user supplies and may require validation against real metrics.
Install Mechanism
No install spec and no code files — instruction-only skill means nothing is written to disk and no external packages or downloads occur.
Credentials
The skill declares no environment variables, credentials, or config paths — consistent with an analysis-only, paste-in tool.
Persistence & Privilege
always is false and the skill does not request elevated or persistent platform privileges. Autonomous invocation is allowed by default on the platform but that is normal and the skill does not require special privileges.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install feedback-roadmap
  3. After installation, invoke the skill by name or use /feedback-roadmap
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release.
Metadata
Slug feedback-roadmap
Version 1.0.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 1
Frequently Asked Questions

What is Feedback Roadmap?

Convert customer feedback, review themes, and complaint clusters into product improvement priorities with clear rationale and urgency ranking. It is an AI Agent Skill for Claude Code / OpenClaw, with 123 downloads so far.

How do I install Feedback Roadmap?

Run "/install feedback-roadmap" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Feedback Roadmap free?

Yes, Feedback Roadmap is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Feedback Roadmap support?

Feedback Roadmap is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Feedback Roadmap?

It is built and maintained by LeroyCreates (@leooooooow); the current version is v1.0.0.

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