What is customer-feedback-framework?

A framework for collecting and managing customer feedback through surveys, interviews, feature requests, and feedback analysis. It explains measures such as NPS, CSAT, and CES, which assess loyalty, satisfaction, and customer effort.

Use it to design customer surveys, plan interviews, analyze satisfaction and effort, prioritize feature requests, close the loop with customers, and create a 90-day feedback program.

It gives teams a structured way to gather customer opinions, identify churn causes, prioritize requests, and follow up on feedback.

customer-feedback-framework — Command by maigentic

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add commands/maigentic/stratarts/customer-feedback-framework

Clone the repo

git clone --depth 1 https://github.com/maigentic/stratarts

Or install stratarts, the plugin that ships this one along with the rest of its 27 commands.

Per session 49 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 8,879 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5	$0.00049	$0.08879
Opus 5	$0.00024	$0.04439
Sonnet 5	$0.00010	$0.01776
Haiku 4.5	$0.00005	$0.00888

Measured 3d ago against content hash 87f00ccdc812, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

customer-feedback-framework scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

stratarts/commands/customer-feedback-framework.md · 870 lines

How it starts

The opening of the file, as written. The whole thing — 870 lines — stays where its author put it; the contents beside it link to each section on GitHub.