check-feedback

Analyze rejection feedback to surface PMF signals like feature gaps and competitor pressure.

3|Updated May 28, 2026
One-click install
npx skills add https://github.com/aitit-inc/leadace --skill check-feedback-aitit-inc
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: check-feedback
Source: https://github.com/aitit-inc/leadace/tree/main/plugin/skills/check-feedback
Command: npx skills add https://github.com/aitit-inc/leadace --skill check-feedback-aitit-inc

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve? Sales rejection data often sits unused, even though it contains product-market-fit signals such as missing features prospects keep asking for or competitors that keep winning deals. This Skill turns recorded rejection feedback into a read-only PMF report so product and strategy decisions can be grounded in real prospect responses. ## Core Features & Use Cases - Feature Gap Analysis: Lists free-text feature_gap rejection notes with dates, organizations, and prospects, ordered most-recent-first. - PMF Reason Distribution: Compares 30-day and all-time counts and percentages for feature_gap, already_have_solution, and competitor_locked rejections. - Signal Summary: Closes with a plain-English verdict that detects thin data, dominant missing capabilities, or high competitor pressure. - Use Case: A founder asks whether a missing integration is costing deals; the report shows multiple recent rejections citing that capability, supporting a roadmap or strategy revision. ## Quick Start Run the check-feedback skill with a project ID to generate a PMF signal report from recorded rejection feedback.

Frequently Asked Questions about check-feedback

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I check rejection feedback for PMF signals?

Run the check-feedback skill with a project ID as the argument. It fetches rejection feedback summaries for 30-day and all-time windows with PMF scope, then renders feature gap notes and a reason distribution table.

What rejection reasons count as PMF signals?

The PMF scope filters to three reasons: feature_gap (a concrete missing capability), already_have_solution (an incumbent vendor), and competitor_locked (a multi-year contract). Counts and percentages are computed within that subset by the server.

Can I use rejection feedback to decide when to recontact prospects?

No. This skill is read-only product reflection and excludes tactical signals like recontact windows and decision-maker pointers. Those tactical signals are consumed automatically by the evaluate step in the daily cycle.

Why does the report say the signal is too thin?

When the total number of PMF-relevant rejections is below 3, the skill reports that the data is too thin to draw conclusions and recommends continued data collection instead of inventing product actions.

Does check-feedback modify any project data?

No. It is a read-only skill with no database writes or side effects. It only calls the get_rejection_feedback_summary tool and formats the returned data into a report.