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.