SkillCheatSheet
change-impact
An AI agent skill from affaan-m/ECC, scored 65 out of 100 by code.
Code score by group
It loses the most points in Done criteria (15), the group that checks whether there is a checklist and a step that verifies the work.
What the author says it does
Perform evidence-backed impact analysis before changing code, data, interfaces, or governance documents, then compare the planned impact with the actual diff after implementation. Covers call paths, data and schema, API contracts, tests, documentation, ADRs, deployment, migration, and rollback. Use for cross-module or high-risk changes, database migrations, authentication, public interfaces, blast-radius questions, pre-change checks, and post-implementation alignment.
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- affaan-m/ECC
- Folder
- skills/change-impact
- License
- MIT
- GitHub stars
- 301,615
- SKILL.md lines
- 87
- Other files
- 0
Add change-impact to your agent
npx skills add affaan-m/ECC --skill change-impactThe command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.
More skills from affaan-m/ECC
-
frontend-design-direction
Set an ECC-specific frontend design direction for production UI work. Use when building or improving websites, dashboards, applications, components, landing pages, visual tools, o…
Verified85A -
prompt-optimizer
Analyze draft prompts, detect intent and missing context, match ECC commands, skills, and agents, and output a ready-to-paste optimized prompt with diagnosis and rationale — advis…
Verified85A -
ui-demo
Record polished UI demo videos using Playwright. Use when the user asks to create a demo, walkthrough, screen recording, or tutorial video of a web application. Produces WebM vide…
Verified85A -
prompt-caching-strategy
Optimize LLM prompt caching hit rate to reduce API costs and improve latency. Analyzes prompt structure, identifies cacheable vs non-cacheable content, and recommends restructurin…
Verified84B -
loop-design-check
Design a goal-oriented agent loop or review one for failure modes: spinning, Goodhart-gaming the verifier, or running a wrong answer to completion. Covers machine-decidable goals,…
Verified80B -
plan-orchestrate
Read a plan document, decompose it into steps, classify each step, and emit the ready-to-paste ECC slash command for that step, carrying the step identifier and scope in the comma…
79B -
data-scraper-agent
Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Runs on a schedule, enriches data with a free…
78B -
accessibility
Design, implement, and audit accessible UI to WCAG 2.2 Level AA across Web, iOS, and Android — semantic ARIA roles and labels, accessibility traits and hints, focus management, co…
77B
Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.