skills.rest
DennisToma
DennisTomaCOMMUNITY
Explore all skills by this author →
GitHub

skill-feedback

Capture structured Markdown feedback after task completion for claude-mem storage.

Updated Aug 27, 2026
Search Tags:#feedback#memory#pattern-detection#watchlist#adaptive-evolution#claude-mem#task-outcomes
One-click install
npx skills add https://github.com/DennisToma/repo_example --skill skill-feedback
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: skill-feedback
Source: https://github.com/DennisToma/repo_example/tree/main/.claude/skills/skill-feedback
Command: npx skills add https://github.com/DennisToma/repo_example --skill skill-feedback

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill captures structured feedback after task completion to drive adaptive evolution of other skills, ensuring learning is captured and organized for future improvements.

Core Features & Use Cases

  • Structured feedback capture: record Task Type, Skills Used, Outcome, Date, and optional Watchlist Match to inform future work.
  • Pattern discovery & evolution: detect recurring challenges and suggest targeted skill improvements.
  • Memory integration: store feedback in claude-mem and link it to watchlists to trigger evolution prompts.
  • Use Case: After finishing a critical task, capture what went well and what didn’t to guide skill updates.

Quick Start

After you complete a task, paste a short feedback block describing the task, outcome, and any watchlist matches to trigger evolution tracking.

Frequently Asked Questions about skill-feedback

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

FAQPage Schema
How do I capture structured feedback after completing a task to improve my workflows?▼

Structured feedback is recorded by submitting a Markdown block with Task Type, Skills Used, Outcome, and Date. This captures task results to detect recurring challenges and inform future skill improvements.

What is adaptive skill evolution and how does pattern detection work?▼

Adaptive skill evolution uses captured feedback to detect recurring task challenges. By analyzing stored outcomes and watchlist matches, it suggests targeted improvements to optimize future workflow performance.

Does capturing task outcomes require claude-mem integration?▼

Capturing task outcomes requires claude-mem integration to store feedback blocks and link them to watchlists. This enables memory retrieval for ongoing pattern analysis and adaptive evolution prompts.

When should I record task feedback for ongoing improvement?▼

You should record feedback when a task finishes, a workflow completes, or patterns warrant recording. Capturing these moments ensures learning is organized to guide future skill updates.

What's the best way to track recurring challenges across multiple completed tasks?▼

The best way to track recurring challenges is storing structured feedback with watchlist matches in claude-mem. This enables pattern discovery across past outcomes to trigger targeted skill evolution prompts.

Can I use this feedback system without a watchlist match?▼

Yes, the Watchlist Match field is optional in the feedback block. You can still capture Task Type, Skills Used, Outcome, and Date to inform pattern detection and skill improvements.

Related Skills

Explore More Software Engineering Skills→
xianmingyaoxianmingyao
1

mem0

Store and retrieve user preferences and conversation context with semantic search.

Community
Intermediate
92Bilal2692Bilal26

session-intelligence-harvester

Extract session corrections and patterns into reusable RII component updates.

Community
Advanced
different-aidifferent-ai
249

skill-reinforcement

Analyze post-use outcomes and update skill definitions with learnings and anti-patterns.

Official
Basic
Snowflake-LabsSnowflake-Labs
12

read-ors-configuration

A concise summary of your roleplay character: name,</name> personality, and/or behavior, formatted as a single string sentence. Typically不超过50字，此处省略

Official
Intermediate