skills.rest
cloud-native-tools
cloud-native-toolsOFFICIAL
Explore all skills by this author →
GitHub

memory-recall

Retrieves project context from indexed files using keyword and tag searches.

1|Updated May 6, 2022
Search Tags:#documentation#productivity#search#memory#knowledge-management#context-retrieval
One-click install
npx skills add https://github.com/cloud-native-tools/cws-lib-bash --skill memory-recall-cloud-native-tools
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory-recall
Source: https://github.com/cloud-native-tools/cws-lib-bash/tree/main/.specify/skills/memory-recall
Command: npx skills add https://github.com/cloud-native-tools/cws-lib-bash --skill memory-recall-cloud-native-tools

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python3, and includes scripts (resource) components.

What problem does it solve?

This Skill solves the problem of fragmented project knowledge by providing a centralized, searchable index of past decisions, session notes, and working state, preventing the loss of context across long-running tasks.

Core Features & Use Cases

  • Context Retrieval: Search through short-term session notes and long-term knowledge bases using keywords, tags, or features.
  • Decision Tracking: Quickly surface prior architectural decisions or conventions to ensure consistency in new tasks.
  • Use Case: When starting a new feature implementation, use this skill to recall previous discussions or constraints related to that specific feature key to avoid repeating past mistakes.

Quick Start

Use the memory-recall skill to search for all prior decisions related to the authentication feature.

Frequently Asked Questions about memory-recall

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

FAQPage Schema
How do I retrieve past project decisions and context from previous sessions?▼

Yes, you can search both short-term session notes and long-term knowledge bases. The system indexes local JSON files and executes keyword or tag-based queries to surface relevant architectural conventions and working state.

How do I search local JSON files for historical knowledge management data?▼

You search local JSON files by running a Python-based memory-utils engine. This script performs keyword and tag-based search operations across your indexed project memory to find specific constraints and historical context.

Do I need Python3 to search session notes and project memory?▼

Yes, Python3 is required to run the memory-utils engine for context retrieval. A local Python environment executes the scripts that perform the keyword and tag-based search operations on your indexed JSON files.

What is the best way to track architectural decisions and prevent context loss?▼

The best way to track architectural decisions is maintaining a centralized, searchable index of project memory. Retrieving prior decisions from a durable knowledge base ensures consistency and prevents knowledge fragmentation across long-running tasks.

When should I use a dedicated context retrieval tool for software engineering?▼

Use a dedicated context retrieval tool when starting new feature implementations. It recalls previous discussions and constraints related to specific feature keys, ensuring consistency and avoiding repeated mistakes from fragmented project knowledge.

Related Skills

Explore More Software Engineering Skills→
wewetv1987-cellwewetv1987-cell

memory-setup

Configure persistent memory search and workspace context storage for Moltbot and Clawdbot.

Community
Intermediate
evgenygurinevgenygurin
2

recall-project-memory

Retrieve past project decisions, patterns, and constraints from Mem0.

Community
Basic
luuspoo-createluuspoo-create

system-wiki

Compile raw insights into structured wiki entries with Obsidian-style links.

Community
Advanced
dtbuchholzdtbuchholz

qmd

Search project memory, skills, and documentation using semantic and keyword queries.

Community
Intermediate