Agent Builder
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
Extract durable memories from recent conversation turns into user, feedback, project, and reference categories while avoiding stale code-state facts.
Install Memory Extractor
$ npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LearnPrompt/cc-harness-skills memory-extractor --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LearnPrompt/cc-harness-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/memory-extractor .claude/skills/memory-extractor && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "memory-extractor" agent skill from https://github.com/LearnPrompt/cc-harness-skills/tree/main/skills/memory-extractor into .claude/skills/memory-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-extractor", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LearnPrompt/cc-harness-skills/tree/main/skills/memory-extractorType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LearnPrompt/cc-harness-skills memory-extractor --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LearnPrompt/cc-harness-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/memory-extractor .agents/skills/memory-extractor && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "memory-extractor" agent skill from https://github.com/LearnPrompt/cc-harness-skills/tree/main/skills/memory-extractor into .agents/skills/memory-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-extractor", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LearnPrompt/cc-harness-skills memory-extractor --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LearnPrompt/cc-harness-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/memory-extractor .cursor/skills/memory-extractor && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "memory-extractor" agent skill from https://github.com/LearnPrompt/cc-harness-skills/tree/main/skills/memory-extractor into .cursor/skills/memory-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-extractor", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LearnPrompt/cc-harness-skills.git --path skills/memory-extractor--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LearnPrompt/cc-harness-skills memory-extractor --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LearnPrompt/cc-harness-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/memory-extractor .gemini/skills/memory-extractor && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "memory-extractor" agent skill from https://github.com/LearnPrompt/cc-harness-skills/tree/main/skills/memory-extractor into .gemini/skills/memory-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-extractor", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LearnPrompt/cc-harness-skills memory-extractorInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LearnPrompt/cc-harness-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/memory-extractor .github/skills/memory-extractor && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "memory-extractor" agent skill from https://github.com/LearnPrompt/cc-harness-skills/tree/main/skills/memory-extractor into .github/skills/memory-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-extractor", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LearnPrompt/cc-harness-skills memory-extractor --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LearnPrompt/cc-harness-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/memory-extractor .opencode/skills/memory-extractor && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "memory-extractor" agent skill from https://github.com/LearnPrompt/cc-harness-skills/tree/main/skills/memory-extractor into .opencode/skills/memory-extractor/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-extractor", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
memory-extractor- GitHub stars
- 236
- Token cost
- ~347 tokens
- SKILL.md length
- 122 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 6
- Repo updated
- First seen
- Licence
- MIT
At a glance
Extract durable memories from recent conversation turns into user, feedback, project, and reference categories while avoiding stale code-state facts.
- AI & LLM Engineering work in your project
- SKILL.md covers Use It For, Avoid It For, Quick Start and Four Types, plus 2 more sections
- Runs Python scripts from its folder; calls python3
What it does
Memory Extractor is an agent skill from LearnPrompt/cc-harness-skills. Extract durable memories from recent conversation turns into user, feedback, project, and reference categories while avoiding stale code-state facts.
Its SKILL.md is about 350 tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `README.md`, `references/prompt-template.md` and `references/source-notes.md`).
It sits in AI & LLM Engineering. The repository describes itself as: Portable CC-inspired skills for memory, verification, multi-agent coordination, context compression, and proactive coding-agent workflows. The licence is MIT.
When your agent uses it
- AI & LLM Engineering work in your project
Example prompts
- “/memory-extractor”
Requirements
- Python 3
What it can do on your machine
Read from SKILL.md and the folder at commit 3899650. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Memory Extractor loads about 347 tokens when it runs, and up to ~678 if it reads all its reference files. Until then it costs about 42 tokens; SKILL.md has 122 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from LearnPrompt/cc-harness-skills at commit 3899650, republished under its MIT licence (© LearnPrompt). 122 words, ~347 tokens.
Download SKILL.mdSave it as
.claude/skills/memory-extractor/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- memory-extractor
- description
- Extract durable memories from recent conversation turns into user, feedback, project, and reference categories while avoiding stale code-state facts.
Memory Extractor
Use this skill when you want to persist durable collaboration context from the latest conversation turns.
Use It For
- capturing user preferences
- saving feedback about how to work
- recording non-code project constraints or deadlines
- storing pointers to external systems
Avoid It For
- storing code structure or file locations
- saving short-lived task state that belongs in a plan
- duplicating an existing memory topic without checking first
Quick Start
Build a manifest of existing memories:
python3 {baseDir}/scripts/memory_manifest.py --memory-root /path/to/memoryThen use the portable prompt in references/prompt-template.md.
Four Types
userfeedbackprojectreference
Rules
- save only durable signals
- avoid code-state facts that can drift
- prefer updating an existing topic file
- organize by topic, not chronology
Supporting Files
- Prompt template: references/prompt-template.md
- Source notes: references/source-notes.md
- Helper script:
python3 {baseDir}/scripts/memory_manifest.py ...
© LearnPrompt, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (scripts, references) in skills/memory-extractor of LearnPrompt/cc-harness-skills.
- SKILL.md
- README.md
- references/prompt-template.md
- references/source-notes.md
- scripts/memory_manifest.py
Open the folder on GitHubat commit 3899650
Compare with similar skills
Memory Extractor next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Memory Extractor this skillLearnPrompt/cc-harness-skills | 236 | — | ~347 | Automated safety check: Pass | MIT | |
| Agent BuildershareAI-lab/learn-claude-code | 78k | 6 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Planning With Filesjarrodwatts/claude-code-config | 1.1k | 5 repos | ~967 | Automated safety check: Pass | None | |
| Codebase Managementgiancarloerra/SocratiCode | 3.3k | 1 repos | ~1.8k | Automated safety check: Pass | AGPL-3.0 | |
| Context Compressionguanyang/open-agent-hub | 975 | 2 repos | ~4.6k | Automated safety check: Pass | MIT | |
| Looperksimback/looper | 710 | — | ~2.7k | Automated safety check: Notes | MIT |
Similar skills
Planning With Files
jarrodwatts/claude-code-config
Transforms workflow to use Manus-style persistent markdown files for planning, progress tracking, and knowledge storage.
Codebase Management
giancarloerra/SocratiCode
Set up, index, and manage SocratiCode codebase indexing. An agent skill from giancarloerra/SocratiCode.
Context Compression
guanyang/open-agent-hub
This skill should be used when long-running agent sessions need context compression, structured summarization, compaction, token-per-task optimization, or durable handoff summaries that preserve…
Looper
ksimback/looper
Scaffold a well-designed agent loop with best-practice coaching and a cross-model review council.
Ktx
Kaelio/ktx
Installs and configures ktx, the open-source context layer for data agents — runs ktx setup non-interactively with hidden CLI flags, configures database connections and embeddings, installs agent…
More from LearnPrompt/cc-harness-skills
Dream Memory
LearnPrompt/cc-harness-skills
Consolidate recent logs, sessions, and existing memory files into durable topic memories, normalize dates, prune stale entries, and keep MEMORY.md short enough for prompt use.
Kairos Lite
LearnPrompt/cc-harness-skills
Build a lightweight proactive mode with scheduled checks, sleep intervals, concise user briefs, and expiry safeguards so an agent can work in the background without becoming an uncontrolled daemon.
Structured Context Compressor
LearnPrompt/cc-harness-skills
Compress a long agent conversation into a nine-part continuation summary that preserves request, files, errors, user messages, current work, and the next aligned step.
Swarm Coordinator
LearnPrompt/cc-harness-skills
Coordinate multiple agents by splitting work into research, synthesis, implementation, and verification, assigning ownership, and keeping the coordinator focused on integration rather than raw…
Verification Gate
LearnPrompt/cc-harness-skills
Run a read-only verification pass after implementation to check whether completion claims are real, validation actually ran, and obvious edge cases or regressions were missed.
Related
Categories
Questions about Memory Extractor
What does Memory Extractor do?
Extract durable memories from recent conversation turns into user, feedback, project, and reference categories while avoiding stale code-state facts. Memory Extractor is an agent skill from LearnPrompt/cc-harness-skills. Extract durable memories from recent conversation turns into user, feedback, project, and reference categories while avoiding stale code-state facts.
When should I use Memory Extractor?
Memory Extractor fits situations like: AI & LLM Engineering work in your project.
How do I install Memory Extractor in Claude Code?
Run `npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a claude-code`. Or copy the skill folder (skills/memory-extractor in LearnPrompt/cc-harness-skills) into .claude/skills/memory-extractor in your project. Claude Code loads it when a task matches its description.
How do I install Memory Extractor in Codex?
Run `npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a codex`. Or copy the skill folder (skills/memory-extractor in LearnPrompt/cc-harness-skills) into .agents/skills/memory-extractor in your project. Codex loads it when a task matches its description.
Can I use Memory Extractor in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LearnPrompt/cc-harness-skills --skill memory-extractor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memory-extractor, .gemini/skills/memory-extractor, .github/skills/memory-extractor and .opencode/skills/memory-extractor in your project.
What does Memory Extractor need to run?
Going by SKILL.md and its folder, Memory Extractor needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Memory Extractor access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Memory Extractor safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Memory Extractor use?
Memory Extractor is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Memory Extractor use?
About 347 tokens (SKILL.md is roughly 1.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 331 tokens, read only when the agent opens those files.
What are the alternatives to Memory Extractor?
Skills that share tags, products or a category with Memory Extractor: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Planning With Files (jarrodwatts/claude-code-config, 1.1k stars), Codebase Management (giancarloerra/SocratiCode, 3.3k stars) and Context Compression (guanyang/open-agent-hub, 975 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Memory Extractor?
LearnPrompt (a GitHub user) maintains it in LearnPrompt/cc-harness-skills, which has 236 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on July 10, 2026.
Source: LearnPrompt/cc-harness-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.