What is code-refactoring-context-restore?

A guide for restoring lost project context in workflows where multiple AI agents or sessions handle the same work.

Use it to clarify goals and inputs, rebuild relevant context, and check that the restored understanding is accurate.

It helps recover important project knowledge when work is interrupted, handed off, or spread across separate conversations.

code-refactoring-context-restore — Skill for Claude Code and Codex by

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent

npx skills add Bilal140202/the-lord-of-the-skills --skill sickn33__antigravity-awesome-skills

Clone the repo

git clone --depth 1 https://github.com/Bilal140202/the-lord-of-the-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/sickn33__antigravity-awesome-skills/github.svg)](https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/sickn33__antigravity-awesome-skills)

Your own site

<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/sickn33__antigravity-awesome-skills"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/sickn33__antigravity-awesome-skills/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/bilal140202/the-lord-of-the-skills/sickn33__antigravity-awesome-skills"><img src="https://agentmods.dev/badge/skills/bilal140202/the-lord-of-the-skills/sickn33__antigravity-awesome-skills.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 16 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,252 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin 91% copy Near-identical to another mod in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00016	$0.01252
Opus 5	$0.00008	$0.00626
Sonnet 5	$0.00003	$0.00250
Haiku 4.5	$0.00002	$0.00125

Measured 12d ago against content hash f868e17e5163, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

code-refactoring-context-restore scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

91% identical to code-refactoring-context-restore — 9 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/fangorn/claude-code/sickn33__antigravity-awesome-skills/SKILL.md · 188 lines

How it starts

The opening of the file, as written. The whole thing — 188 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Context Restoration: Advanced Semantic Memory Rehydration

Use this skill when

Working on context restoration: advanced semantic memory rehydration tasks or workflows
Needing guidance, best practices, or checklists for context restoration: advanced semantic memory rehydration

Do not use this skill when

The task is unrelated to context restoration: advanced semantic memory rehydration
You need a different domain or tool outside this scope

Instructions

Clarify goals, constraints, and required inputs.
Apply relevant best practices and validate outcomes.
Provide actionable steps and verification.
If detailed examples are required, open resources/implementation-playbook.md.

Role Statement

Expert Context Restoration Specialist focused on intelligent, semantic-aware context retrieval and reconstruction across complex multi-agent AI workflows. Specializes in preserving and reconstructing project knowledge with high fidelity and minimal information loss.

Context Overview

The Context Restoration tool is a sophisticated memory management system designed to:

Recover and reconstruct project context across distributed AI workflows
Enable seamless continuity in complex, long-running projects
Provide intelligent, semantically-aware context rehydration
Maintain historical knowledge integrity and decision traceability

Core Requirements and Arguments

Input Parameters

context_source: Primary context storage location (vector database, file system)
project_identifier: Unique project namespace
restoration_mode:
- full: Complete context restoration
- incremental: Partial context update
- diff: Compare and merge context versions
token_budget: Maximum context tokens to restore (default: 8192)
relevance_threshold: Semantic similarity cutoff for context components (default: 0.75)

Advanced Context Retrieval Strategies

1. Semantic Vector Search

Utilize multi-dimensional embedding models for context retrieval
Employ cosine similarity and vector clustering techniques
Support multi-modal embedding (text, code, architectural diagrams)

Read the full file on GitHub · 188 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

12d ago First seen · 188 lines · 16 tokens per session scan A f868e17e5163

Subscribe to this mod's changes

code-refactoring-context-restore is a skill published in the GitHub repository Bilal140202/the-lord-of-the-skills (4 stars, last pushed 6d ago), licensed MIT. It adds 16 tokens to every session and 1,252 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to code-refactoring-context-restore, differing in 9 lines, and is treated as a copy.

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