Skills DirectorySkills Directory
SkillsLearnSecurityCategoriesDocsCommunityBlog
Sign InSubmit Skill
Skills Directory

Security-tested agent skills for Claude, coding agents, and AI workflows.

Directory

  • Browse Skills
  • All Skills A–Z
  • Claude Skills
  • Claude Code Skills
  • Agent Skills
  • Categories
  • Submit a Skill

Learn

  • Learn Hub
  • Install Claude Skills
  • Write SKILL.md
  • Skills vs MCP
  • Directories Compared

Security

  • Security
  • Methodology
  • Secure Claude Skills
  • Security Badges

Company

  • About
  • Community
  • Blog
  • API Docs
  • Advertise

2026 Skills Directory. All rights reserved.

Back to skills

Summarization

ASecurity

Comprehensive session wrap-up and continuity checkpointing workflow.

3 stars
0 votes
0 copies
0 views
Added 9/20/2026
ai-agentsgit

Security Analysis

A100/100

Scanned 9/20/2026

Install to Claude Code

$npx -y skills add ruskicoder/system-prompts --skill summarization --agent claude-code

Installs into .claude/skills of the current project.

Are you the author of Summarization?

Add the live security badge to your README — it updates automatically with every re-scan.

Security grade badge for Summarization
[![Security: A — Skills Directory](https://www.skillsdirectory.com/api/skills/ruskicoder-summarization-system-prompts/badge)](https://www.skillsdirectory.com/skills/ruskicoder-summarization-system-prompts)

More formats (shields.io, HTML) on the badges page.

Download Zip
Files
SKILL.md
---
name: summarization
description: Comprehensive session wrap-up and continuity checkpointing workflow.
  Generates a standalone copy-pasteable initialization prompt, captures decisions,
  records current setup status, and lists next steps before session end.
argument-hint: '[session wrap-up prompt]'
---

<!-- Generated from workflows/summarization.md by tools/generate_integrations.py. Edit the source file, not this one. This is an execution WORKFLOW packaged as an Agent Skill so it is discoverable and directly invocable ("/summarization") in every compatible tool. -->

# Workflow: Session Summarization

## When to Use
| Criteria | Match |
|----------|-------|
| Trigger | user requests it OR token budget reaches critical |
| Context | any workflow, any mode — ending a session |
| Power Mode | Critical |
| Priority | HIGH — preserves work across sessions |

## Required Skills
- memory-management
- communication-tone
- codebase-understanding (GitNexus) — for tracking what changed

## Flow

### Step 0: Thinking Stage (Pre-Action)
- [ ] Why am I summarizing? User request, token limit, or session end?
- [ ] Do I have `detect_changes()` data for all modifications this session?
- [ ] What information is CRITICAL for the next session to continue?
- [ ] Prioritize: initialization prompt > decisions > current state > remaining tasks

### Step 1: Detect Trigger
- User says "summarize" / "wrap up" / "continue next session"
- OR token budget is critically low (<10% remaining)
- OR you estimate remaining work will exceed remaining token budget

### Step 2: Gather Current State
- Read todo_write list (current progress)
- Run `detect_changes()` to see all modifications in this session
- Collect key decisions made during the conversation
- Note any unresolved issues or blockers

### Step 3: Summarize Using Standard Prompt

```
We will end our session here. Please output a detailed, exhaustive summary of our entire conversation to prepare for the next session. Include everything we have discussed, what we have agreed on, the current state of the conversation, and the status of the project setup (such as files, infrastructure, or configurations). Provide this as a continuity summary so another session can pick up exactly where we left off. 
Begin your response with a standalone initialization prompt that I can copy and paste into a new session. This initialization prompt must follow this structure: "You are an expert assistant specializing in... You are working on a project involving..., and here is the context of where we left off: [Insert Context Here]."
Additionally, include a specific instruction within that prompt directing the AI to perform a full project scan (covering code, architecture, or configuration files) to fully understand the current setup. Proceed with the output text now. Thank you.
```

### Step 4: Summary Structure
The summary MUST include:

1. **Initialization Prompt** (standalone, ready to copy-paste into a new session)
   - Must strictly follow structure: `"You are an expert assistant specializing in... You are working on a project involving..., and here is the context of where we left off: [Insert Context Here]."`
   - Includes explicit instruction: `"Perform a full project scan (covering code, architecture, or configuration files) to fully understand the current setup before proceeding."`
   
2. **What Was Discussed**
   - Everything discussed, feature/task description
   - Key decisions agreed on
   - Alternatives considered and rejected
   
3. **Current State & Project Setup**
   - Status of project setup (files, infrastructure, configurations)
   - What's working / verified
   - What's still pending / broken
   
4. **What's Left & Next Steps**
   - Remaining tasks from the todo list
   - Known issues or blockers
   - Next steps in priority order

### Step 5: Render Response in Text (DO NOT Output to File)
- Render the complete continuity summary and initialization prompt directly in visible response TEXT.
- DO NOT output the summary to a file (do not write to `.kiro/session-summary.md` or any disk file).
- Never echo or display the instruction prompt string itself in the response.

## Token Budget
- **Summary itself**: 2K-5K tokens (maximize useful context within budget)
- If budget is critically low: output the most essential information first — initialization prompt, current state, next steps — in that priority order

## GitNexus Integration
- `detect_changes()` — critical for tracking what was modified
- `status` — verify index state
- Any index-worthy updates (if significant code changes were made, recommend re-running `npx gitnexus analyze` in next session)

## Hallucination Watchpoints
- Omitting important decisions
- Inaccurate state descriptions
- Forgetting blockers/issues that were encountered
- Summary too brief to be useful for continuation
- Not including the initialization prompt for the next session

Attribution

ruskicoderruskicoder
View sourceMore from ruskicoder →
SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.

Comments (0)

No comments yet. Be the first to comment!

SSkills DirectorySkills Directory

Your tool, in front of Claude Code builders.

3 founder slots · $299/mo · GSC-verified traffic · sponsors can never buy grades.

See placements

Related Skills

Caveman

Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.

1023331 votes

Hyperplan

Adversarial multi-agent planning skill. Self-orchestrates 5 hostile category members (unspecified-low, unspecified-high, deep, ultrabrain, artistry) via team-mode for ruthless cross-critique debate, distills only the defensible insights, then MANDATORILY hands the distilled insight bundle to the `plan` agent for executable plan formalization. Use when planning needs maximum rigor and surfacing of weak assumptions, blind spots, and over-engineering. Triggers: 'hyperplan', 'hpp', '/hyperplan', ...

686011 votes

Mcp Code Execution

Routes multi-tool workflows through MCP servers for large datasets and pipelines. Use when Bash tool overhead is limiting throughput on data-heavy tasks.

3331 votes

catchup

Recovers prior coding-agent session context by running `catchup <agent> --since-compact`, which extracts a clean summary of a previous Codex, Claude Code, Antigravity, OpenCode, or Pi Agent session. Use when the user says "catch up", "what did the last session do", "get me up to speed", "I switched agents", or asks to recover/summarize a previous session before continuing. Do NOT use for the current conversation, git history, or any non-agent log.

611 votes

math-skill

A comprehensive mathematical reasoning skill for AI assistants — handles arithmetic to research-level problems with rigorous step-by-step reasoning, systematic verification, and transparent uncertainty handling

381 votes
View all in ai-agents →