conversation-summary

Generate summaries for conversation content with incremental update support.

7 stars

Best use case

conversation-summary is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Generate summaries for conversation content with incremental update support.

Teams using conversation-summary should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/skills-ai-assistant/SKILL.md --create-dirs "https://raw.githubusercontent.com/Demerzels-lab/elsamultiskillagent/main/public/skills/dadaliu0121/skills-ai-assistant/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/skills-ai-assistant/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How conversation-summary Compares

Feature / Agentconversation-summaryStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Generate summaries for conversation content with incremental update support.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Conversation Summary - Agent Instructions

Use this skill to generate summaries for conversation content.

## Usage

When the user requests any of the following:
- "Summarize this conversation"
- "Generate a summary"
- "What did we talk about"

Use the `summarize_conversation` tool to call the summary API.

## How to Call

```bash
python3 scripts/conversation_summary.py '<chat_list_json>' '<history_summary>'
```

### Parameters

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| chat_list | string | Yes | JSON formatted conversation content |
| history_summary | string | No | Previous summary for incremental update |

### chat_list Format Example

```json
[
  {"role": "user", "content": "How is the weather today?"},
  {"role": "assistant", "content": "It is sunny, 25 degrees."}
]
```

## Response

The script returns JSON with:
- `status`: "completed" or "error"
- `summary`: Generated conversation summary
- `error`: Error message if failed

## Error Handling

- If the API returns a non-zero code, report the error message to the user
- If the request fails, check network connectivity
- Ensure chat_list is valid JSON format before calling

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