From 40fccbd0cc852d061b13dedaac8a490ce4a03642 Mon Sep 17 00:00:00 2001
From: wdm <wdm@wdmdeMacBook-Air.local>
Date: Mon, 30 Mar 2026 01:06:17 +0800
Subject: [PATCH] Update README: add generate_article_summaries tool and
 single-item format support

---
 README.md | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/README.md b/README.md
index 17ca538..696d317 100644
--- a/README.md
+++ b/README.md
@@ -9,12 +9,13 @@ pip install -e .
 summary-mcp
 ```
 
-The server exposes four tools:
+The server exposes five tools:
 
 - `extract_url_content`
 - `extract_item_content`
 - `filter_summary_result`
 - `run_freshrss_openclaw_pipeline`
+- `generate_article_summaries`
 
 Article-summary post-processing (separate LLM optional):
 
@@ -258,9 +259,11 @@ python scripts/run_article_summaries.py ^
 
 …or through the MCP server tool `generate_article_summaries` exposed by `summary_mcp.server`:
 
-- `extracted_path` (string): path to the extracted JSON, for example `outputs/freshrss/extracted/freshrss.extracted.json`.
-- `selected_ids` (array of strings): one or more `item_id` values from the extracted payload to summarize.
+- `extracted_path` (string): path to a single-item extracted JSON (e.g. `outputs/freshrss/rerun/<run_id>/extracted/item-01.extracted.json`) or a batch extracted JSON containing a `results` array.
+- `selected_ids` (array of strings): one or more `item_id` values to summarize. Pass an empty array to summarize all items in the file.
 - `output_dir` (optional string): directory to write Markdown summaries. If omitted, summaries are written under `single_summaries/` next to the extracted file.
 - `llm_api_key` / `llm_model` / `llm_api_url` (optional strings): overrides for article-summary LLM settings. If omitted, the tool falls back to `ARTICLE_SUMMARY_*` or main `LLM_*` env vars as described above.
 
 The tool returns a JSON array of file paths for the generated Markdown summaries.
+
+The article summary uses a dedicated prompt (`outputs/prompts/article-summary-prompt.txt`) that is completely independent from the daily digest prompt. It outputs a structured knowledge note in Chinese with sections: 核心结论、主要论点、关键方法 / 机制、重要细节、可复用启发、关键词、主题.