- Add validate_json.py for field coverage validation - Add hard constraints and one-shot examples to prompt templates - Add parameter retrieval sections before prompts - Translate all SKILL.md files to English - Update report.md with technical requirements 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2.9 KiB
2.9 KiB
description, allowed-tools
| description | allowed-tools |
|---|---|
| Summarize deep research results into markdown report, cover all fields, skip uncertain values. | Read, Write, Glob, Bash |
Research Report - Summary Report
Trigger
/research-report
Workflow
Step 1: Locate Results Directory
Find */outline.yaml in current working directory, read topic and output_dir config.
Step 2: Generate Python Conversion Script
Generate generate_report.py in {topic}/ directory, script requirements:
- Read all JSON from output_dir
- Read fields.yaml to get field structure
- Cover all field values from each JSON
- Skip fields with values containing [uncertain]
- Skip fields listed in uncertain array
- Generate markdown report format: Table of contents (with anchor links) + Detailed content (by field category)
- Save to
{topic}/report.md
Script Technical Requirements (Must Follow)
1. JSON Structure Compatibility Support two JSON structures:
- Flat structure: Fields directly at top level
{"name": "xxx", "release_date": "xxx"} - Nested structure: Fields in category sub-dict
{"basic_info": {"name": "xxx"}, "technical_features": {...}}
Field lookup order: Top level -> category mapping key -> Traverse all nested dicts
2. Category Multi-language Mapping fields.yaml category names and JSON keys can be any combination (CN-CN, CN-EN, EN-CN, EN-EN). Must establish bidirectional mapping:
CATEGORY_MAPPING = {
"Basic Info": ["basic_info", "Basic Info"],
"Technical Features": ["technical_features", "technical_characteristics", "Technical Features"],
"Performance Metrics": ["performance_metrics", "performance", "Performance Metrics"],
"Milestone Significance": ["milestone_significance", "milestones", "Milestone Significance"],
"Business Info": ["business_info", "commercial_info", "Business Info"],
"Competition & Ecosystem": ["competition_ecosystem", "competition", "Competition & Ecosystem"],
"History": ["history", "History"],
"Market Positioning": ["market_positioning", "market", "Market Positioning"],
}
3. Complex Value Formatting
- list of dicts (e.g., key_events, funding_history): Format each dict as one line, separate kv with
| - Normal list: Short lists joined with comma, long lists displayed with line breaks
- Nested dict: Recursive formatting, display with semicolon or line breaks
4. Extra Fields Collection Collect fields that exist in JSON but not defined in fields.yaml, put in "Other Info" category. Note to filter:
- Internal fields:
_source_file,uncertain - Nested structure top-level keys:
basic_info,technical_featuresetc.
5. Uncertain Value Skipping Skip conditions:
- Field value contains
[uncertain]string - Field name is in
uncertainarray - Field value is None or empty string
Step 3: Execute Script
Run python {topic}/generate_report.py
Output
{topic}/generate_report.py- Conversion script{topic}/report.md- Summary report