research-report

Files (1)

• SKILL.md

SKILL.md (first lines)

# 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: Scan Optional Summary Fields
Read all JSON results, extract fields suitable for TOC display (numeric, short metrics), e.g.:
- github_stars
- google_scholar_cites
- swe_bench_score
- user_scale
- valuation
- release_date

Use ask_followup_question to ask user:
- Which fields to display in TOC besides item name?
- Provide dynamic options list (based on actual fields in JSON)

### Step 3: 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 + user-selected summary fields) + Detailed content (by field category)
- Save to `{topic}/report.md`

**TOC Format Requirements**:
- Must include every item
- Each item displays: number, name (anchor link), user-selected summary fields
- Example: `1. [GitHub Copilot](#github-copilot) - Stars: 10k | Score: 85%`

#### 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 Mapping**
fields.yaml category names and JSON keys may differ. Read
`~/.roo/skills/research/category_mapping.yaml` to get the category mapping.
Each top-level key is a canonical category name; its value is the list of accepted
aliases used as JSON keys and display names.

**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
- Long text strings (over 100 chars): Add line breaks `<br>` or use blockquote format for readability

**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_features` etc.
- `uncertain` array: Display each field name on separate line, don't compress into one line

**5. Uncertain Value Skipping**
Skip conditions:
- Field value contains `[uncertain]` string
- Field name is in `uncertain` array
- Field value is None or empty string

### Step 4: Execute Script
Run `python {topic}/generate_report.py`

## Output
- `{topic}/generate_report.py` - Conversion script
- `{topic}/report.md` - Summary report

From lkiesow/zoo-deep-research, MIT.

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