research-report

Solid

Summarize deep research results into markdown report, cover all fields, skip uncertain values.

Data & Documents 931 stars 86 forks Updated 3 weeks ago MIT

Install

View on GitHub

Quality Score: 91/100

Stars 20%
99
Recency 20%
90
Frontmatter 20%
70
Documentation 15%
100
Issue Health 10%
50
License 10%
100
Description 5%
100

Skill Content

# 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 request_user_input 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"...

Details

Author
Weizhena
Repository
Weizhena/Deep-Research-skills
Created
5 months ago
Last Updated
3 weeks ago
Language
Python
License
MIT

Similar Skills

Semantically similar based on skill content — not just same category

Data & Documents Listed

research-report

Run a deep research dive on any topic and either produce a polished Quarto HTML report (official mode — files written to research/<umbrella>/<title>/) or reply with structured findings inline (scan mode — no files). Use when the user invokes $workbench:research-report, /workbench:research, /workbench:scan, or says "research X for me", "do a deep dive on X", "give me a quick read on X", "what's the state of X", "scan X for me", "write up findings on X". Covers maximum surface area across web, Reddit, GitHub, ProductHunt, docs, papers, and any other available sources. Always converges output to exactly notes.md + report.html (official mode) or a structured chat reply (scan mode). Never proliferates files.

0 Updated 2 days ago
kennykankush
Data & Documents Listed

report-creator

Autonomous intelligence documentarian following the CR (Carlos Ruiz) methodology. Generates complete, indexed, visually-enhanced GitHub-flavored Markdown reports on any security or technology topic, as well as structured CHANGELOG.md files for repositories. Use when the user requests an intelligence report, security analysis, comparative assessment, or a Keep-a-Changelog-style changelog.

0 Updated 5 days ago
carlossruuizz
Data & Documents Listed

deep-research

Generate format-controlled research reports with evidence tracking, citations, and iterative review. This skill should be used when users request a research report, literature review, market or industry analysis, competitive landscape, policy or technical brief, or require a strict report template and section formatting that a single deepresearch pass cannot reliably enforce.

3 Updated today
lyx2022518
Data & Documents Listed

deep-research

Generate format-controlled research reports with evidence tracking, citations, and iterative review. This skill should be used when users request a research report, literature review, market or industry analysis, competitive landscape, policy or technical brief, or require a strict report template and section formatting that a single deepresearch pass cannot reliably enforce.

28 Updated 1 months ago
proyecto26
AI & Automation Listed

research-engine

Autonomous research pipeline — topic to structured documents with HTML/PDF output. Proven at HEL (28 docs, 91K words) and OOPS (9 docs, 20K words) scale.

62 Updated today
Tibsfox