ai-tool-research

Researches how people are using an AI tool (Claude Desktop, Cursor, OpenAI Codex, Google Gemini, or OpenClaw) and generates a Productivity Playbook plus a Skills Catalog in a consistent, rated, month-over-month format. Use when the user asks for a monthly research update on one of these tools, a productivity playbook, a skills catalog, a "what's new this month" report on an AI coding/agent tool, or wants to regenerate any of the files named <Tool>-Productivity-Playbook.md or <Tool>-Skills-Catalog.md. Also use if the user wants to run the same research cycle across all five tools.

AI Tool Research Skill

Generates two Markdown artifacts for a given AI tool, updated for the last N days:

1. <Tool>-Productivity-Playbook.md — how real people are using it (personas, use cases, unusual examples, links).
2. <Tool>-Skills-Catalog.md — rated list of skills / extensions / plugins / rules / MCP servers with persona mapping.

The skill is runtime-agnostic. It works in Cursor, Claude Desktop, ChatGPT (web), Codex, Gemini CLI, and OpenClaw. See Usage across runtimes.

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When to invoke

Trigger on requests like:

• "Update the Cursor playbook with what happened this month"
• "Do the same research for Claude / Codex / Gemini / OpenClaw"
• "Run the monthly AI tool research"
• "Rebuild <Tool>-Skills-Catalog.md with fresh ratings"
• "Do all five tools for this month"

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Supported tools

Tool key	What it is	Primary sources
claude	Claude Desktop + Claude Code + Anthropic Skills	anthropic.com, anthropics/skills, obra/superpowers, ComposioHQ
cursor	Cursor AI IDE + Rules / Skills / Plugins	cursor.com, cursor.directory, awesome-cursorrules
codex	OpenAI Codex (CLI + IDE + App + Cloud)	openai.com/codex, openai/skills, openai/codex-plugins
gemini	Google Gemini app + Gemini CLI + Code Assist + NotebookLM + Gems	ai.google.dev, gemini-cli-extensions, Piebald-AI/awesome-gemini-cli-extensions
openclaw	Peter Steinberger's OpenClaw local AI agent	openclaw.ai, openclaw/clawhub, VoltAgent/awesome-openclaw-skills

All five honor the agentskills.io open SKILL.md standard, so skills from one ecosystem often work in another — this is called out in every catalog.

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Inputs

Gather these before starting:

Input	Required?	Default
tool	yes	ask the user: one of claude / cursor / codex / gemini / openclaw / all
since_date	no	30 days before today (monthly cadence)
output_dir	no	current working directory
existing_file_mode	no	rewrite (default) or append-appendix (preserves body, adds "Updates since YYYY-MM-DD" appendix)

If tool = all, loop through the five tools and produce ten files total.

Always print today's date and the since_date used at the top of every generated file so the user can verify the time window later.

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High-level workflow

Copy this checklist into the conversation and track progress:

text

Research Progress:
- [ ] 1. Confirm inputs (tool, since_date, output_dir, mode)
- [ ] 2. Check existing files — if present, read them to avoid regressions
- [ ] 3. Research phase — search primary sources with since_date filter
- [ ] 4. Rating phase — apply validity + usefulness rubric to every item
- [ ] 5. Compose Productivity Playbook using playbook-template.md
- [ ] 6. Compose Skills Catalog using catalog-template.md
- [ ] 7. Verify link integrity + date stamps
- [ ] 8. Write files
- [ ] 9. Append run log entry

Do not skip any step. Step 2 is important — if the files already exist, you must read them so your update reflects genuine "what's new" signal, not repeated evergreen content.

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Step 1 — Confirm inputs

If a tool isn't specified, ask with a quick multi-choice question. Example:

Which tool should I research this month?

1. Claude Desktop
2. Cursor
3. OpenAI Codex
4. Google Gemini
5. OpenClaw
6. All five

Default since_date = today - 30 days. If the user already ran this skill recently, prefer since_date = last_run_date from the run log (see Step 9).

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Step 2 — Check existing files

Check for these files in output_dir:

• <Tool>-Productivity-Playbook.md
• <Tool>-Skills-Catalog.md
• research-log.md (created by Step 9)

If any exist:

• Read them. Note the existing structure, tone, and skill ratings.
• Preserve link references that are still valid.
• In the new file, explicitly list what changed since the last run in a "Changes since <last_run_date>" section near the top.
• If existing_file_mode = append-appendix, do NOT rewrite the body. Add a new appendix called Updates — <YYYY-MM-DD> at the end with only the deltas.

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Step 3 — Research phase

Source categories to cover (in order of trust)

1. Official — the tool vendor's own docs, blog, changelog, release notes
2. Official GitHub orgs — e.g., anthropics/, openai/, getcursor/, google-gemini/, openclaw/
3. Curated "awesome" lists — usually the fastest signal for new skills / rules / plugins
4. Community marketplaces — ClawHub, cursor.directory, Composio, geminicli.com/extensions
5. X.com / Twitter — search <tool> since:YYYY-MM-DD for fresh real-user workflows
6. Dev blogs — dev.to, Medium, Substack, HackerNoon, Pragmatic Engineer, The New Stack
7. Reddit — r/ClaudeAI, r/cursor, r/ChatGPTCoding, r/Bard
8. YouTube — transcripts of creator tutorials (last 30 days)

For the exact search-query library per tool, read research-queries.md.

Time filter

Apply date filtering to every search:

• Google / Web: after:<since_date> (e.g., after:2026-03-21)
• X.com: since:<since_date>
• GitHub: filter by pushed:>=<since_date> on repo search; for issues/PRs use updated:>=<since_date>

What to collect per item

For every skill / rule / plugin / use case you plan to include, capture:

• Canonical name and author/org
• Canonical URL (prefer the GitHub repo or the vendor's doc page — not a random blog)
• One-sentence "what it does" description
• Last-update date (for validity rating)
• Install count / stars / endorsements if available
• Persona fit (from personas.md)

Minimum coverage bar

A single-tool run should surface:

• ≥ 10 new or updated skills / rules / plugins since since_date
• ≥ 6 new real-world use-case stories (X threads, case studies, blog posts)
• ≥ 1 officially announced product/feature change (release notes / changelog)
• ≥ 3 community discussions (Reddit / HN / Discord)

If you can't hit this bar, state so explicitly in the final file and lower the confidence claims.

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Step 4 — Rating phase

Apply the rating system from rating-system.md to every skill / rule / plugin entry.

Quick version (details in the reference file):

Validity = is it real + maintained?

• ✅ Verified — Official, OR GitHub push in last ~90 days AND ⭐ > 500 or installs > 1k
• 🟢 Likely-valid — confirmed repo, moderate traction, recent activity
• 🟡 Early / Niche — real but new, low traction
• 🔴 Unverified — mentioned but canonical source couldn't be confirmed

Usefulness = editorial 1–5 stars based on breadth, docs, persona fit, time-to-value.

• ★★★★★ must-install
• ★★★★ weekly use
• ★★★ niche but excellent
• ★★ narrow fit
• ★ experimental / novelty

Be honest. If something is hyped but you couldn't confirm maintenance, rate it 🔴 and say so. Do not give sympathy stars.

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Step 5 — Compose the Productivity Playbook

Use the exact section structure in playbook-template.md. Do not renumber or rename sections — this is what makes month-over-month diffs useful.

Personas: always cover all eight from personas.md in the same order (PhD/research, solopreneur, marketer, designer, video/creator, developer, PKM/student, sales/finance/ops). If a persona has nothing meaningful for this tool, write one honest paragraph explaining why and move on.

Tone rules:

• Third person, not "you can…"
• Concrete verbs, no marketing fluff
• Every claim cites a link
• No emojis (except ratings badges)
• Prefer tables over prose for comparisons

Length: 300–600 lines is the healthy range. Longer than 700 = you're padding.

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Step 6 — Compose the Skills Catalog

Use the exact section structure in catalog-template.md.

Mandatory sections (skipping any breaks month-over-month consistency):

1. Primer — what are the tool's extensibility primitives
2. Install commands — copy-pasteable
3. Rating legend (link to or copy from rating-system.md)
4. Built-in / official foundation skills
5. Marketplaces / meta-collections
6. Skills by persona (all eight)
7. Cross-tool skills (agentskills.io-compatible, works in ≥ 2 ecosystems)
8. Starter kits (one per persona, copy-paste-able)
9. How to create your own skill — minimum viable SKILL.md
10. Safety / vetting protocol
11. Tier-1 must-installs (5–8 items)
12. Cross-catalog navigation (links to sibling catalogs)
13. Master source index

Ratings appendix at the end is encouraged but not required if ratings are already inline.

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Step 7 — Verify

Before writing files, run these checks:

• Every skill has a name + URL + one-line description + both ratings
• Every URL resolves (when a WebFetch-type tool is available, sample-test a handful)
• Last updated: line exists near the top of each file
• since_date and today_date are both printed
• Sibling catalog links use correct relative paths (./Claude-Skills-Catalog.md, etc.)
• No invented repo URLs or fake GitHub orgs
• Persona order matches personas.md
• Rating badges render correctly in Markdown (no broken emojis)

If any check fails, fix before proceeding to Step 8.

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Step 8 — Write files

Write to <output_dir>/<Tool>-Productivity-Playbook.md and <output_dir>/<Tool>-Skills-Catalog.md.

File-naming rules:

• <Tool> capitalization: Claude, Cursor, Codex, Gemini, OpenClaw
• For Claude specifically, the playbook is historically Claude-Desktop-Productivity-Playbook.md (note the "Desktop"). Preserve that exact name when updating — the skill catalog drops "Desktop" and is just Claude-Skills-Catalog.md.

If existing_file_mode = append-appendix, append to the existing files instead of overwriting.

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Step 9 — Append run log

Append a row to <output_dir>/research-log.md (create it if missing):

markdown

# AI Tool Research — Run Log

| Date run | Tool | since_date | Mode | New skills found | New use cases | Notable changes |
|---|---|---|---|---|---|---|
| 2026-04-21 | cursor | 2026-03-21 | rewrite | 14 | 9 | Composer 2 GA; 3 new MCP servers |

This is the source of truth for "when did I last run this" on future invocations.

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Output contract (what the user sees in chat)

When finished, reply with:

1. One-line summary: "Generated <Tool>-Productivity-Playbook.md (N lines) and <Tool>-Skills-Catalog.md (M lines), covering <since_date> → ."
2. Top 5 what's-new bullets — what the user should actually care about this month.
3. Any sources where you hit rate-limits or had to downgrade confidence.
4. Run-log row that was appended.

Do NOT dump the full file contents into chat. The file exists — let the user open it.

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Usage across runtimes

Cursor

1. Put this whole folder in .cursor/skills/ai-tool-research/ (project-local) or ~/.cursor/skills/ai-tool-research/ (personal).
2. Ensure Skills are enabled in Cursor settings.
3. Ask: "Run the AI tool research skill for Cursor this month."

Claude Desktop / Claude Code

1. Put this folder in ~/.claude/skills/ai-tool-research/ (or the Anthropic Skills path on your OS).
2. In Claude Desktop, enable the skill under Settings → Skills.
3. Ask: "Use the ai-tool-research skill to update the Codex playbook."

ChatGPT (web — no file system)

1. Start a new conversation.
2. Paste this SKILL.md as the first message, preceded by: You are an agent following this skill definition. Apply it to my next request.
3. Also paste the five supporting files (playbook-template.md, catalog-template.md, personas.md, rating-system.md, research-queries.md) in subsequent turns — ChatGPT will keep them in context.
4. Then say: "Run it for Gemini this month."
5. ChatGPT will return the two Markdown files as assistant messages; copy them into .md files locally.

Gemini CLI

1. Put this folder in ~/.gemini/skills/ai-tool-research/ (or whichever Skills path your Gemini CLI is configured with — see GEMINI.md).
2. Ask: "Use ai-tool-research to update the OpenClaw skills catalog."

OpenAI Codex (CLI / IDE / Cloud)

1. Put this folder in ~/.codex/skills/ai-tool-research/.
2. Reference in AGENTS.md if you want it auto-loaded per project.
3. Ask: "Run ai-tool-research for Claude this month."

OpenClaw

1. Put this folder in ~/.openclaw/workspace/skills/ai-tool-research/.
2. Restart the gateway if needed.
3. Message the agent (on WhatsApp / Telegram / Slack): "Run the ai-tool-research skill for all five tools and DM me a summary."

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Reference files (read only when needed — progressive disclosure)

• playbook-template.md — exact section structure + tone guide for the Productivity Playbook
• catalog-template.md — exact section structure for the Skills Catalog
• personas.md — the 8 consistent personas, use-case angles, and what "good coverage" looks like per persona
• rating-system.md — the full validity + usefulness rubric with decision flowcharts
• research-queries.md — reusable search-query templates per tool, per source type

Read these only when the step requires it — they're progressive disclosure to keep this top-level SKILL.md lean.

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Examples of past output

If available, the user's own previous files in output_dir are the best examples:

• Claude-Desktop-Productivity-Playbook.md + Claude-Skills-Catalog.md
• Cursor-Productivity-Playbook.md + Cursor-Skills-Catalog.md
• Codex-Productivity-Playbook.md + Codex-Skills-Catalog.md
• Gemini-Productivity-Playbook.md + Gemini-Skills-Catalog.md
• OpenClaw-Productivity-Playbook.md + OpenClaw-Skills-Catalog.md

Match their voice, section numbering, and level of detail. If the user's versions differ from the templates in this skill, prefer the user's version — their file is the source of truth for their stylistic preferences.

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Anti-patterns to avoid

• ❌ Inventing repos or URLs. If you can't confirm it, rate 🔴 or drop it.
• ❌ Copying the previous month's file and changing the date. Always verify what actually changed.
• ❌ Giving five stars to everything. The rating system is useless if everything is ★★★★★.
• ❌ Marketing-speak ("revolutionary", "game-changing", "unlock"). Use concrete verbs.
• ❌ Long prose where a table would communicate faster.
• ❌ Skipping persona sections because "nothing new this month" — write one honest paragraph instead.
• ❌ Mentioning the skill file internals to the user. They just want the output files.

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This skill is intentionally portable — no hard-coded paths, no runtime-specific features. It works because Claude, Cursor, Codex, Gemini, and OpenClaw all honor the agentskills.io open spec.