cli-faq-shortcuts

Stop typing the same long request to your coding agent every day. This Agent Skill reads your own history, finds the asks you keep repeating, and turns each one into a short command, like /sent or /project billing. It works in Claude Code, Codex and Cursor.

The extractor uses only Python's standard library: no packages, API keys, or network access are needed. Intent grouping happens in your coding agent.

Watch or download the 24-second video · What's new in v1.2.0

The demo illustrates the workflow with synthetic data; it is not a live agent recording.

1. Install (macOS / Linux, needs git and Python 3.9+; on Windows see Windows):

git clone https://github.com/kishormorol/cli-faq-shortcuts ~/.agents/skills/faq-shortcuts
mkdir -p ~/.claude/skills && ln -sfn ~/.agents/skills/faq-shortcuts ~/.claude/skills/faq-shortcuts

2. Open your project in Claude Code, Codex or Cursor, in a new session.

3. Ask "what do I keep asking in this project?", or type /faq-shortcuts in Claude Code.

You'll get a table of your most repeated asks with how often you typed each. Pick the ones you want and they become shortcuts in that project.

The repo is cli-faq-shortcuts; the skill it installs is called faq-shortcuts.

If it saves you typing, please ⭐ star the repo. Stars are how other people find it.

# inside your project, in Claude Code
/faq-shortcuts                        # find your repeated asks and propose shortcuts
/faq-shortcuts --since 2026-06-01     # only look at recent history
/faq-shortcuts --source codex         # only what you asked Codex

# the extractor on its own: no agent, nothing leaves your machine
E=~/.agents/skills/faq-shortcuts/scripts/extract_asks.py
python3 "$E" .                       # matching prompts, oldest first
python3 "$E" . --since 2026-09-01 | wc -l               # how many since September
python3 "$E" . --format jsonl         # structured records for your own scripts
python3 "$E" . | awk -F'\t' 'split($3,w," ")>=4 {print tolower($3)}' \
  | sort | uniq -c | sort -rn | head                     # your most repeated exact requests

The last one counts exact repeats only, and it undercounts. On one real project, the most repeated exact request appeared 4 times. Grouped by intent, however it was worded, the top ask had been typed 127 times. That grouping is the agent's job in /faq-shortcuts.

Each shortcut is a small file in your project, .claude/skills/<name>/SKILL.md, for example:

---
name: sent
description: Check whether a batch email actually reached people. Use for "did the
  newsletter go out?", "did it reach everyone?", "did X get the email?".
---
# Did it go out

Report only. Never re-send from this shortcut.

## Query
scripts/email-status.js --batch <name>   ← the script your project already has

## Traps
- A "delivered" status to a shared inbox proves nobody read it (happened 3 May).

## Report
Sent / delivered / bounced counts, then the bounced addresses. Then ask.

The shortcuts point at the scripts and queries your project already uses, and they record the mistakes already made on that path. /sent checks the send record, not the earlier message where the agent said it sent it. So a shortcut is shorter to type, and it verifies the outcome instead of trusting a previous claim. Anything that writes or sends does a dry run first and waits for your yes, so a typo stops at the preview.

1. Collect. scripts/extract_asks.py prints every prompt you typed in the project, from Claude Code and Codex history. It skips subagent turns and scripted runs, because you didn't type those.
2. Cluster. The agent groups prompts by intent, whatever the wording, and counts them.
3. Check. It looks for shortcuts you already have and the tools your project already has.
4. Propose. You get a table of shortcut, the ask it replaces, and how often you asked. You pick.
5. Write. Each chosen shortcut becomes a SKILL.md in .claude/skills/, linked into .agents/skills/ so all three agents load it, committed so your team gets it too.
6. List. A table in CLAUDE.md / AGENTS.md maps each shortcut to the sentence it replaces.

The quick start above is the whole install. It puts the skill where each agent looks:

Update: git -C ~/.agents/skills/faq-shortcuts pull --ff-only, then start a new agent session.

Uninstall: rm ~/.claude/skills/faq-shortcuts && rm -rf ~/.agents/skills/faq-shortcuts

If you only use Claude Code, you can install it as a plugin instead, inside Claude Code:

/plugin marketplace add kishormorol/cli-faq-shortcuts
/plugin install faq-shortcuts@cli-faq-shortcuts

The command is then /faq-shortcuts:faq-shortcuts, or just ask "what do I keep asking in this project?". Codex and Cursor don't read Claude Code plugins, so use the quick start for those.

In PowerShell, with git and Python 3.9+ installed. A directory junction links the skill into ~/.claude/skills and, unlike a symlink, needs no admin rights or Developer Mode:

git clone https://github.com/kishormorol/cli-faq-shortcuts "$env:USERPROFILE\.agents\skills\faq-shortcuts"
New-Item -ItemType Directory -Force "$env:USERPROFILE\.claude\skills" | Out-Null
New-Item -ItemType Junction -Path "$env:USERPROFILE\.claude\skills\faq-shortcuts" -Target "$env:USERPROFILE\.agents\skills\faq-shortcuts"

Run the extractor with python (or py), not python3:

python "$env:USERPROFILE\.agents\skills\faq-shortcuts\scripts\extract_asks.py" . | Select-Object -First 10

Update: git -C "$env:USERPROFILE\.agents\skills\faq-shortcuts" pull --ff-only, then start a new agent session.

Uninstall: remove the junction with rmdir, which leaves its target alone, then the clone:

cmd /c rmdir "$env:USERPROFILE\.claude\skills\faq-shortcuts"
Remove-Item -Recurse -Force "$env:USERPROFILE\.agents\skills\faq-shortcuts"

To see what it finds without the agent:

python3 ~/.agents/skills/faq-shortcuts/scripts/extract_asks.py ~/my-project | head

This prints date<TAB>source<TAB>prompt. Add --source claude, --source codex, or --source cursor to read one tool only, and --since 2026-01-01 to skip older prompts.

python scripts/extract_asks.py [project_dir] [--source all|claude|codex|cursor]
                              [--since YYYY-MM-DD] [--max-len N] [--format tsv|jsonl]

JSONL records have date, source, and prompt fields. Both formats collapse prompt whitespace to single spaces. Dates are YYYY-MM-DD, or an empty string when unavailable; undated records sort first. Counts and diagnostics go to stderr, keeping stdout usable in a pipeline. Exit codes: 0 when a source is available (even if filters match nothing), 1 when no source is available, and 2 for invalid arguments.

• This is a view of the history still stored on your machine, not a complete activity log.
• Prompts longer than 400 characters, injected context, and non-interactive runs are filtered out. Increase --max-len if your usual requests are longer.
• Projects are matched by folder, without recursively including child folders or other worktrees. Moving a project does not move the paths recorded in old history.
• Cursor's storage format is undocumented and can change. Chats without a recorded workspace or repository cannot be attributed to a project.
• Malformed records are skipped. An invalid timestamp becomes an unknown date.

Issues and pull requests are welcome. See CONTRIBUTING.md for local checks and guidance on creating a safe reproduction. Good first contributions:

• History compatibility fixes backed by small synthetic fixtures.
• Install and troubleshooting improvements for the tools and platforms you use.
• A bug report with your OS, Python version, command, and sanitized error message.

Windows installation and extraction are supported and covered by CI, alongside Linux and macOS. See the changelog for unreleased improvements.

Everyone whose pull request is merged appears here:

Built and maintained with help from Claude Code and OpenAI Codex.

The extractor only reads local files and makes no network calls. Your prompts can contain names, emails and tokens, so the skill writes the list to a scratch folder, never into your repo. Your agent then reads that list the same way it reads any file you show it.

That agent may send the prompts to its configured model provider. Review your agent's settings before using sensitive history. Do not attach raw history, extractor output, or Cursor databases to public issues. Use invented prompts in bug reproductions and review generated shortcuts before committing them.

Apache-2.0.