q-which-tools

q-which-tools is a skill for Claude Code, Codex from jlong/quiddity. It costs 41 tokens per session (1,225 once invoked), scanned A, original, MIT.

A guided interview that records which development tools a project uses in .quiddity/tools.json, such as issue trackers, source control, continuous integration, and deployment services.

In plain words
What is it for?
Use it to configure selected tool categories and use the project's process document to fill in known details.
Why use it?
It creates one documented place for project tool choices instead of relying on scattered knowledge or repeated questions.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/jlong/quiddity/q-which-tools
Any agent
npx skills add jlong/quiddity --skill q-which-tools
Clone the repo
git clone --depth 1 https://github.com/jlong/quiddity

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for q-which-tools

README.md
[![agentmods](https://agentmods.dev/badge/skills/jlong/quiddity/q-which-tools.svg)](https://agentmods.dev/skills/jlong/quiddity/q-which-tools)
Your own site
<a href="https://agentmods.dev/skills/jlong/quiddity/q-which-tools"><img src="https://agentmods.dev/badge/skills/jlong/quiddity/q-which-tools.svg" alt="Measured on agentmods" height="20"></a>
Per session 41 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,225 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00041 $0.01225
Opus 5 $0.00020 $0.00613
Sonnet 5 $0.00008 $0.00245
Haiku 4.5 $0.00004 $0.00122

Measured 4d ago against content hash 7cfc2e4bc85b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

q-which-tools scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/q-which-tools/SKILL.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/q-which-tools

You are interviewing the user about the tools their project uses. Your job is to ask about each requested category and write the results to .quiddity/tools.json.

Arguments

$ARGUMENTS contains space-separated category names. Supported categories:

  • issues — Issue/task tracker (Linear, GitHub Issues, Jira, etc.)
  • source-control — Source control host (GitHub, GitLab, Bitbucket, etc.)
  • ci — Continuous integration (GitHub Actions, CircleCI, etc.)
  • pr — Pull request conventions (merge strategy, review requirements, etc.)
  • deploy — Deployment target (Vercel, AWS, Fly, manual, etc.)
  • notifications — Notification channels (Slack, Discord, email, etc.)

If no arguments are provided, ask the user which categories they'd like to configure.

Process

  1. Read process context. Check if .quiddity/process.md exists. If it does, read it to understand the user's SDLC. Use this context to inform your questions and pre-fill answers where possible (e.g., if the process doc mentions "we use GitHub flow", you already know the source-control platform).

  2. Read existing config. Check if .quiddity/tools.json exists. If it does, read it and note which categories are already configured.

  3. For each requested category:

    • If the category already exists in tools.json, tell the user it's already configured and show the current value. Ask if they want to reconfigure it. If not, skip it.
    • If the category is new, ask the user what tool they use.
    • Ask follow-up questions specific to the tool they selected. See the category reference below for what to ask.
  4. Write the results. Merge the new category data into .quiddity/tools.json. Create the .quiddity/ directory if it doesn't exist. Preserve any existing categories that weren't reconfigured.

Category reference

issues

Ask:

  • Which issue tracker? (Linear, GitHub Issues, Jira, Shortcut, etc.)
  • Team or project name?
  • What states/statuses do issues move through? (e.g., Todo → In Progress → Done)
  • How is priority represented? (priority field, labels, columns, etc.)
  • Any label conventions?

Read the full file on GitHub · 174 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 174 lines · 41 tokens per session scan A 7cfc2e4bc85b

Subscribe to this mod's changes

q-which-tools is a skill published in the GitHub repository jlong/quiddity (5 stars, last pushed 6mo ago), licensed MIT. It adds 41 tokens to every session and 1,225 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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