questionnaire

A guided question tool that collects several related choices in one dialog, such as scope, priorities, or settings.

In plain words
What is it for?
Use it when work depends on multiple choices from a known set, or when the user asks for a menu, form, or dialog.
Why use it?
It avoids long back-and-forth lists of free-text questions and returns selected answers in a consistent form.

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/firstp1ck/pi-coding-agent-forge/questionnaire
Any agent
npx skills add Firstp1ck/pi-coding-agent-forge --skill questionnaire
Clone the repo
git clone --depth 1 https://github.com/Firstp1ck/pi-coding-agent-forge

Made for: Claude Code, Codex.

Per session 110 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,600 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 $0.00110 $0.01600
Opus 5 $0.00055 $0.00800
Sonnet 5 $0.00022 $0.00320
Haiku 4.5 $0.00011 $0.00160

Measured 2d ago against content hash 797aa14ad280, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

questionnaire 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 2d 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.

pi-package-questionnaire/skills/questionnaire/SKILL.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Questionnaire

Ask related structured questions in one native dialog flow and read the answers back as stable IDs.

The questionnaire tool runs Pi's native selector and text-input dialogs sequentially. It works in the TUI (Up/Down + Enter) and in the WebUI (options are ordinary clickable buttons).

When to use

Use questionnaire when:

  • two or more related choices must be settled before work can continue;
  • the choices have a known, bounded option set you can name;
  • the user asked to be prompted with a menu, list, form, or dialog;
  • a prior questionnaire result returned QUESTIONNAIRE_NEEDS_CLARIFICATION.

Do not use questionnaire when:

  • the question is genuinely open-ended and better answered in prose;
  • one trivial confirmation is enough — just ask in normal text;
  • you are requesting secrets, passwords, tokens, or other credentials;
  • you already have the answer in context, or can determine it by reading files or running a read-only command.

Never invent a questionnaire to look thorough. Ask only what actually changes what you will do.

Question design rules

  1. Combine. Put every related question into one start call. Do not run several sequential questionnaires for one decision.
  2. Stable IDs. Give each question and option a stable, descriptive, non-empty id (deploy_target, target_staging). IDs are what you read back; labels are only display text.
  3. Unique IDs. Question IDs must be unique in the call; option IDs must be unique within their question.
  4. Concise text. Short label, one clear prompt sentence, and an optional short description per option only when the label is not self-explanatory.
  5. Honest types. Use single when exactly one answer is valid, multi when several are. Do not fake multi-select with several single questions.
  6. Realistic bounds. A multi question defaults to minSelections: 0; set minSelections: 1 whenever an empty answer is not useful. Set maxSelections only when the task needs a ceiling. Selection bounds are rejected on single questions.
  7. Other. allowOther defaults to true. Set it to false when a custom answer is meaningless or unusable.
  8. Bounded size. 1–20 questions, 1–50 options per question, IDs ≤128 chars, labels ≤200, prompts ≤2000, option descriptions ≤500.

Read the full file on GitHub · 133 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. 2d ago First seen · 133 lines · 110 tokens per session scan A 797aa14ad280

Subscribe to this mod's changes

questionnaire is a skill published in the GitHub repository Firstp1ck/pi-coding-agent-forge (74 stars, last pushed 2d ago), licensed MIT. It adds 110 tokens to every session and 1,600 once invoked, about $0.0006 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 2026-08-30.