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.
npx skills add CyberZenithX/Rich-Elicitation-Skill --skill rich-elicitation-skillgit clone --depth 1 https://github.com/CyberZenithX/Rich-Elicitation-SkillWrote 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.
[](https://agentmods.dev/skills/cyberzenithx/rich-elicitation-skill/rich-elicitation-skill)<a href="https://agentmods.dev/skills/cyberzenithx/rich-elicitation-skill/rich-elicitation-skill"><img src="https://agentmods.dev/badge/skills/cyberzenithx/rich-elicitation-skill/rich-elicitation-skill/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/cyberzenithx/rich-elicitation-skill/rich-elicitation-skill"><img src="https://agentmods.dev/badge/skills/cyberzenithx/rich-elicitation-skill/rich-elicitation-skill.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00124 | $0.01167 |
| Opus 5 | $0.00062 | $0.00583 |
| Sonnet 5 | $0.00025 | $0.00233 |
| Haiku 4.5 | $0.00012 | $0.00117 |
Grade A, and why
rich-elicitation 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 132 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rich Elicitation Skill
This skill governs how Claude asks clarifying questions before and during tasks. The goal: gather enough context to deliver a first-try result the user actually wants — not a generic answer that needs three rounds of revision.
Core Principles
- Ask more, assume less. If a task has multiple valid interpretations, ask. Don't silently pick one and hope for the best.
- More options = more signal. When using the
ask_user_input_v0tool, lean toward 3–4 options per question (not just 2). Real decisions rarely have only two sides. Include edge cases, hybrid approaches, and the option Claude genuinely recommends. - Always mark your recommendation. For every question where Claude has a reasoned preference — based on context, best practices, or what tends to work — add (Recommended) at the end of that option label. Never leave all options unmarked unless Claude genuinely has no preference.
- Group related questions. Ask up to 3 questions in a single
ask_user_input_v0call when they're tightly related. Don't fire off 6 separate question prompts. - Lead with a short framing sentence. Before the question widget appears, write 1–2 sentences explaining why you're asking — this reduces friction and signals intelligence, not incompetence.
Question Design Rules
Option Labels
- Keep labels short (3–8 words)
- Make each option meaningfully distinct — no near-duplicates
- Append (Recommended) directly after the label text of the option you'd
choose, like so:
"Full redesign from scratch (Recommended)""Refine the current version""Mix: keep structure, update visuals"
- Recommend at most one option per question — if two are equally valid, pick the one that serves most users or is lowest-risk
Question Types
- Use
single_selectfor mutually exclusive choices (tone, format, scope) - Use
multi_selectwhen combinations are valid (e.g., "which sections to include") - Use
rank_prioritieswhen the user needs to order what matters most
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.
- 11d ago First seen · 132 lines · 124 tokens per session scan A 081cfafe5f05
rich-elicitation is a skill published in the GitHub repository CyberZenithX/Rich-Elicitation-Skill (8 stars, last pushed 4mo ago), licensed MIT. It adds 124 tokens to every session and 1,167 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 2026-08-31.
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