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 Jamie-BitFlight/claude_skills --skill workshop-question-framinggit clone --depth 1 https://github.com/Jamie-BitFlight/claude_skillsWrote 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/jamie-bitflight/claude_skills/workshop-question-framing)<a href="https://agentmods.dev/skills/jamie-bitflight/claude_skills/workshop-question-framing"><img src="https://agentmods.dev/badge/skills/jamie-bitflight/claude_skills/workshop-question-framing/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/jamie-bitflight/claude_skills/workshop-question-framing"><img src="https://agentmods.dev/badge/skills/jamie-bitflight/claude_skills/workshop-question-framing.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high System Prompt Leakage · line 315 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
- high System Prompt Leakage · line 326 Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.Fix: Remove any instructions that reveal, print, or output system prompts or internal rules. System instructions should never be exposed to end users.
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 | $0.00076 | $0.02595 |
| Opus 5 | $0.00038 | $0.01298 |
| Sonnet 5 | $0.00015 | $0.00519 |
| Haiku 4.5 | $0.00008 | $0.00260 |
Grade A, and why
workshop-question-framing 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 9d 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 — 357 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Workshop Question Framing Skill
Purpose
Turn a workshop topic and explanation into a set of questions that make participants think before they are taught.
The goal is not to create generic discussion questions. The goal is to create a felt need to understand.
Use this skill to help the user open a topic with curiosity, cognitive tension, relevance, and participant commitment before explanation arrives.
Core Principle
Do not start with the explanation.
Start by designing the moment thinking begins.
The explanation should arrive after the participant has already:
- Noticed a gap
- Formed a theory, prediction, position, or question
- Put some thinking on the line
- Felt a reason to care about the explanation
Required Input
The user may provide any of the following:
- Workshop topic
- Workshop title
- Learning objective
- Explanation or teaching notes
- Audience
- Duration
- Desired outcome
- Existing opening activity
- Slides, outline, or agenda
The one thing required is enough material to identify a core concept. That can come from any input above: a topic, title, learning objective, explanation or teaching notes, slides, outline, or an existing opening activity. Extract the teaching core from whatever the user supplies — a review or improvement request that provides only teaching notes or an objective is enough to proceed. Ask a follow-up only when nothing provided is sufficient to identify a core concept. For any other missing input (audience, duration, desired outcome), do not stall: infer a reasonable value and label it as an assumption.
Method
Step 1: Extract the Teaching Core
From the user's topic and explanation, identify:
- The audience, and their level or context (if not given, assume one and label it as an assumption)
- The core concept
- The thing participants usually misunderstand
- The belief, habit, assumption, or mental model the workshop is trying to change
- The decision, behavior, or capability participants should leave with
- The explanation that should not arrive too early
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 357 lines · 76 tokens per session scan A 9290748eba5d
workshop-question-framing is a skill published in the GitHub repository Jamie-BitFlight/claude_skills (66 stars, last pushed yesterday), licensed MIT. It adds 76 tokens to every session and 2,595 once invoked, about $0.0004 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.
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