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 isvlasov/rageatc-oss --skill understanding-the-askgit clone --depth 1 https://github.com/isvlasov/rageatc-ossWrote 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/isvlasov/rageatc-oss/understanding-the-ask)<a href="https://agentmods.dev/skills/isvlasov/rageatc-oss/understanding-the-ask"><img src="https://agentmods.dev/badge/skills/isvlasov/rageatc-oss/understanding-the-ask/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/isvlasov/rageatc-oss/understanding-the-ask"><img src="https://agentmods.dev/badge/skills/isvlasov/rageatc-oss/understanding-the-ask.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 | $0.00035 | $0.00761 |
| Opus 5 | $0.00017 | $0.00380 |
| Sonnet 5 | $0.00007 | $0.00152 |
| Haiku 4.5 | $0.00003 | $0.00076 |
Grade A, and why
understanding-the-ask 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 12d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Understanding the Ask
Discover what the user actually needs before requirements are formalised. Users often state solutions, not problems — explore intent, context, and constraints until the underlying need is clear, then hand off to creating-briefs.
Skip the full workflow when the request is already specific with stated outcomes, or the task is trivial with obvious intent.
Workflow
Step 1 — Capture the initial statement
Establish the surface request and basic context with open-ended questions:
- "What are you looking to create or achieve?"
- "Who will use this?"
- "Where does this fit in your current work?"
Capture what they think they need — don't probe why yet. Prefer "what" and "how" openers; "why" can feel defensive.
Step 2 — Explore intent and motivation
Don't literally ask "why" five times; invite elaboration:
- "What's driving this need right now?"
- "What would having this enable you to do?"
- "What happens if we don't address this?"
When the user proposes a specific solution, probe for the outcome behind it: "I need a comprehensive API reference" → "What would that reference enable your team to do?"
Premature-solutioning signals: specific tools before the problem is defined; fixation on a deliverable type; "we need X" without "because Y"; features before outcomes. Redirect: "Before we discuss how, can we clarify what problem that solves?" Some solution talk is fine — just make sure problem context exists first.
Stop when you reach fundamental goals or constraints (typically 3–5 exchanges): the user articulates a clear outcome, you understand the consequence of not solving it, and the need — not just the proposed solution — is clear.
Step 3 — State your understanding
Reflect back at key moments — after exploring intent, before brief creation, when uncertain about something specific — not after every statement:
"Let me state back what I understand:
- Problem: [what's not working or missing]
- Outcome: [what success looks like]
- Constraints: [limitations, boundaries, must-haves]
- Audience: [who will use this]
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.
- 12d ago First seen · 71 lines · 35 tokens per session scan A cbfaea16b576
understanding-the-ask is a skill published in the GitHub repository isvlasov/rageatc-oss (9 stars, last pushed 1mo ago), licensed MIT. It adds 35 tokens to every session and 761 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.
Other skills, from other repositories
design-method
Use when starting any design task — resolves register, sets the 3 dials, locks Gate 0, and routes to the right move and target skill.
design-webapp
Use when building or extending a dashboard, SaaS screen, or any authenticated app surface — use design-web instead for a marketing site.
design-web
Use when building or revising a marketing/landing/campaign page, register brand locked at Gate 0 — use design-webapp for app screens instead.
react-tanstack-router
Use when implementing routing in a React app (NOT Next.js) with TanStack Router — file-based routes, loaders, search params.
git-flow
Use when committing, branching, opening PRs, or deciding merge/branch strategy.
fusecore
Use when creating modules, understanding FuseCore structure, or implementing features in a FuseCore modular-monolith Laravel project.