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 liqiongyu/lenny_skills_plus --skill problem-definitiongit clone --depth 1 https://github.com/liqiongyu/lenny_skills_plusWrote 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/liqiongyu/lenny_skills_plus/problem-definition)<a href="https://agentmods.dev/skills/liqiongyu/lenny_skills_plus/problem-definition"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/problem-definition/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/liqiongyu/lenny_skills_plus/problem-definition"><img src="https://agentmods.dev/badge/skills/liqiongyu/lenny_skills_plus/problem-definition.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 | $0.00030 | $0.01992 |
| Opus 5 | $0.00015 | $0.00996 |
| Sonnet 5 | $0.00006 | $0.00398 |
| Haiku 4.5 | $0.00003 | $0.00199 |
Grade A, and why
problem-definition 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 — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Problem Definition
Scope
Covers
- Turning a vague idea into a crisp, testable problem definition
- Writing a shareable problem statement (1-liner + expanded)
- Capturing Jobs To Be Done (JTBD) and target segments
- Mapping current alternatives (including non-digital/analog) and “why now / why digital”
- Building an evidence + assumptions log to drive learning
- Defining success metrics + guardrails and clear scope boundaries
When to use
- “Write a problem statement for…”
- “We need to define the problem space / JTBD.”
- “We keep jumping to solutions; help us get clear on the real problem.”
- “Pressure to ‘do AI’ — verify there’s a real pain point first.”
- “Before we write a PRD, align on what problem we’re solving.”
When NOT to use
- You already have an approved problem definition and need a delivery-ready PRD (use
writing-prds) - You need roadmap prioritization across many competing initiatives (use
prioritizing-roadmap) - You need to set company-level strategy/vision (use
defining-product-vision) - You need a competitive landscape analysis as the primary output (use
competitive-analysis); this skill references alternatives only to frame the problem - You’re doing deep research execution (recruiting, interviews, analysis); use this to frame what to learn, not as a substitute for
conducting-user-interviewsordesigning-surveys - You need to analyze existing user feedback data (use
analyzing-user-feedback); this skill frames the problem, not the evidence pipeline
Inputs
Minimum required
- Product/context + target user (or segment hypotheses)
- The triggering signal (customer quotes, data trend, stakeholder request, competitor move)
- The decision to make (e.g., invest now vs later; explore vs stop) + timeline
- Known constraints (tech/legal/privacy/compliance/capacity)
Missing-info strategy
- Ask up to 5 questions from references/INTAKE.md.
- If still missing, proceed with clearly labeled assumptions and list Open questions that would change the decision.
What ships with it
13 files 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.
- eval/eval_config.json 759 B
- eval/SHOWCASE.md 4.4 KB
- eval/with_skill.md 22 KB
- eval/without_skill.md 9.4 KB
- README.md 1.7 KB
- references/CHECKLISTS.md 1.9 KB
- references/EXAMPLES.md 1.9 KB
- references/INTAKE.md 2.2 KB
- references/RUBRIC.md 3.3 KB
- references/SOURCE_SUMMARY.md 1.1 KB
- references/TEMPLATES.md 2.9 KB
- references/WORKFLOW.md 3.0 KB
- skillpack.json 378 B
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 · 138 lines · 30 tokens per session scan A c4b2375cdbf5
problem-definition is a skill published in the GitHub repository liqiongyu/lenny_skills_plus (52 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 1,992 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 2026-09-03.
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