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 agentmods add skills/uthumany/uthy-legacy-os/problem-statementnpx skills add uthumany/uthy-legacy-os --skill problem-statementgit clone --depth 1 https://github.com/uthumany/uthy-legacy-osWrote 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/uthumany/uthy-legacy-os/problem-statement)<a href="https://agentmods.dev/skills/uthumany/uthy-legacy-os/problem-statement"><img src="https://agentmods.dev/badge/skills/uthumany/uthy-legacy-os/problem-statement.svg" alt="Measured on agentmods" 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 | $0.00031 | $0.00975 |
| Opus 5 | $0.00015 | $0.00487 |
| Sonnet 5 | $0.00006 | $0.00195 |
| Haiku 4.5 | $0.00003 | $0.00097 |
Grade A, and why
problem-statement 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 5d 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 — 83 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Problem Statement
Overview
A well-crafted problem statement aligns teams around what to solve before arguing about how to solve it. This skill guides you through writing evidence-based problem statements that frame the customer problem, its impact, and why it matters — without prescribing a solution.
When to Use
- Starting a new feature, product, or initiative
- Aligning cross-functional stakeholders on what to prioritize
- Writing a PRD or project brief
- Responding to a vague request ("We need to do something about X")
- Don't use for: execution work where the problem is already well-understood
Instructions
1. Gather Evidence
A problem statement is only as strong as its evidence. Collect:
- Qualitative: Customer interview quotes, support tickets, user feedback
- Quantitative: Usage data, funnel drop-offs, revenue impact, churn stats
- Context: Market trends, competitive moves, business goals
2. Write the Problem Statement
Use this template:
[Who] has a problem [what/that]. This matters because [impact on user business]. We have evidence: [evidence summary]. Solving this would [desired outcome].
Example:
"Mid-market engineering teams have a problem staying aligned on project status across distributed teams. This matters because they spend 4+ hours/week in status meetings instead of building. We have evidence: 6/8 interview participants described status sync as their #1 time waste, and our analytics show 70% of daily active users check project boards for status updates. Solving this would reduce status overhead by 50% and increase time for feature work."
3. Validate the Statement
Check your problem statement against these criteria:
- No solution embedded: Does it describe WHAT not HOW? (Bad: "We need a chatbot" / Good: "Users struggle to find answers")
- Evidence-backed: Can you point to real data or interviews for each claim?
- Scoped: Is it specific enough to act on, broad enough to allow creative solutions?
- User-centered: Is the problem from the user's perspective, not the business's?
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.
- 5d ago First seen · 83 lines · 31 tokens per session scan A f9695365a8b4
problem-statement is a skill published in the GitHub repository uthumany/uthy-legacy-os (5 stars, last pushed 3mo ago), licensed MIT. It adds 31 tokens to every session and 975 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.
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