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/getcrew44/crew44/problem-statementnpx skills add getcrew44/crew44 --skill problem-statementgit clone --depth 1 https://github.com/getcrew44/crew44What 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 | $0.00044 | $0.02184 |
| Opus 5 | $0.00022 | $0.01092 |
| Sonnet 5 | $0.00009 | $0.00437 |
| Haiku 4.5 | $0.00004 | $0.00218 |
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 2d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- problem-statement — 98% identical, 3 lines differ
How it starts
The opening of the file, as written. The whole thing — 247 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Articulate a problem from the user's perspective using an empathy-driven framework that captures who they are, what they're trying to do, what's blocking them, why, and how it makes them feel. Use this to align stakeholders on the problem before jumping to solutions, and to frame product work around user outcomes rather than feature requests.
This is not a requirements doc—it's a human-centered problem narrative that ensures you're solving a problem worth solving.
Key Concepts
The Problem Framing Framework
Based on Jobs-to-be-Done and empathy mapping, the framework structures problems as:
Problem Framing Narrative:
- I am: [Describe the persona experiencing the problem]
- Trying to: [Desired outcomes the persona cares about]
- But: [Barriers preventing the outcomes]
- Because: [Root cause of the problem]
- Which makes me feel: [Emotional impact]
Context & Constraints:
- [Geographic, technological, time-based, demographic factors]
Final Problem Statement:
- [Single, concise, empathetic summary]
Why This Structure Works
- Persona-centric: Forces you to see the problem through the user's eyes
- Outcome-focused: "Trying to" emphasizes desired results, not tasks
- Root cause analysis: "Because" pushes past symptoms to underlying issues
- Emotional validation: "Makes me feel" humanizes the problem and builds empathy
- Contextual: Constraints acknowledge real-world limitations
Anti-Patterns (What This Is NOT)
- Not a solution in disguise: "The problem is we lack AI-powered analytics" = sneaking in a solution
- Not a business problem: "Our revenue is down" isn't a user problem (it's a symptom)
- Not a feature request: "Users need a dashboard" isn't a problem (what are they trying to do?)
- Not generic: "Users want better UX" is too vague to be actionable
When to Use This
- Kicking off discovery or problem validation work
- Aligning stakeholders before solutioning
- Socializing a problem with engineering, design, or exec teams
- When you have feature requests but unclear underlying problems
- Pitching why a problem is worth solving
What ships with it
2 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.
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.
- 2d ago First seen · 247 lines · 44 tokens per session scan A b7cfbb259e1d
problem-statement is a skill published in the GitHub repository getcrew44/crew44 (359 stars, last pushed 2mo ago), licensed MIT. It adds 44 tokens to every session and 2,184 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 2026-08-30.
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