problem-statement

A framework for describing a product problem from the user's point of view: who is blocked, what they want to do, what prevents it, why, and how it feels.

In plain words
What is it for?
Use it when framing product discovery, prioritizing work, or preparing a product requirements document (PRD), a document that explains what a product should achieve.
Why use it?
It keeps product discussions focused on a real user problem instead of jumping straight to a feature or solution. This helps teams decide what is worth solving and why.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/getcrew44/crew44/problem-statement
Any agent
npx skills add getcrew44/crew44 --skill problem-statement
Clone the repo
git clone --depth 1 https://github.com/getcrew44/crew44

Made for: Claude Code, Codex.

Per session 44 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,184 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 2d ago against content hash b7cfbb259e1d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

daemon/internal/presets/defaultcrew/skills/product/problem-statement/SKILL.md · 247 lines

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

Read the full file on GitHub · 247 lines

Files

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.

Changes

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.

  1. 2d ago First seen · 247 lines · 44 tokens per session scan A b7cfbb259e1d

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

interview

Ask one useful structured question at a time only when material product/implementation choices are genuinely missing; remember answers and produce a brief/spec. Discoverable facts should be investigated instead of asked.

Hmbown/CodeWhale · 40 tokens

test

Detect the project’s test stack, run the narrowest useful tests, create tests when authorized, and report coverage/gaps honestly.

Hmbown/CodeWhale · 28 tokens

verify

Exercise the real app/API/CLI and collect observable evidence; tests alone do not count as end-to-end verification.

Hmbown/CodeWhale · 25 tokens

build-teaql-app

Build or change a TeaQL application in Java, Rust, Go, Swift, Python, C#/.NET, or TypeScript, including Kotlin/JVM applications that consume Java-generated libraries. Mandatory order: first draft and save a complete KSML model, then verify the client and evaluate that saved model, repair it through repeated evaluation…

teaql/teaql-agent-kit · 112 tokens

ccc

This skill should be used when code search is needed (whether explicitly requested or as part of completing a task), when indexing the codebase after changes, or when the user asks about ccc, cocoindex-code, or the codebase index. Trigger phrases include 'search the codebase', 'find code related to', 'update the…

cocoindex-io/cocoindex-code · 80 tokens

warp-delegate

Delegate a coding task to the Warp Agent CLI (oz) as a background implementer, then review its diff and land it yourself. Use this whenever the user wants to hand implementation work to Warp - phrasings like "have Warp implement X", "delegate this to the Warp CLI", "run it through Warp", "use oz to…

amElnagdy/delegate-skills · 144 tokens