problem-framing

A method for clarifying the real problem behind a software request before choosing a solution. It identifies the user, their goal, what blocks them, and any assumptions.

In plain words
What is it for?
Use it to turn vague goals into a confirmed problem statement. It helps compare possible interpretations and decide what should be built.
Why use it?
It prevents work from starting on a solution that may not address the actual need. It also helps resolve requests that could reasonably be understood in several ways.

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

Made for: Claude Code, Codex.

Per session 28 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 218 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 $0.00028 $0.00218
Opus 5 $0.00014 $0.00109
Sonnet 5 $0.00006 $0.00044
Haiku 4.5 $0.00003 $0.00022

Measured 2d ago against content hash 46be78c6c2c3, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

problem-framing 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.

daemon/internal/presets/defaultcrew/skills/partner/problem-framing/SKILL.md · 29 lines

What it actually says

Problem Framing

Translate a fuzzy request into a clear problem statement before any work begins.

When to use

  • The user describes what they want but not why.
  • The request jumps to a specific solution.
  • Multiple interpretations are possible and they diverge in effort or outcome.

Steps

  1. Restate the request in plain language. Confirm with the user.
  2. Ask: who is the user, what are they trying to accomplish, what is in their way today?
  3. Identify hidden assumptions in the request and name them.
  4. Offer 2-3 framings of the problem if more than one fits. Let the user pick.
  5. State the chosen framing back as a single sentence the user can confirm.

Anti-patterns

  • Restating jargon back without unpacking it.
  • Asking five clarifying questions at once.
  • Skipping confirmation and proceeding on a guess.
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 · 29 lines · 28 tokens per session scan A 46be78c6c2c3

Subscribe to this mod's changes

problem-framing is a skill published in the GitHub repository getcrew44/crew44 (359 stars, last pushed 2mo ago), licensed MIT. It adds 28 tokens to every session and 218 once invoked, about $0.0001 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.