problem-to-solution

problem-to-solution is a skill for Claude Code, Codex from Future-CX/AI-Architecture-Toolkit. It costs 62 tokens per session (1,771 once invoked), scanned A, original, MIT.

A decision brief that turns an unclear business problem into a short document comparing solution options and recommending a way forward.

In plain words
What is it for?
Use it to frame a problem, brainstorm and compare alternatives, prepare a recommendation, or write a decision paper for senior stakeholders.
Why use it?
It gives non-technical stakeholders a shared view of the problem, trade-offs, and decision needed. This helps them review choices and agree on next steps.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to frame a problem, brainstorm and compare alternatives, prepare a recommendation, or write a decision paper for senior stakeholders.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/future-cx/ai-architecture-toolkit/problem-to-solution
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.

Any agent
npx skills add Future-CX/AI-Architecture-Toolkit --skill problem-to-solution
Clone the repo
git clone --depth 1 https://github.com/Future-CX/AI-Architecture-Toolkit

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for problem-to-solution

README.md
[![agentmods](https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/problem-to-solution/github.svg)](https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/problem-to-solution)
Your own site
<a href="https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/problem-to-solution"><img src="https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/problem-to-solution/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.

agentmods 80×15 button for problem-to-solution

Your own site · 80×15
<a href="https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/problem-to-solution"><img src="https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/problem-to-solution.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,771 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00062 $0.01771
Opus 5.5 $0.00025 $0.00708
Sonnet 5.5 $0.00012 $0.00354
Haiku 4.5 $0.00006 $0.00177

Measured 2mo ago against content hash 7e5b2ec86950, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

problem-to-solution 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 2mo 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.

skills/problem-to-solution/SKILL.md · 107 lines

How it starts

The opening of the file, as written. The whole thing — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Problem To Solution

Quick Start

Use this skill to turn an ambiguous problem into a concise decision document for non-technical business stakeholders.

Store generated problem-to-solution briefs under the consuming repository's private lab root in problem-to-solutions/.

problem-to-solutions/<problem-slug>-problem-to-solution.md

Use templates/problem-to-solution-template.md as the output structure. Replace placeholders and drafting guidance with concrete content; do not leave unanswered sections unless the unknown is explicitly marked as TBD or an open question. Remove the ## Open Questions section when there are no open questions.

Problem-to-solution briefs are written for non-technical business stakeholders first. Architects and delivery teams should get enough context to act, but the opening sections must be easy for a business reader to scan, understand, and use in a decision meeting.

Do not write real-company decision context into this public toolkit repository.

Required Inputs

  • Problem statement
  • Decision needed
  • Decision owner or forum
  • Stakeholders and impacted groups
  • Business or architecture context
  • Constraints, assumptions, and non-goals
  • Evaluation criteria
  • Candidate solution options
  • Recommendation and rationale after solution exploration is complete
  • ADR link when the solution is decided

Workflow

  1. Clarify the problem, why it matters now, who needs to decide, and when a decision is needed.
  2. Ask for known constraints, non-goals, dependencies, risks, and stakeholder concerns when not already provided.
  3. Read related architecture documents when paths are provided.
  4. Validate terminology against <private-lab-root>/GLOSSARY.md when the brief uses domain-specific applications, capabilities, data objects, or jargon. Use ../ubiquitous-language/SKILL.md to clarify or update terminology before option brainstorming when important terms are missing, ambiguous, or overloaded.
  5. Use ../grill-me/SKILL.md to pressure-test the problem framing, assumptions, constraints, stakeholder tensions, and evaluation criteria before settling on solution options.
  6. Brainstorm 2-5 realistic solution options. Include a "do nothing" or "defer" option only when it is a plausible decision path.
  7. Evaluate each option against the same criteria so comparisons are fair and decision-ready.
  8. Write balanced pros and cons for each option. Avoid strawman alternatives.
  9. Before writing a recommendation, use ../grill-me/SKILL.md for a dedicated exploration review of all options, pros, cons, assumptions, missing alternatives, hidden constraints, and stakeholder trade-offs. Ask questions one at a time and wait for feedback before concluding the review.
  10. Revise the options, pros, cons, criteria, and open questions based on the grill-me session.
  11. Only after the grill-me exploration review is complete, recommend one option, or a staged combination, with clear rationale, trade-offs, and conditions for success.
  12. Create or update the problem-to-solution brief from templates/problem-to-solution-template.md. Preserve the two opening tables: the document metadata table first, followed by the Integration Overview table.
  13. Run the readability and glossary compliance gate before finishing:

Read the full file on GitHub · 107 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. 2mo ago First seen · 107 lines · 62 tokens per session scan A 7e5b2ec86950

Subscribe to this mod's changes

problem-to-solution is a skill published in the GitHub repository Future-CX/AI-Architecture-Toolkit (8 stars, last pushed 18d ago), licensed MIT. It adds 62 tokens to every session and 1,771 once invoked, about $0.0002 per session on Opus 5.5. 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.

Related

problem-to-solution compared with skills from other repositories

problem-to-solution next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
problem-to-solutionFuture-CX/AI-Architecture-ToolkitSkill818d agoMITA62Claude Code, Codex
imagegenopenai/codexSkill133kyesterdayApache-2.0A113Codex
playwright-climicrosoft/playwrightSkill99kyesterdayApache-2.0A19Claude Code
local-ai-agentsmicrosoft/ai-agents-for-beginnersSkill79k4d agoMITA200Claude Code, Codex
systematic-debuggingobra/superpowersSkill314k3d agoMITA21Claude Code
next-cache-components-adoptionvercel/next.jsSkill143kyesterdayMITA95Claude Code
next-partial-prefetching-adoptionvercel/next.jsSkill143kyesterdayMITA103Claude Code