assess-solution

assess-solution is a skill for Claude Code, Codex from Future-CX/AI-Architecture-Toolkit. It costs 60 tokens per session (1,395 once invoked), scanned A, original, MIT.

An interview-based assessment of a proposed or existing solution against architecture principles and a chosen capability overview or solution design. A capability overview describes what a product or platform needs to provide; a solution design describes how it will be built.

In plain words
What is it for?
Use it to gather the solution description, supplier information, references, and assessment baseline through focused questions, then evaluate the evidence.
Why use it?
It helps determine whether a solution fits the agreed principles and required capabilities before producing an assessment report.

Skill for Claude CodeCodex

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

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/future-cx/ai-architecture-toolkit/assess-solution
Any agent
npx skills add Future-CX/AI-Architecture-Toolkit --skill assess-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 assess-solution

README.md
[![agentmods](https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/assess-solution.svg)](https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/assess-solution)
Your own site
<a href="https://agentmods.dev/skills/future-cx/ai-architecture-toolkit/assess-solution"><img src="https://agentmods.dev/badge/skills/future-cx/ai-architecture-toolkit/assess-solution.svg" alt="Measured on agentmods" height="20"></a>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,395 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 5.1 $0.00060 $0.01395
Opus 5 $0.00030 $0.00698
Sonnet 5 $0.00012 $0.00279
Haiku 4.5 $0.00006 $0.00139

Measured 5d ago against content hash de0c9802a7cc, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

assess-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 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.

skills/assess-solution/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Assess Solution

Quick Start

Run an interview-based assessment of a proposed or existing solution against:

  1. The architecture principles available in principles/.
  2. One user-selected baseline:
    • A capability overview under capabilities/<slug>/.
    • A solution architecture design under solution-architectures/<slug>/.

If the user has not identified the capability overview or solution design, ask which one to use before starting the assessment. Use the selected baseline and principles to ask focused questions. Do not produce the final report until the user has answered the interview topics and confirmed that the assessment evidence is complete enough.

Required Inputs

  • Solution description, proposal, implementation notes, or path to an existing solution document, gathered or confirmed through the interview.
  • Solution supplier, vendor, product company, or implementation partner when the solution depends on an external company.
  • Customer references, case studies, testimonials, analyst notes, or reference-call findings when available.
  • Assessment baseline: one capability overview or one solution architecture design.
  • Architecture principles to assess against. Prefer all principle documents under principles/ unless the user names a subset.
  • Target audience and desired depth, if different from architecture and delivery stakeholders.

Workflow

  1. Start in interview mode. Ask one question at a time and do not generate the final assessment until the interview is complete.
  2. Confirm the solution, supplier, and whether to assess against a capability overview or solution architecture design when the baseline is not explicit.
  3. Locate and read the selected baseline and architecture principles. If multiple baselines match, ask the user to choose one.
  4. Extract baseline expectations to build the interview plan:
    • Business outcome and scope boundary.
    • Main business features or requirements, users, processes, data, integrations, systems, and dependencies.
    • Security, privacy, compliance, non-functional, operational, and lifecycle expectations.
    • Explicit risks, assumptions, constraints, open questions, and design decisions.
  5. Interview the user for each main business feature or requirement. Ask for fit, evidence, known gaps, user impact, operational impact, and required action.
  6. Interview the user on each assessment topic: ease of use, other features, integrations, target architecture alignment, principle alignment, supplier, references, price indication, risks, constraints, and open questions.
  7. After each topic, summarize captured facts, assumptions, missing evidence, and follow-up questions. Ask follow-ups when answers are vague or unsupported. When there is a strong evidence-based suggestion, include it with the question and ask the user to confirm, correct, or reject it.
  8. Before writing the report or scorecard, summarize the evidence collected and ask the user to confirm whether to proceed or answer remaining questions.
  9. Assess principle alignment using Aligned, Partly aligned, Misaligned, or Not enough evidence.
  10. Create the simple 5-star scorecard only after the interview is complete and the user has confirmed there is enough evidence. Use whole stars only; do not use half-star symbols.
  11. Identify gaps, risks, trade-offs, and open questions. Do not invent missing facts.
  12. Give a practical recommendation:
    • Proceed when only minor issues remain.
    • Proceed with conditions when risks or gaps need tracked mitigation.
    • Revise before approval when material conflicts or missing decisions remain.
    • Do not proceed when the solution conflicts with critical principles or baseline expectations.

Read the full file on GitHub · 80 lines

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. 5d ago First seen · 80 lines · 60 tokens per session scan A de0c9802a7cc

Subscribe to this mod's changes

assess-solution is a skill published in the GitHub repository Future-CX/AI-Architecture-Toolkit (5 stars, last pushed 2d ago), licensed MIT. It adds 60 tokens to every session and 1,395 once invoked, about $0.0003 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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