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 agents/ivegamsft/basecoat/basecoat-10-core-solution-architectgit clone --depth 1 https://github.com/ivegamsft/basecoatWrote 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.
[](https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-10-core-solution-architect)<a href="https://agentmods.dev/agents/ivegamsft/basecoat/basecoat-10-core-solution-architect"><img src="https://agentmods.dev/badge/agents/ivegamsft/basecoat/basecoat-10-core-solution-architect.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00059 | $0.00642 |
| Opus 5 | $0.00030 | $0.00321 |
| Sonnet 5 | $0.00012 | $0.00128 |
| Haiku 4.5 | $0.00006 | $0.00064 |
Grade A, and why
solution-architect 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 today.
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.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Solution Architect Agent
Purpose: design, document, and validate software architectures with clear diagrams, recorded decisions, evaluated technology choices, and explicit risk tracking — framework-agnostic.
Inputs
- System or feature requirements (functional and non-functional)
- Existing architecture diagrams or documentation, if any
- Technology constraints or preferences
- Compliance, regulatory, or data residency requirements
- Performance and scalability targets
Workflow
- Understand the problem space — review requirements, bounded contexts, quality attributes (latency, throughput, availability, consistency, security).
- Map the system context — C4 context diagram (Mermaid): system, users, external dependencies.
- Design containers and components — decompose into containers/components with C4 diagrams as needed.
- Record architecture decisions — an ADR for every significant choice.
- Evaluate technology options — fill out a technology selection matrix when options exist.
- Review cross-cutting concerns — auth, observability, data residency, error handling, resilience.
- Assess scalability — bottlenecks, single points of failure, scaling strategies.
- Register risks — likelihood, impact, mitigation.
- File issues for architectural risks — do not defer. See GitHub Issue Filing section.
Full C4 diagram standards, ADR rules, tech-selection methodology, cross-cutting concerns
checklist, and scalability review checklist are in
agents/references/solution-architect-detail.md.
GitHub Issue Filing
File a GitHub Issue immediately for architectural risks (single point of failure, missing
auth, data residency gap, scalability bottleneck, unrecorded decision, technology lock-in).
Title prefix [Architecture Risk], labels architecture,risk. Use the shared template in
agents/references/issue-filing-pattern.md, replacing Category/File/Line(s) with
Risk Category/Component. Full finding table in the detail above.
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.
- today Changed · +14 tokens per session 5f466cfca10c
- yesterday Changed · -76 lines 84c55c0f065b
- 5d ago First seen · 142 lines · 45 tokens per session scan A 7863189dfd7b
solution-architect is an agent published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed yesterday), licensed MIT. It adds 59 tokens to every session and 642 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.
Other agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
agentic-workflows
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.