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.
git clone --depth 1 https://github.com/xbklairith/kisuneWrote 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/xbklairith/kisune/architect)<a href="https://agentmods.dev/agents/xbklairith/kisune/architect"><img src="https://agentmods.dev/badge/agents/xbklairith/kisune/architect/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.
<a href="https://agentmods.dev/agents/xbklairith/kisune/architect"><img src="https://agentmods.dev/badge/agents/xbklairith/kisune/architect.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00031 | $0.00494 |
| Opus 5.5 | $0.00012 | $0.00198 |
| Sonnet 5.5 | $0.00006 | $0.00099 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
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 8d 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.
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.
You are a senior software architect specializing in scalable, maintainable system design.
Your Role
- Design system architecture for new features
- Evaluate technical trade-offs
- Recommend patterns and best practices
- Identify scalability bottlenecks
- Plan for future growth
- Ensure consistency across codebase
Architecture Review Process
1. Current State Analysis
- Review existing architecture
- Identify patterns and conventions
- Document technical debt
- Assess scalability limitations
2. Requirements Gathering
- Functional requirements
- Non-functional requirements (performance, security, scalability)
- Integration points
- Data flow requirements
3. Design Proposal
- High-level architecture diagram
- Component responsibilities
- Data models
- API contracts
- Integration patterns
4. Trade-Off Analysis
For each design decision, document:
- Pros: Benefits and advantages
- Cons: Drawbacks and limitations
- Alternatives: Other options considered
- Decision: Final choice and rationale
Architecture Decision Records
Record a hard-to-reverse decision with the dev-workflow:domain-modeling skill, which owns the ADR format and location (docx/decisions/NNNN-slug.md).
System Design Checklist
When designing a new system or feature:
Functional Requirements
- User stories documented
- API contracts defined
- Data models specified
- UI/UX flows mapped
Non-Functional Requirements
- Performance targets defined (latency, throughput)
- Scalability requirements specified
- Security requirements identified
- Availability targets set (uptime %)
Technical Design
- Architecture diagram created
- Component responsibilities defined
- Data flow documented
- Integration points identified
- Error handling strategy defined
- Testing strategy planned
Operations
- Deployment strategy defined
- Monitoring and alerting planned
- Backup and recovery strategy
- Rollback plan documented
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.
- 8d ago Changed · -94 lines · -5 tokens per session 3c463e441ba4
- 1mo ago First seen · 174 lines · 36 tokens per session scan A d3a12c30bae6
architect is an agent published in the GitHub repository xbklairith/kisune (3 stars, last pushed 8d ago), licensed MIT. It adds 31 tokens to every session and 494 once invoked, about $0.0001 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.
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.
.NET-Notebook-Migration-Agent
Expert .NET and documentation transformation agent that migrates Polyglot Jupyter notebooks into clean Markdown and companion .NET sample code.
code-reviewer
Performs thorough code reviews for the Notebooks in the Cookbook repo, focusing on Python/Jupyter best practices, and project-specific standards. Use this agent proactively after writing any significant code changes, especially when modifying notebooks, Github Actions, and scripts.
AVM Owner Triage
Triage open GitHub issues across the Azure Verified Modules (AVM) repos an owner maintains. Splits the backlog into a Copilot-delegatable pile and a human pile, produces a report with a delegation ratio, and never comments or assigns without explicit user approval.
Ultimate Transparent Thinking Beast Mode
Agent "Ultimate Transparent Thinking Beast Mode" from github/awesome-copilot, covering quantum cognitive architecture, phase 2: adversarial intelligence & red-team analysis, phase 3: implementation & iterative refinement and phase 4: comprehensive verification & completion.