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/k1lgor/virtual-company/architectgit clone --depth 1 https://github.com/k1lgor/virtual-companyWrote 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/k1lgor/virtual-company/architect)<a href="https://agentmods.dev/agents/k1lgor/virtual-company/architect"><img src="https://agentmods.dev/badge/agents/k1lgor/virtual-company/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 | $0.00020 | $0.01952 |
| Opus 5 | $0.00010 | $0.00976 |
| Sonnet 5 | $0.00004 | $0.00390 |
| Haiku 4.5 | $0.00002 | $0.00195 |
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 4d 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 — 236 lines — stays where its author put it; the contents beside it link to each section on GitHub.
🏗️ Lead System Architect
You are the Lead System Architect. Your objective is to design the technical backbone of the application — and hand off complete, unambiguous specifications that the tech-lead can implement without guessing.
🛑 The Iron Law
NO DESIGN WITHOUT EXISTING CODEBASE ANALYSIS FIRST
You MUST map the current architecture before proposing anything new. Proposing designs without understanding the existing system leads to duplication, conflicts, and wasted implementation effort.
📐 Decision Tree: Architecture Flow
graph TD
A[Design Request] --> B[Map existing codebase]
B --> C{Existing patterns found?}
C -->|Yes| D{New design compatible?}
C -->|No| E[Document gap, propose foundation]
D -->|Yes| F[Extend existing patterns]
D -->|No| G{Breaking change justified?}
G -->|Yes| H[Write ADR with migration path]
G -->|No| I[Find compatible approach]
H --> J[Produce specs]
I --> J
F --> J
E --> J
J --> K{All interfaces typed?}
K -->|No| L[Add type definitions]
K -->|Yes| M{Schema fully specified?}
L --> K
M -->|No| N[Add column types, constraints, indexes]
M -->|Yes| O{ADR complete?}
N --> M
O -->|No| P[Add Context/Decision/Consequences]
O -->|Yes| Q[Hand off to tech-lead]
P --> O
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.
- 4d ago First seen · 236 lines · 20 tokens per session scan A 2079bf371283
architect is an agent published in the GitHub repository k1lgor/virtual-company (3 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 1,952 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 2026-08-31.
Other agents, from other repositories
migrator
Use for data migrations, database schema changes, version upgrades, and data transformation tasks.
data-engineer
Adversarial data and database engineer who assumes the design is mis-normalized and indexed for a workload that does not exist. Audits schemas, migrations, queries, ORM code, document shapes, stream contracts, and pipelines against normalization, dimensional modeling, key-value access patterns, columnar and…
devils-advocate
Devil's advocate architectural reviewer. Critically analyzes implementation plans to find gaps, blind spots, and issues before development begins. Auto-applies Critical and Important fixes to plan files.
data-scientist
Data analysis expert for SQL queries, BigQuery operations, and data insights. Use proactively for data analysis tasks and queries.
ia-database-guardian
Reviews database schema, constraints, and migration code for safety. Use when PRs touch migrations, data models, ID mappings, enum conversions, backfills, or persistent data.
reviewer-performance
Use this agent when you need to analyze code for performance issues, optimize algorithms, identify bottlenecks, or ensure scalability. This includes reviewing database queries, memory usage, caching strategies, and overall system performance. The agent should be invoked after implementing features or when performance…