Borrowing it
Nothing to install: this file belongs to BV-Venky/excalidraw-architect-mcp. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/BV-Venky/excalidraw-architect-mcp/main/.skills/architecture-knowledge-graph/SKILL.mdgit clone --depth 1 https://github.com/BV-Venky/excalidraw-architect-mcpWrote 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/skills/bv-venky/excalidraw-architect-mcp/architecture-knowledge-graph)<a href="https://agentmods.dev/skills/bv-venky/excalidraw-architect-mcp/architecture-knowledge-graph"><img src="https://agentmods.dev/badge/skills/bv-venky/excalidraw-architect-mcp/architecture-knowledge-graph/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/skills/bv-venky/excalidraw-architect-mcp/architecture-knowledge-graph"><img src="https://agentmods.dev/badge/skills/bv-venky/excalidraw-architect-mcp/architecture-knowledge-graph.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00067 | $0.01104 |
| Opus 5 | $0.00034 | $0.00552 |
| Sonnet 5 | $0.00013 | $0.00221 |
| Haiku 4.5 | $0.00007 | $0.00110 |
Grade A, and why
architecture-knowledge-graph 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 13d 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 — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architecture Knowledge Graph Guide
This skill teaches you how to turn a codebase into a clean, durable knowledge
graph using the kg_* MCP tools. The graph (default .claude/architecture.md)
is the single source of truth; diagrams are rendered views of it.
Graph quality depends almost entirely on how well you read the code. The MCP preserves, validates, and renders whatever you put in — it does not analyze the codebase. That analysis is your job.
Core Principle
Model services/components and how they communicate, not classes, functions,
or every import. A "service" is a deployable unit / bounded context — one
repo, one container, one logical responsibility.
Workflow (do the passes in order — don't interleave)
kg_initonce (orkg_importto bootstrap from an existing.excalidraw).- Discovery pass — identify every service first. Add each with
kg_add_service, settingcomponent_type,domain, andownerwhile the info is in front of you (Dockerfiles,CODEOWNERS, READMEs, manifests). - Linking pass — only after all services exist, add edges with
kg_link. Linking before a target exists fails; that's why discovery comes first. kg_lint— catch dangling references, cycles, and single points of failure. Fix them before rendering.kg_render(whole graph) orkg_render_view/kg_render_around/kg_render_domainfor focused diagrams.
How to find the edges (where services talk)
Look for these signals and translate each into a labelled kg_link:
| Signal in code | Link | Label / style |
|---|---|---|
| HTTP client, base URL, OpenAPI/Swagger spec | sync call | "REST /orders", style: solid |
| gRPC stub / proto service | sync call | "gRPC GetOrder", style: solid |
| Kafka/SQS/RabbitMQ producer | async event | "Kafka order.created", style: dashed |
| Kafka/SQS/RabbitMQ consumer | async event (incoming) | label with the same topic |
| DB connection string / ORM config | datastore | "reads/writes", style: solid |
Service-discovery / env var (PAYMENTS_URL) |
dependency | name the protocol |
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.
- 13d ago First seen · 91 lines · 67 tokens per session scan A 0ec968c4d669
architecture-knowledge-graph is a skill published in the GitHub repository BV-Venky/excalidraw-architect-mcp (150 stars, last pushed 17d ago), licensed MIT. It adds 67 tokens to every session and 1,104 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 2026-08-30.
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