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 skills add Kastalien-Research/thoughtbox --skill diagramgit clone --depth 1 https://github.com/Kastalien-Research/thoughtboxWrote 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/kastalien-research/thoughtbox/diagram)<a href="https://agentmods.dev/skills/kastalien-research/thoughtbox/diagram"><img src="https://agentmods.dev/badge/skills/kastalien-research/thoughtbox/diagram/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/kastalien-research/thoughtbox/diagram"><img src="https://agentmods.dev/badge/skills/kastalien-research/thoughtbox/diagram.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 | $0.00024 | $0.00299 |
| Opus 5.5 | $0.00010 | $0.00120 |
| Sonnet 5.5 | $0.00005 | $0.00060 |
| Haiku 4.5 | $0.00002 | $0.00030 |
Grade A, and why
diagram 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 1mo 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.
What it actually says
Generate architecture diagrams for: $ARGUMENTS
Workflow
- Launch the
architecture-diagrammeragent with the target subsystem - The agent will:
- Explore all files in the target module
- Map entry points, data flows, and component relationships
- Produce
docs/<target>-architecture.mdwith Mermaid diagrams
- Report which diagrams were produced
Execution
Use the Task tool to launch the architecture-diagrammer agent:
Task({
subagent_type: "architecture-diagrammer",
prompt: "Generate architecture diagrams for the '$ARGUMENTS' subsystem. Explore the codebase, trace data flows, and produce docs/$ARGUMENTS-architecture.md with Mermaid diagrams covering: system context, sequence diagrams for key flows, component architecture, and startup lifecycle.",
description: "Diagram $ARGUMENTS architecture"
})
Output
After the agent completes, summarize:
- File produced:
docs/<target>-architecture.md - Number and types of diagrams generated
- Key architectural insights discovered
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.
- 1mo ago First seen · 38 lines · 24 tokens per session scan A 03a5de88d4ab
diagram is a skill published in the GitHub repository Kastalien-Research/thoughtbox (65 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 299 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 2026-08-30.
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