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 DDS-Solutions/AI-TadPole-OS --skill improve-codebase-architecturegit clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSWrote 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/dds-solutions/ai-tadpole-os/improve-codebase-architecture)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/improve-codebase-architecture"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/improve-codebase-architecture/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/dds-solutions/ai-tadpole-os/improve-codebase-architecture"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/improve-codebase-architecture.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 | $0.00032 | $0.01516 |
| Opus 5.5 | $0.00013 | $0.00606 |
| Sonnet 5.5 | $0.00006 | $0.00303 |
| Haiku 4.5 | $0.00003 | $0.00152 |
Grade A, and why
improve-codebase-architecture 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 9d 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 — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.
[!IMPORTANT] AI Context & Knowledge Heritage
- Subsystem: Agent Skills Registry / improve-codebase-architecture
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Shallow module proliferation, scattered locality, or leaky abstraction seams.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
Codebase Architecture Improvement Protocol
Purpose: Scan the codebase for architectural friction, identify shallow modules and high-churn hotspots, compute symbol blast radius via the Sovereign Symbol Graph, and propose deepening opportunities that transform shallow pass-through layers into robust, high-leverage engines.
Workflow Bindings: Integrated into/refactorand/audit.
📚 Progressive Disclosure & L3 Reference Index
Read the core Sovereign rules below; consult deep L3 Reference Guides on demand:
| L3 Reference Guide | Purpose | Trigger / When to Load |
|---|---|---|
references/deep_module_design_patterns.md |
Ousterhout's Deep Module theory, the 7 design concepts, and refactoring patterns | Planning refactors, evaluating module interfaces, or decomposing hubs |
scripts/architecture_scanner.py |
Automated git hotspot scanner and offline visual HTML report generator | Initiating an architecture audit or locating high-churn friction |
code-review-graph |
Symbol graph call-tree inspector and blast radius calculator (npm run graph:blast) |
Measuring blast radius before editing Rust hubs or React stores |
🏛️ 1. The 7 Deep Module Vocabulary Concepts
Every architectural review and refactoring proposal must strictly employ the Deep Module Vocabulary:
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago Changed · +49 lines ad791d66f075
- 1mo ago First seen · 59 lines · 32 tokens per session scan A c318798132f2
improve-codebase-architecture is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed 5d ago), licensed MIT. It adds 32 tokens to every session and 1,516 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 2026-09-03.
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