Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/DDS-Solutions/AI-TadPole-OSnpx agentmods add skills/dds-solutions/ai-tadpole-os/architectureWrote 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/architecture)<a href="https://agentmods.dev/skills/dds-solutions/ai-tadpole-os/architecture"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/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/architecture"><img src="https://agentmods.dev/badge/skills/dds-solutions/ai-tadpole-os/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 | $0.00028 | $0.00775 |
| Opus 5.5 | $0.00011 | $0.00310 |
| Sonnet 5.5 | $0.00006 | $0.00155 |
| Haiku 4.5 | $0.00003 | $0.00077 |
Grade A, and why
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 12d 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 — 67 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 / architecture
- Architecture:
@docs ARCHITECTURE:Documentation- Failure Path: Information drift, legacy terminology, or documentation mismatch.
- Observability: Traceability via
execution/parity_guard.py([SKILL])
Architecture Decision Framework
"Requirements drive architecture. Trade-offs inform decisions. ADRs capture rationale." Workflow Binding: Used directly during the
/plan,/brainstorm, and/auditworkflows.
🎯 Progressive Disclosure & L3 Topic Index
Read REQUIRED core standards below; consult deep L3 Topic Guides on demand:
| Guide / Tool | Description | When to Read |
|---|---|---|
references/context-discovery.md |
Questions to ask, project classification | Starting architecture design |
references/trade-off-analysis.md |
ADR templates, trade-off framework | Documenting decisions |
references/pattern-selection.md |
Decision trees, anti-patterns | Choosing patterns |
references/examples.md |
MVP, SaaS, Enterprise examples | Reference implementations |
references/patterns-reference.md |
Quick lookup for patterns | Pattern comparison |
scripts/architecture_linter.py |
Deterministic ADR structure and architecture boundary validator | Validating ADR documents or self-test verification |
🛡️ Socratic Gate: Architectural Trade-Off Alignment
Before committing to a structural or architectural decision:
- At Least 2 Competing Paradigms: What are the alternatives (e.g. SQLite vs PostgreSQL, Tauri IPC vs HTTP REST)?
- Blast Radius Analysis: What components, routes, or stores are impacted? (
npm run graph:blast) - Rollback & Reversibility: If this architectural assumption fails in production, how painful is unwinding it?
What ships with it
6 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.
- 12d ago Changed · -12 lines efaf3baee731
- 2mo ago First seen · 79 lines · 28 tokens per session scan A 8eb08a6971f8
architecture is a skill published in the GitHub repository DDS-Solutions/AI-TadPole-OS (8 stars, last pushed today), licensed MIT. It adds 28 tokens to every session and 775 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.
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