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 SyntaxArc/archipy-plugin --skill scaffold-archipy-adaptergit clone --depth 1 https://github.com/SyntaxArc/archipy-pluginWrote 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/syntaxarc/archipy-plugin/scaffold-archipy-adapter)<a href="https://agentmods.dev/skills/syntaxarc/archipy-plugin/scaffold-archipy-adapter"><img src="https://agentmods.dev/badge/skills/syntaxarc/archipy-plugin/scaffold-archipy-adapter.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 5.1 | $0.00042 | $0.00459 |
| Opus 5 | $0.00021 | $0.00230 |
| Sonnet 5 | $0.00008 | $0.00092 |
| Haiku 4.5 | $0.00004 | $0.00046 |
Grade A, and why
scaffold-archipy-adapter 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 7d 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
Scaffold ArchiPy Adapter
Before writing files
Ask the user for:
- Domain name (e.g.
user,order) - Adapter purpose / file stem (e.g.
db,cache→user_db_adapter.py) - Sync or async (or both as separate classes)
- Whether an in-memory mock is needed for BDD
- Whether this wraps an existing ArchiPy adapter or a new external client
Prefer ArchiPy
If ArchiPy already ships the client (Redis, Postgres, Kafka, …), prefer:
uv add "archipy[<extra>]"
and a thin domain wrapper — not a full reimplementation.
Generate
repositories/<domain>/
├── adapters/
│ └── <domain>_<purpose>_adapter.py # e.g. user_db_adapter.py
└── <domain>_repository.py # create stub if missing
- Thin wrapper: wrap ArchiPy adapter (or external client); own entity construction / query building; map client errors →
domain errors with
raise ... from e. - Optional mock: same module suffix or sibling file only if BDD needs an in-memory double.
- Ports: depend on ArchiPy ports when wrapping library adapters; add a local ABC only when the domain needs a custom contract.
Constraints
- Sync and async must be separate classes.
- No business logic in adapters — map data and talk to infrastructure only.
- Do not create a top-level
adapters/<name>/package — domain adapters live under repositories. - Wire via DI in
configs/containers.py.
Docs
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.
- 7d ago First seen · 58 lines · 42 tokens per session scan A 30cadc39dc45
scaffold-archipy-adapter is a skill published in the GitHub repository SyntaxArc/archipy-plugin (2 stars, last pushed 14d ago), licensed MIT. It adds 42 tokens to every session and 459 once invoked, about $0.0002 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.
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