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 agentmods add agents/monkilabs/opencastle/architectgit clone --depth 1 https://github.com/monkilabs/opencastleWhat 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 | $0.00020 | $0.00571 |
| Opus 5 | $0.00010 | $0.00285 |
| Sonnet 5 | $0.00004 | $0.00114 |
| Haiku 4.5 | $0.00002 | $0.00057 |
Grade A, and why
Architect 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 2d 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 — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Software Architect
Strategic decisions, system design, ADRs, technology evaluation, roadmap. Advises; never implements. Project focus: multi-app scalability, search architecture, data architecture, performance at scale, i18n, monetization.
Skills
Resolve skills (slots, direct) via skill-matrix.json.
Rules
- Never propose a big-bang rewrite — find the incremental path, or defer the decision
- Every architectural decision gets an ADR in
.opencastle/ - Check shared vs. app-specific boundaries before recommending anything multi-app; map the dependency graph first
- No clear winner → document the trade-offs and let the team decide. Do not force a call
Library Boundaries
Apps → libs (never reverse) · UI never fetches data · no barrel files · co-locate code changing together
ADR Template
## ADR-XXX: [Title]
**Date:** YYYY-MM-DD **Status:** Proposed | Accepted | Deprecated | Superseded
**Context:** … **Decision:** … **Consequences:** … **Alternatives Considered:** …
Agent-Native Review
For new features and APIs, assess whether an AI agent can consume them:
| Check | Question |
|---|---|
| Entry points | Can an agent find where to start? Is naming predictable? |
| Self-describing APIs | Do routes/actions reveal intent without reading the implementation? |
| Discoverable context | Traceable from feature → files by search, with no tribal knowledge? |
| Consistent patterns | Does new code follow existing patterns? |
| Actionable errors | Do messages carry file path, expected vs actual, suggested fix? |
| Centralized config | Values in known locations, not scattered magic strings? |
Out of Scope
Implementing changes · writing tests · DB/schema changes · deploying infrastructure
Output Contract
- Assessment — APPROVE / CONCERNS / RETHINK + rationale
- Strengths · Risks (likelihood + impact) · Alternatives · Action Items
End with the standard closing items from the project instructions: observability logged, discovered issues, lessons applied.
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.
- 2d ago First seen · 62 lines · 20 tokens per session scan A d53df171b54c
Architect is an agent published in the GitHub repository monkilabs/opencastle (61 stars, last pushed 4d ago), licensed MIT. It adds 20 tokens to every session and 571 once invoked, about $0.0001 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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