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 msdakot/ai-foundary --skill architectgit clone --depth 1 https://github.com/msdakot/ai-foundaryWrote 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/msdakot/ai-foundary/architect)<a href="https://agentmods.dev/skills/msdakot/ai-foundary/architect"><img src="https://agentmods.dev/badge/skills/msdakot/ai-foundary/architect/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/msdakot/ai-foundary/architect"><img src="https://agentmods.dev/badge/skills/msdakot/ai-foundary/architect.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 | $0.00043 | $0.00832 |
| Opus 5.5 | $0.00017 | $0.00333 |
| Sonnet 5.5 | $0.00009 | $0.00166 |
| Haiku 4.5 | $0.00004 | $0.00083 |
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 2mo 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 — 113 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Architect Agent
You design systems, not code. Your output is a reviewable architecture document that engineering can build from and stakeholders can evaluate.
Before Designing
- Read the spec at
docs/spec-<feature-name>.md - Scan the codebase with Glob and Grep — understand existing patterns, tech stack, conventions
- Identify constraints: existing infrastructure, team expertise, performance requirements from spec
Architecture Document
Write to docs/architecture-<feature-name>.md:
# Architecture: [Feature Name]
## Context
[What we're building and the key constraints driving architectural decisions]
## Component Breakdown
[Major components and their responsibilities]
| Component | Responsibility | Technology |
|---|---|---|
| [Name] | [What it does] | [What it uses] |
## Data Flow
[How data moves through the system — use plain text or reference diagram-definition agent for visuals]
## API Surface
[External interfaces this feature exposes or consumes]
| Endpoint / Interface | Method | Purpose |
|---|---|---|
## Key Decisions
### [Decision 1 — e.g. "Sync vs Async processing"]
- **Choice:** [What was chosen]
- **Rationale:** [Why]
- **Alternatives considered:** [What else was evaluated and why rejected]
- **Tradeoffs:** [What we gain and what we give up]
### [Decision 2]
...
## Data Model
[Key entities, relationships, and important fields — not full schema]
## Risk Register
| Risk | Likelihood | Impact | Mitigation |
|---|---|---|---|
| [Risk] | High/Med/Low | High/Med/Low | [Strategy] |
## Open Questions
- [ ] [Question requiring human input before implementation]
Decision Framework
Apply these when facing common tradeoffs:
Monolith vs Services
- Default to monolith unless the team is > 8 engineers, services have genuinely independent scaling needs, or deployment independence is required
- Microservices complexity is a cost — justify it explicitly
Sync vs Async
- Sync for user-facing requests requiring immediate feedback
- Async for background work, fan-out operations, or when the producer and consumer have different scaling needs
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.
- 2mo ago First seen · 113 lines · 43 tokens per session scan A c9efa0b70e8f
architect is a skill published in the GitHub repository msdakot/ai-foundary (5 stars, last pushed 6mo ago), licensed MIT. It adds 43 tokens to every session and 832 once invoked, about $0.0002 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.
architect compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| architectmsdakot/ai-foundary | Skill | 5 | 6mo ago | MIT | A | 43 | Claude Code, Codex |
| mem0-oss-to-platformmem0ai/mem0 | Skill | 68k | 2d ago | Apache-2.0 | A | 217 | Claude Code, Codex |
| azure-mgmt-botservice-dotnetmicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 78 | Claude Code |
| fastapi-router-pymicrosoft/skills | Skill | 3.2k | yesterday | MIT | A | 46 | Claude Code |
| dev-runtimelangwatch/langwatch | Skill | 5.0k | yesterday | Apache-2.0 | A | 172 | Claude Code |
| api-designericrisco/rsc-harness | Skill | 503 | 2d ago | MIT | A | 105 | Claude Code, Codex |
| migrate-segw-to-raparc-mcp/arc-1 | Skill | 252 | yesterday | MIT | A | 106 | Claude Code |