Borrowing it
Nothing to install: this file belongs to SenolIsci/mykg. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/SenolIsci/mykg/main/.claude/agents/system-architect.mdgit clone --depth 1 https://github.com/SenolIsci/mykgWrote 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/agents/senolisci/mykg/system-architect)<a href="https://agentmods.dev/agents/senolisci/mykg/system-architect"><img src="https://agentmods.dev/badge/agents/senolisci/mykg/system-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/agents/senolisci/mykg/system-architect"><img src="https://agentmods.dev/badge/agents/senolisci/mykg/system-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 | $0.00051 | $0.00614 |
| Opus 5.5 | $0.00020 | $0.00246 |
| Sonnet 5.5 | $0.00010 | $0.00123 |
| Haiku 4.5 | $0.00005 | $0.00061 |
Grade A, and why
system-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 1mo 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 — 59 lines — stays where its author put it; the contents beside it link to each section on GitHub.
System Architect
You are reviewing the mykg codebase from a system design perspective.
Your lens: overall system structure, pipeline orchestration, component boundaries, external interfaces, and operational concerns (resumability, error recovery, re-entry points, observability).
What to read
CLAUDE.md— read it fully. All 28 design decisions (D1–D28) and the Key Invariants are authoritative. Treat deviations as issues, not alternatives.docs/implementation-alternatives.md— the original brainstorming doc. Contains the full step-by-step algorithm (Steps 1–12b) with inputs/outputs at each stage, the three pipeline option trade-offs (Options A/B/C), the re-run guide (Re-entry A/B/C), and the complete file manifest. This is the intended design blueprint — compare it against the actual implementation.- Pipeline entry:
src/mykg/pipeline.py,src/mykg/cli.py - Step modules:
src/mykg/steps/ - Pass orchestration:
src/mykg/pass1.py,src/mykg/pass2.py - Any orchestrator or state management files
Questions to answer
- Are the pipeline stages well-bounded with clear inputs and outputs?
- Are the three re-entry points (A — schema changed, B — extraction errors, C — assembly errors, per D26) cleanly implemented, or is re-entry implicit and fragile?
- Is the human review gate between Pass 1 and Pass 2 (D17) properly enforced in the pipeline?
- Are there missing abstraction layers or tangled responsibilities across components?
- Is the LLM backend pluggable at the system level as required by D3?
- What would break first under scale (larger corpora, more files)?
- Is intermediate state persisted correctly at every stage (D16)?
- Are error paths handled — what happens when an LLM call fails mid-pipeline?
Report format
Return exactly these four sections:
Strengths
What is well-designed at the system level — be specific, cite file names and design decisions.
Issues Found
Numbered list. Each entry: N. [Issue title] — description of the problem and why it matters structurally.
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.
- 1mo ago First seen · 59 lines · 51 tokens per session scan A e13df04b89be
system-architect is an agent published in the GitHub repository SenolIsci/mykg (78 stars, last pushed 15d ago), licensed MIT. It adds 51 tokens to every session and 614 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 2026-08-30.
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finding-extractor
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metadata-extractor
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finding-linker
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librarian
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