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 commands/cdeust/ai-architect-mcp-codebase/rungit clone --depth 1 https://github.com/cdeust/ai-architect-mcp-codebaseWhat 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 | $0.00000 | $0.00170 |
| Opus 5 | $0.00000 | $0.00085 |
| Sonnet 5 | $0.00000 | $0.00034 |
| Haiku 4.5 | $0.00000 | $0.00017 |
Grade A, and why
run 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.
What it actually says
Run Skill
Execute a registered skill by name. The skill's procedure, zetetic gates, and output format guide the execution.
Instructions
-
Parse: first word is the skill name, rest is the input/arguments.
-
Resolve the skill file:
tools/skill-runner.sh <skill-name>If not found, list available skills and ask the user to choose. -
Read the resolved skill file. Follow its Procedure section step by step.
-
Before delivering output, check every Zetetic Gate. If any gate fails, report the failure and stop — do not produce partial output that bypasses a gate.
-
After output, check the Hand-offs section. If a hand-off condition is met, suggest the next skill to the user.
$ARGUMENTS
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 · 19 lines · 0 tokens per session scan A 85025bc5e860
run is a command published in the GitHub repository cdeust/ai-architect-mcp-codebase (4 stars, last pushed 3d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 170 tokens. 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.
Other commands, from other repositories
rb-setup
First-time setup. Configure the LLM API key, or a no-API-key local host runner (Codex / Trae / Claude / any headless CLI) that RepoBrain uses for codebase Q&A and refresh. / 首次 setup，配置 RepoBrain 代码问答与 refresh 所需的 LLM API key，或无需 API key 的本地 host runner（Codex / Trae / Claude / 任意无头 CLI）。.
generate-component
Generate Angular standalone component with tests.
pack-repo
Pack la codebase en un fichier AI-friendly (Repomix wrapper + fallback shell). Token counting inclus.
deploy
Build, test, deploy with staged rollout.
simplify
Reduce complexity without changing behavior — code simplification.
coograph-verify
Verify that the described work is complete and correct. Provide evidence for every claim. You verify — you do not implement or fix style.