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/beevibe-ai/beevibe-cto/principlesgit clone --depth 1 https://github.com/beevibe-ai/beevibe-ctoWrote 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/commands/beevibe-ai/beevibe-cto/principles)<a href="https://agentmods.dev/commands/beevibe-ai/beevibe-cto/principles"><img src="https://agentmods.dev/badge/commands/beevibe-ai/beevibe-cto/principles.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 | $0.00092 | $0.01277 |
| Opus 5 | $0.00046 | $0.00639 |
| Sonnet 5 | $0.00018 | $0.00255 |
| Haiku 4.5 | $0.00009 | $0.00128 |
Grade A, and why
principles 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 6d 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 — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/adr:principles — Discover the team's code-review principles
Use when the user wants the bot to learn their team's conventions so PR review can cite the team's own code as the reference.
Step 1 — Check the environment
npx -y --package=github:beevibe-ai/beevibe-cto adr-doctor
adr principles only needs an LLM provider (no web search). If that one is missing, invoke /adr:doctor.
Step 2 — Set expectations, then run
Before calling the tool, tell the user EXACTLY what's about to happen — the tool runs for 2-4 minutes with no other visible output, so without this the user just sees a spinner.
Print something like:
Running principles discovery on the repo. This takes ~2-4 minutes and runs in five steps:
- Scan the repo (files, manifests, docs) — instant
- Sample ~24 representative source files — instant
- Extract product intent + discover review lenses (parallel LLM, ~15s)
- Per-lens pattern extraction (parallel LLM, ~30s)
- Consolidate + cite-verify + write
.adr/principles.{md,json}(~30s)Cost: ~$0.15 on gpt-4.1-mini. You'll see the result when it's done.
THEN call the adr_principles MCP tool with non_interactive: true:
{
"repo_path": ".",
"non_interactive": true
}
The MCP server emits notifications/message for every step, and notifications/progress when the client opts in via _meta.progressToken. Some clients surface these in the spinner; others don't. Either way the upfront step list gives the user something to read.
The tool returns the lenses, the per-lens patterns, AND the product intent block (identity, architectural_intent, product_philosophy, non_goals). The full content lives in .adr/principles.{md,json} on disk.
Step 3 — Show the user what we found
Read .adr/principles.json to see the full structure. Then show the user — lead with the product portrait, NOT the lint rules:
- What this is — the
identityfield. One sentence on what the product actually is. - Architectural intent — the 3-6 foundational decisions from
architectural_intent. Each with itswhyand the files cited. - Product philosophy — the 3-6 recurring design principles from
product_philosophy. These are the team's voice — quote verbatim where pulled from CLAUDE.md / AGENTS.md. - Non-goals — what the team explicitly chose NOT to do. Often the most telling part.
- Code-level lenses + their principles — show top 2-3 strongest per lens, with team
file:linecitations.
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.
- 6d ago First seen · 94 lines · 92 tokens per session scan A 073c284dc1e7
principles is a command published in the GitHub repository beevibe-ai/beevibe-cto (105 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 92 tokens to every session and 1,277 once invoked, about $0.0005 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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