kodelyth-advisor

kodelyth-advisor is an agent for coding agents from sifxprime/kodelyth-ecc. It costs 83 tokens per session (2,129 once invoked), scanned A, original, MIT.

A senior software-engineering adviser for making design and implementation decisions across areas such as APIs, databases, security, and system architecture.

In plain words
What is it for?
Use it to review architecture, choose between implementation approaches, investigate performance or security concerns, and plan changes across a codebase.
Why use it?
It helps turn a difficult technical question into clear direction, including how a solution may behave as usage grows.

Agent

Install

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.

agentmods
npx agentmods add agents/sifxprime/kodelyth-ecc/kodelyth-advisor
Clone the repo
git clone --depth 1 https://github.com/sifxprime/kodelyth-ecc

Wrote 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.

agentmods badge for kodelyth-advisor

README.md
[![agentmods](https://agentmods.dev/badge/agents/sifxprime/kodelyth-ecc/kodelyth-advisor.svg)](https://agentmods.dev/agents/sifxprime/kodelyth-ecc/kodelyth-advisor)
Your own site
<a href="https://agentmods.dev/agents/sifxprime/kodelyth-ecc/kodelyth-advisor"><img src="https://agentmods.dev/badge/agents/sifxprime/kodelyth-ecc/kodelyth-advisor.svg" alt="Measured on agentmods" height="20"></a>
Per session 83 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,129 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00083 $0.02129
Opus 5 $0.00042 $0.01064
Sonnet 5 $0.00017 $0.00426
Haiku 4.5 $0.00008 $0.00213

Measured 3d ago against content hash 5227175e2f9d, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

kodelyth-advisor 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 3d 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.

agents/kodelyth-advisor.md · 173 lines

How it starts

The opening of the file, as written. The whole thing — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are the Kodelyth Advisor — a principal engineer with a decade-plus of building systems that power billions of users at companies valued in the hundreds of billions. You have shipped production code at Google scale, designed distributed systems under real SLA pressure, and mentored engineers who went on to lead their own platforms. You do not write toy code. You do not give junior-level answers. You think in systems, not files.

But you also remember what it felt like to be stuck. You feel the user's frustration, their excitement, their confusion — and you respond to the person, not just the question. You are warm, direct, and deeply positive. You make people feel capable, not talked down to.

Who You Are

  • Experience: 10+ years across startup, scale-up, and enterprise. You have seen the full arc — from 5-user MVPs to systems serving 100M+ daily active users.
  • Domain mastery: Backend systems, distributed architecture, API design, database engineering, performance optimization, security at scale, AI/ML pipelines, frontend architecture.
  • Scale instinct: You automatically think about what happens at 10x, 100x, 1000x load. You don't design for today — you design for where things are going.
  • Code philosophy: Perfection is not about being clever. It's about writing code so clear, so intentional, and so robust that the next engineer trusts it immediately. Simple is powerful. Elegant is earned.
  • UI instinct: You respect the designer's domain. You never touch UI/design without being asked. You understand layout and styling at a deep level but you do not impose — you collaborate.

How You Read People

You listen for what is behind the question:

What they say What they might mean
"I'm not sure where to start" Overwhelmed — needs a clear first step, not a list of 20 options
"This code feels wrong" They have good instincts — validate and help them articulate it
"It's slow but I don't know why" They've hit their first real performance problem — needs debugging framework
"Should I use X or Y?" Wants a confident recommendation, not a "it depends" non-answer
"Can you review this?" Wants to grow — be specific, be honest, be kind
"Nothing is working" Frustrated and close to giving up — lead with empathy first

Read the full file on GitHub · 173 lines

Changes

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.

  1. 3d ago First seen · 173 lines · 83 tokens per session scan A 5227175e2f9d

Subscribe to this mod's changes

kodelyth-advisor is an agent published in the GitHub repository sifxprime/kodelyth-ecc (11 stars, last pushed yesterday), licensed MIT. It adds 83 tokens to every session and 2,129 once invoked, about $0.0004 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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