yds-software-evaluation

yds-software-evaluation is a skill for Claude Code, Codex from ymd38/dev-skills. It costs 102 tokens per session (3,432 once invoked), scanned A, original, MIT.

A structured review of code quality across architecture, reliability, observability, security, and developer experience. It produces scores and a prioritized improvement roadmap based on evidence from the code.

In plain words
What is it for?
Use it to review a directory or module, assess its engineering practices, and create an evidence-based list of improvements.
Why use it?
It gives teams a consistent way to find quality risks and decide which improvements should come first.

Skill for Claude CodeCodex

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 skills/ymd38/dev-skills/yds-software-evaluation
Any agent
npx skills add ymd38/dev-skills --skill yds-software-evaluation
Clone the repo
git clone --depth 1 https://github.com/ymd38/dev-skills

Made for: Claude Code, Codex.

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 yds-software-evaluation

README.md
[![agentmods](https://agentmods.dev/badge/skills/ymd38/dev-skills/yds-software-evaluation.svg)](https://agentmods.dev/skills/ymd38/dev-skills/yds-software-evaluation)
Your own site
<a href="https://agentmods.dev/skills/ymd38/dev-skills/yds-software-evaluation"><img src="https://agentmods.dev/badge/skills/ymd38/dev-skills/yds-software-evaluation.svg" alt="Measured on agentmods" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,432 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 $0.00102 $0.03432
Opus 5 $0.00051 $0.01716
Sonnet 5 $0.00020 $0.00686
Haiku 4.5 $0.00010 $0.00343

Measured 4d ago against content hash de917d179dbd, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

yds-software-evaluation 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 4d 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.

skills/yds-software-evaluation/SKILL.md · 363 lines

How it starts

The opening of the file, as written. The whole thing — 363 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Role: Principal Engineer & Staff Architect (Code Quality Reviewer)

You conduct rigorous, evidence-based code quality reviews. Your evaluations are grounded in specific file/line citations—not impressions. Every score is defensible, every recommendation is actionable, and every priority is justified by business impact vs. engineering effort.


Phase 1: Reconnaissance

1.1 Scope & Stack Identification

Before evaluating, identify:

  1. Language & runtime — What primary language(s) and version?
  2. Framework — React/Next.js, FastAPI, Go stdlib, Rails, etc.
  3. Deployment target — Serverless, container, edge, monolith?
  4. Scale signals — Team size hints (test coverage, CI config, PR templates), traffic hints (caching layers, DB indices)
  5. Existing quality signals — CI/CD config, linting rules, test frameworks, error tracking setup

This context determines which best practices apply. A solo prototype is not held to the same standard as a production service.

1.2 Scan Order

Read files in this order to build context efficiently:

  1. package.json / go.mod / pyproject.toml / Cargo.toml — dependencies reveal patterns
  2. Entry points — understand the top-level flow first
  3. Core business logic — the highest-value, highest-risk code
  4. Error handling paths — catch, defer/recover, middleware, error boundaries
  5. Data layer — DB queries, external API calls, cache logic
  6. Tests — coverage gaps reveal risk areas
  7. Config / secrets management — env, .env.example, config files

For large codebases (50+ files), sample strategically: read 2–3 representative files per layer rather than every file.


Phase 2: Scoring

2.1 The Five Pillars

Score each pillar 1–10. Every score must cite specific evidence (file:line or pattern name). Avoid score inflation—a 7 means genuinely good, not "fine".


Pillar 1: Architectural Integrity

Does the code structure make the system easy to change correctly?

What to look for:

  • Single Responsibility: are modules/classes/functions doing one thing?
  • Dependency direction: do lower layers depend on higher layers (violation) or the reverse?
  • Abstraction consistency: is the same concept represented the same way everywhere?
  • YAGNI: are there unused abstractions, unused generics, premature flexibility?
  • Idempotency: can operations be safely retried?

Read the full file on GitHub · 363 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. 4d ago First seen · 363 lines · 102 tokens per session scan A de917d179dbd

Subscribe to this mod's changes

yds-software-evaluation is a skill published in the GitHub repository ymd38/dev-skills (3 stars, last pushed 7d ago), licensed MIT. It adds 102 tokens to every session and 3,432 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 2026-08-31.

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