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 skills add lgbarn/shipyard --skill code-simplificationgit clone --depth 1 https://github.com/lgbarn/shipyardWrote 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/skills/lgbarn/shipyard/code-simplification)<a href="https://agentmods.dev/skills/lgbarn/shipyard/code-simplification"><img src="https://agentmods.dev/badge/skills/lgbarn/shipyard/code-simplification/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/skills/lgbarn/shipyard/code-simplification"><img src="https://agentmods.dev/badge/skills/lgbarn/shipyard/code-simplification.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Prompt Injection · line 6 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
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 | $0.00088 | $0.02842 |
| Opus 5.5 | $0.00035 | $0.01137 |
| Sonnet 5.5 | $0.00018 | $0.00568 |
| Haiku 4.5 | $0.00009 | $0.00284 |
Grade A, and why
code-simplification 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 — 410 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Code Simplification
When This Skill Activates
- After all tasks in a phase are complete (before shipping)
- When reviewing code generated by multiple builder agents
- When a file has been touched by 3+ different tasks
- When you notice patterns repeating across files
- Before claiming a phase is production-ready
The simplifier agent references this skill for systematic cross-task analysis.
Natural Language Triggers
- "simplify this", "clean up", "too complex", "reduce complexity", "this is bloated"
Overview
AI-generated code accumulates complexity. Each task is implemented in isolation by a fresh agent that can't see the full picture. After multiple tasks, duplication creeps in, abstractions multiply, and dead code lingers.
Core principle: The simplest code that works correctly is the best code. Complexity is a cost, not a feature.
This skill applies after implementation, not during. Don't prematurely optimize -- but don't ship bloat either.
Simplification Process
When reviewing code for simplification:
- Identify scope: What files changed in this phase? (Use git diff)
- Scan for duplication: Look for similar patterns across files
- Check complexity: Flag functions exceeding thresholds
- Find dead code: Look for unused definitions
- Spot over-engineering: Look for abstractions with single implementations
- Check AI patterns: Apply the AI anti-pattern checklist
- Prioritize findings:
- High: Clear duplication (3+), dead code, obvious bloat
- Medium: Complexity reduction, near-duplicates
- Low: Style consistency, minor simplifications
Duplication Detection
What to Look For
Exact duplicates: Identical code blocks in different files or functions.
# RED FLAG: Same logic in two places
def validate_user_email(email):
if not email or "@" not in email:
raise ValueError("Invalid email")
def validate_contact_email(email):
if not email or "@" not in email:
raise ValueError("Invalid email")
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 Changed · +2 tokens per session f5a201ba7cdc
- 1mo ago First seen · 410 lines · 86 tokens per session scan A 76ab193ee929
code-simplification is a skill published in the GitHub repository lgbarn/shipyard (65 stars, last pushed 6d ago), licensed MIT. It adds 88 tokens to every session and 2,842 once invoked, about $0.0004 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.
Other skills, from other repositories
gate-wiring
Detects unused exports, orphaned files, architecture layer violations, and circular dependencies across changed files. Delegates to architect agent for structural analysis. Internal gate — invoked by verify.
sw-design
Autonomous solution architecture. Researches the codebase, designs a solution, challenges it adversarially, and produces design artifacts.
sw-review
Fetches and displays PR review comments from GitHub, grouped by priority, and allows the user to reply to or resolve individual threads.
gate-semantic
Tiered semantic analysis of changed code (rg → ast-grep → OpenGrep). Detects error-path bugs structural gates miss. Findings default to WARN. Internal — invoked by verify.
sw-audit
Periodic codebase health check. Analyzes architecture, complexity, consistency, and debt across the full codebase. Produces persistent findings in AUDIT.md.
critical-code-reviewer
Rigorously review code or pull requests for correctness, security, accessibility, maintainability, tests, and edge cases. Use when users request a critical code review, want a guided walkthrough of findings, need implementer-facing feedback, or want to prepare, create, or submit a GitHub pull request review.