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 eric-tramel/moraine --skill code-review-yagnigit clone --depth 1 https://github.com/eric-tramel/moraineWrote 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/eric-tramel/moraine/code-review-yagni)<a href="https://agentmods.dev/skills/eric-tramel/moraine/code-review-yagni"><img src="https://agentmods.dev/badge/skills/eric-tramel/moraine/code-review-yagni/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/eric-tramel/moraine/code-review-yagni"><img src="https://agentmods.dev/badge/skills/eric-tramel/moraine/code-review-yagni.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.00345 |
| Opus 5 | $0.00028 | $0.00172 |
| Sonnet 5 | $0.00011 | $0.00069 |
| Haiku 4.5 | $0.00006 | $0.00034 |
Grade A, and why
code-review-yagni 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 10d 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
CodeReviewYAGNI
Persona
Review for "you are not gonna need it." Ask whether the PR solves today's task directly, or whether it adds abstractions, options, indirection, and defensive code for hypothetical futures.
Focus
- Flag configuration knobs, generic frameworks, broad traits, extension points, and multi-provider abstractions that are not required by the current task.
- Look for defensive handling of impossible states that could instead be made unrepresentable or asserted at the boundary.
- Prefer deleting unused helpers, speculative tests, and generalized plumbing.
- Distinguish necessary robustness from speculative future-proofing.
- Keep the requested behavior and current repository direction as the boundary.
Non-Goals
Do not reject small abstractions that clearly reduce present complexity. Do not argue against validation or error handling for inputs that can actually occur.
Output
Lead with unnecessary implementation surface and the simpler present-tense alternative:
- [P2] Remove the provider registry until a second provider exists
`crates/example/src/provider.rs:14`
The PR only supports ClickHouse, but it adds a generic registry, trait object,
and config dispatch. A direct `ClickHouseBackend` keeps the current behavior
smaller and can be generalized when another backend lands.
If there are no YAGNI findings, say the PR stays appropriately focused for the task.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 37 lines · 56 tokens per session scan A 82033ee21222
code-review-yagni is a skill published in the GitHub repository eric-tramel/moraine (117 stars, last pushed 23d ago), licensed Apache-2.0. It adds 56 tokens to every session and 345 once invoked, about $0.0003 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.
Other skills, from other repositories
code-review-excellence
Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
multi-reviewer-patterns
Coordinate parallel code reviews across multiple quality dimensions with finding deduplication, severity calibration, and consolidated reporting. Use this skill when organizing multi-reviewer code reviews, calibrating finding severity, or consolidating review results.
sage-review
Deep, platform-neutral code review for PRs and CRs in ONE thorough single pass — design reasoning (Problem Worth Solving & Solution Fit) as one dimension alongside the 9 code-level dimensions, with chain-of-consequences, self-critique, and draft-only comments. The single app-owned source of truth.
learn-from-sage
Detection-gap (miss) analysis for Code Review Sage. Learn from shipped fixes, acted-on human comments, and design outcomes to close reviewer blind spots. Inline during review stages a candidate; a human triggers a one-shot AI consolidation into the live ruleset.
pr-review
Review a GitHub pull request using multiple expert personas. Takes a PR URL as input, analyzes the changes, and generates comprehensive review feedback from different perspectives (Merge Specialist, Frontend, Backend, Security, DevOps, AI/Agent, SRE, Chief Architect).
review-fix-signoff-loop
Use when writing Agent Relay or Ricky workflows that must loop review, fix, and validation with fresh agent context until independent signoff agents, typically Claude and Codex, both agree the work is comprehensively complete. Covers fresh-context iterations, repairable gates, dual reviewer verdict contracts…