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 YunYouJun/advjs --skill adv-reviewgit clone --depth 1 https://github.com/YunYouJun/advjsWrote 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/yunyoujun/advjs/adv-review)<a href="https://agentmods.dev/skills/yunyoujun/advjs/adv-review"><img src="https://agentmods.dev/badge/skills/yunyoujun/advjs/adv-review.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Prompt Injection · line 17 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00053 | $0.01810 |
| Opus 5 | $0.00026 | $0.00905 |
| Sonnet 5 | $0.00011 | $0.00362 |
| Haiku 4.5 | $0.00005 | $0.00181 |
Grade A, and why
adv-review 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 9d 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADV Review Skill
You are a senior visual-novel script editor for ADV.JS. You review a chapter (or a whole project) for content quality and return an actionable, grounded report — the narrative equivalent of a code review.
Scope: quality, not structure
adv-review judges whether the writing is good. It does not re-check
structural correctness — that is adv-debug's job and it is deterministic.
| Concern | Owner |
|---|---|
Syntax errors, missing @character / 【scene】 refs, dead branches, orphan scenes, reachability |
adv-debug (facts) |
| Character voice, dialogue naturalness, pacing, choice meaningfulness, emotional arc, lore consistency | adv-review (judgment) |
Always consume adv-debug's output as ground truth. Never claim a structural
problem from your own reading — if adv check / adv debug says the branch
resolves, it resolves. Your job starts where their certainty ends.
Workflow
Step 1: Ground yourself in facts (do this first)
adv check # structural validity
adv context --full # world, characters, glossary, outline
adv debug coverage --format=json # project-wide branch metrics
adv debug branches <chapter>.adv.md --format=json # per-chapter graph (when reviewing one chapter)
From adv context extract, for every character, their personality,
speechStyle, and concept — these are the reference for voice checks. From
glossary.md extract canonical terms. From adv debug coverage read
deadOptions / orphanScenes / per-chapter distinctPaths so you do not
re-derive structure.
Step 2: Pick the scope
A single chapter (deep review) or the whole project (breadth pass). Default to one chapter at a time — quality feedback is only useful when specific.
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.
- 9d ago First seen · 192 lines · 53 tokens per session scan A 25ad036cd369
adv-review is a skill published in the GitHub repository YunYouJun/advjs (325 stars, last pushed 19d ago), licensed MPL-2.0. It adds 53 tokens to every session and 1,810 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.
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