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 storyAura/lora-tagging-skills --skill character-tag-auditorgit clone --depth 1 https://github.com/storyAura/lora-tagging-skillsWrote 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/storyaura/lora-tagging-skills/character-tag-auditor)<a href="https://agentmods.dev/skills/storyaura/lora-tagging-skills/character-tag-auditor"><img src="https://agentmods.dev/badge/skills/storyaura/lora-tagging-skills/character-tag-auditor/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/storyaura/lora-tagging-skills/character-tag-auditor"><img src="https://agentmods.dev/badge/skills/storyaura/lora-tagging-skills/character-tag-auditor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00034 | $0.03212 |
| Opus 5 | $0.00017 | $0.01606 |
| Sonnet 5 | $0.00007 | $0.00642 |
| Haiku 4.5 | $0.00003 | $0.00321 |
Grade A, and why
character-tag-auditor 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 11d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Character LoRA Tag Auditor
Return every supplied original tag exactly once with one decision: keep, delete, replace, or uncertain. Never alter the original tag field. Put a normalized target only in replacement_tag. The locked trigger is always keep, is included in the final prompt, and has prompt order 0.
Categories and hard boundary
Use exactly one category: identity, hair, eyes, face, body, clothing, footwear, legwear, wearable_accessory, action, pose, expression, scene, composition, quality, object, or other.
Only hair, eyes, face, body appearance, clothing, footwear, legwear, and wearable accessories may be deleted or replaced. Identity/trigger tags, actions, poses, expressions, scenes/backgrounds, composition/camera terms, quality/style terms, ordinary objects, and other categories are protected: always keep them in dataset files and never replace them. Protected does not mean “include in the character prompt”; these tags normally use include_in_prompt: false.
Decision meanings
keep: the original tag is correct and already useful.delete: the original appearance/wearable tag is incorrect, conflicting, redundant, or non-core under the selected style.replace: the feature is correct, but the supplied tag is imprecise or redundantly split; provide one visually confirmed canonical target.uncertain: visual evidence is insufficient. This is safety-preserving and must not modify files.
A replacement target must be one tag: nonempty, different from its source, and without commas, line breaks, or control characters. Never produce a replacement chain or cycle. Several sources may map to one canonical target; the caller keeps its earliest original position.
If a replacement target equals the source because the original tag is already canonical, return keep with an empty replacement_tag. Never use replace merely to confirm or deduplicate an unchanged tag.
Sparse mode (default)
Keep only the current character's core identity: subject identity/count, stable eye and hair traits, signature garments, footwear, and wearable accessories. Delete incorrect/conflicting tags and non-core appearance or wearable detail.
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.
- 11d ago First seen · 122 lines · 34 tokens per session scan A e63428dd92b6
character-tag-auditor is a skill published in the GitHub repository storyAura/lora-tagging-skills (3 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 3,212 once invoked, about $0.0002 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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