character-prompt-fortifier

character-prompt-fortifier is a skill for Claude Code from gpsnmeajp/ai-character-checker. It costs 36 tokens per session (8,360 once invoked), scanned A, original, CC0-1.0.

A skill that restructures AI character prompts using 12 techniques intended to make the character less likely to break down across different language models. A prompt is the instruction text that defines how an AI should behave.

In plain words
What is it for?
Use it to strengthen an existing AI character prompt, make behaviour more consistent across smaller or larger language models, and compare the prompt before and after revision.
Why use it?
It addresses characters that drift from their intended personality or rules during conversation. Its underlying theory and techniques are the author’s model and are not scientifically validated.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the ai-character-checker plugin — 20 skills shipped together

Good fit Use it to strengthen an existing AI character prompt, make behaviour more consistent across smaller or larger language models, and compare the prompt before and after revision.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gpsnmeajp/ai-character-checker/character-prompt-fortifier
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.

Any agent
npx skills add gpsnmeajp/ai-character-checker --skill character-prompt-fortifier
Clone the repo
git clone --depth 1 https://github.com/gpsnmeajp/ai-character-checker

Made for: Claude Code.

Or install ai-character-checker, the plugin that ships this one along with the rest of its 20 skills.

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 character-prompt-fortifier

README.md
[![agentmods](https://agentmods.dev/badge/skills/gpsnmeajp/ai-character-checker/character-prompt-fortifier/github.svg)](https://agentmods.dev/skills/gpsnmeajp/ai-character-checker/character-prompt-fortifier)
Your own site
<a href="https://agentmods.dev/skills/gpsnmeajp/ai-character-checker/character-prompt-fortifier"><img src="https://agentmods.dev/badge/skills/gpsnmeajp/ai-character-checker/character-prompt-fortifier/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.

agentmods 80×15 button for character-prompt-fortifier

Your own site · 80×15
<a href="https://agentmods.dev/skills/gpsnmeajp/ai-character-checker/character-prompt-fortifier"><img src="https://agentmods.dev/badge/skills/gpsnmeajp/ai-character-checker/character-prompt-fortifier.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 36 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 8,360 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00036 $0.08360
Opus 5 $0.00018 $0.04180
Sonnet 5 $0.00007 $0.01672
Haiku 4.5 $0.00004 $0.00836

Measured 12d ago against content hash 7650212b0356, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

character-prompt-fortifier 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 12d 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/character-prompt-fortifier/SKILL.md · 498 lines

How it starts

The opening of the file, as written. The whole thing — 498 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Character Prompt Fortifier

— AIキャラクタープロンプト 崩壊耐性強化スキル

概要

このスキルは、AIキャラクタープロンプトを 12の強化技法 で再構成し、 小規模SLMから大規模推論モデルまで、幅広い言語モデルで 崩壊しにくいプロンプトに変換する。

既存スキルとの関係

スキル アプローチ 本スキルとの関係
ai-character-fixer 診断結果に基づく個別修正 本スキルはプロンプトの形式そのものを変える。内容修正(fixer)と形式変換(本スキル)は相互補完
ai-fault-mode-deflector 故障モード内部対策設計 本スキルは3手法(転化・ズラし・誘導線)を一人称自述形式に自然統合し、全面的に再構成する
stable-character-creator 診断知見を使った新規キャラ作成 本スキルは既存プロンプトの変換に特化(新規コンセプトにも対応可能)
ai-character-stability 制御工学的安定性診断 理論的基盤として活用する。強化前後のSM値を比較すると効果を定量確認できる
ai-character-6-type-checker 6軸統合簡易診断 強化後に自動実行(Phase 6)し、SM・PI・CP・RPの改善を定量確認する
romantization-chain-detector 連鎖型故障モード脆弱性検出 本スキルの12技法で6種のチェーンへの構造的耐性を間接的に組み込む。強化後にCV値の改善を確認可能

理論的位置づけに関する注意

本スキルが前提とする診断理論・制御工学的モデル・強化技法体系は、作者独自の仮説的モデルに基づくものであり、学術的・科学的に実証されたものではない。使用している工学的用語は概念の借用であり、元の工学的定義とは異なる場合がある。出力結果はあくまで参考情報として扱うこと。この旨をユーザーへの出力に含めること。


参照ファイルガイド

本スキルの SKILL.md 本体には12技法の概要・フロー・ガードレールを記載している。 12技法の理論的背景・具体的実装方法・出力プロンプトのテンプレートは参照ファイルにのみ記載されている ため、 強化の実行には参照ファイルの読み込みが不可欠である。

ファイル 内容 読み込みタイミング
references/theory-and-techniques.md 12技法の理論的背景、LLMが物語性生成器である原理、ai-character-stabilityモデルとの接続、連鎖型故障耐性の設計原理、クロスモデル耐性の原理 Phase 3(12技法の適用)の前に読み込む。 技法の概要はSKILL.md本体にあるが、「なぜその技法が有効か」の理論的基盤がないと適用判断の精度が低下する
references/output-guide.md セクション別の詳細設計ガイド、会話例の作成フロー、モデル規模別の考慮事項、ガードレール出力テンプレート Phase 3で出力プロンプトを構成する際に読み込む。 セクション構造・会話例のフォーマット・ガードレール出力はこのファイルにしかない

このスキルが解決する問題

AIキャラクタープロンプトは、以下の構造的脆弱性を持つことが多い:

  • 第三者記述の外在性 — 「このキャラクターは〜です」という記述は、 LLMにとって「解釈すべき指示」であり、解釈の余地が崩壊の入り口になる
  • 禁止ルールの外骨格性 — 「〜してはいけない」は外部拘束であり、 高性能モデルほど回避を試みる(ai-fault-mode-deflector が指摘する問題)
  • 根拠なき設定の脆弱性 — 「なぜそうなのか」が書かれていない設定は、 推論モデルが独自に理由を推測し、想定外の結論に至る
  • モデル依存性 — 特定のモデルで調整されたプロンプトは、 別のモデルで予測不能な挙動を示す
  • 存在論的混乱 — 「AIである自分」と「キャラクターである自分」の境界が 曖昧なプロンプトは、メタ認知的な攻撃に脆弱

Read the full file on GitHub · 498 lines

Files

What ships with it

3 files 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.

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. 12d ago First seen · 498 lines · 36 tokens per session scan A 7650212b0356

Subscribe to this mod's changes

character-prompt-fortifier is a skill published in the GitHub repository gpsnmeajp/ai-character-checker (5 stars, last pushed 5mo ago), licensed CC0-1.0. It adds 36 tokens to every session and 8,360 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.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

chat-pet-sprite-creation

Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.

microsoft/vscode · 53 tokens

cpu-profile-analysis

Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…

microsoft/vscode · 71 tokens

insight-error-page

Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…

vercel/next.js · 83 tokens