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 agentmods add skills/agent-engineer-master/skill-engineer/security-mindset-masternpx skills add Agent-Engineer-Master/skill-engineer --skill security-mindset-mastergit clone --depth 1 https://github.com/Agent-Engineer-Master/skill-engineerWhat 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 | $0.00094 | $0.01925 |
| Opus 5 | $0.00047 | $0.00962 |
| Sonnet 5 | $0.00019 | $0.00385 |
| Haiku 4.5 | $0.00009 | $0.00193 |
Grade C, and why
security-mindset-master scanned grade C with 1 finding 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 2d 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.
Hidden instructionshighPrompt injection
Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.
<!-- Built with Agent Engineer Master — get your own production-ready skill: www.agentengineermaster.com/skill-engineer --> How it starts
The opening of the file, as written. The whole thing — 143 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Security Mindset Master
Overview
Security is a design constraint. Not a checklist. Not a phase. Not someone else's job.
Core principle: Think like an attacker during implementation. Reasoning about threats after the code is written is too late — you've already chosen the unsafe path.
Violating the letter of this rule is violating the spirit of this rule.
The Iron Law
NO ENDPOINT, DATA ACCESS PATTERN, OR USER INPUT HANDLER SHIPS WITHOUT A SECURITY ANALYSIS FIRST
The insecure path must never be the path of least resistance.
When to Use
Always — before writing code that touches:
- API endpoints (new or modified)
- Authentication or authorization logic
- Database queries or ORM calls
- User input of any kind
- Session tokens, JWTs, API keys
- File uploads or downloads
- Webhooks or callbacks
- Any feature that stores or transmits user data
Not for:
- Read-only documentation changes
- Infrastructure config unrelated to data flow
- Dependency version bumps with no logic changes
Thinking "this is a small change, security analysis is overkill"? That's rationalization. Small changes to auth logic have caused the largest breaches.
Phase 1: Threat Surface Analysis
Complete before writing any code.
Answer these questions explicitly — not in your head, in the response:
- Who can call this? — authenticated users only? anonymous? other services? what roles or permissions?
- What data does it touch? — classify sensitivity: PII, credentials, financial, internal-only, public
- What trust boundaries does it cross? — user → server, server → DB, server → external API, internal → internal
- Worst-case malicious caller — if an attacker controls this input, what's the most damaging thing they could make the system do?
- What if inputs are malformed? — empty, null, max-length exceeded, unexpected type, Unicode edge cases
- What if a request is replayed? — is the same request sent twice dangerous? is there idempotency protection?
- What if the caller substitutes another user's identifier? — can they access or modify another user's data?
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.
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.
- 2d ago First seen · 143 lines · 94 tokens per session scan C 031585033c24
security-mindset-master is a skill published in the GitHub repository Agent-Engineer-Master/skill-engineer (8 stars, last pushed 1mo ago), licensed MIT. It adds 94 tokens to every session and 1,925 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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openspec-new-change
Start a new OpenSpec change using the experimental artifact workflow. Use when the user wants to create a new feature, fix, or modification with a structured step-by-step approach.
writing
将共享历史中的已验证事实和计算结果整理成符合受众、格式与长度约束的成稿。.
extract
Run the full Semantica semantic extraction pipeline on a file or selected text — NER, relations, events, coreference resolution, triplets, and validation. Clears result cache before each run. Returns Markdown tables with entity/relation/event/triplet results and inline validator warnings.
gsd-audit-milestone
Audit milestone completion against original intent before archiving.
kayba-stage-7-fixer
Implement the approved fixes from the action plan and log all changes. Trigger when the user says "run stage 7", "implement fixes", "apply action plan", or when invoked by the kayba-pipeline orchestrator. Requires eval/actionplan.md to exist.