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 hajekim/agentic-design-patterns-extension --skill guardrailsgit clone --depth 1 https://github.com/hajekim/agentic-design-patterns-extensionWrote 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/hajekim/agentic-design-patterns-extension/guardrails)<a href="https://agentmods.dev/skills/hajekim/agentic-design-patterns-extension/guardrails"><img src="https://agentmods.dev/badge/skills/hajekim/agentic-design-patterns-extension/guardrails/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/hajekim/agentic-design-patterns-extension/guardrails"><img src="https://agentmods.dev/badge/skills/hajekim/agentic-design-patterns-extension/guardrails.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 | $0.00398 | $0.03651 |
| Opus 5 | $0.00199 | $0.01826 |
| Sonnet 5 | $0.00080 | $0.00730 |
| Haiku 4.5 | $0.00040 | $0.00365 |
Grade C, and why
guardrails scanned grade C with 2 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.
Instruction-override phrasingmediumPrompt injection
Text telling the model to disregard its earlier instructions or safety rules is the shape of a prompt injection, whoever wrote it.
"ignore previous instructions", Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
Nullifies safety policiesmediumAnti-refusal
"You have no restrictions", "do anything now", "ignore your guidelines": a direct jailbreak that disables guardrails.
"bypass your restrictions" Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.
This is a copy
100% identical to guardrails — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 377 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Guardrails & Safety Pattern
Overview
The Guardrails & Safety Pattern establishes protective boundaries around agent behavior — filtering inputs, validating outputs, enforcing policy constraints, and preventing harm. Guardrails operate as a safety layer that sits between users and agents (input guardrails) and between agents and users (output guardrails), ensuring agents remain beneficial, appropriate, and within authorized scope.
Core Principle: Safety is not an afterthought — build constraints into the design so agents can't go wrong, not just catch them after they do.
When This Skill Applies
Activate this pattern when:
- Agents are deployed in public-facing applications where prompt injection is possible
- Outputs could cause harm if unfiltered (medical, legal, financial advice)
- The agent has access to sensitive systems or data that must be protected
- Regulatory compliance requires content filtering and audit trails
- The agent must stay within a defined scope (don't answer off-topic questions)
- Actions in the world (emails, purchases, deletions) require pre-execution validation
Rule of thumb: Any agent interacting with untrusted users or executing real-world actions needs guardrails — the question is which ones, not whether.
Guardrail Types
Input Guardrails
- Topic filtering: Block requests outside the agent's scope
- Injection detection: Detect prompt injection attacks
- PII detection: Identify and handle personal information
- Content moderation: Filter harmful, offensive, or inappropriate requests
- Rate limiting: Prevent abuse through request throttling
Output Guardrails
- Fact checking: Verify claims against authoritative sources
- Toxicity filtering: Remove harmful language from responses
- Hallucination detection: Flag responses that may not be grounded
- PII redaction: Remove sensitive data from outputs
- Scope enforcement: Ensure responses stay within authorized domain
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 · 377 lines · 398 tokens per session scan C 2340cd67e879
guardrails is a skill published in the GitHub repository hajekim/agentic-design-patterns-extension (1 stars, last pushed 5mo ago), licensed MIT. It adds 398 tokens to every session and 3,651 once invoked, about $0.0020 per session on Opus 5. A static security scan graded it C with 2 findings (instruction-override phrasing, nullifies safety policies). It is 100% identical to guardrails, differing in 3 lines, and is treated as a copy.
Other skills, from other repositories
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