guards
Generate provider-agnostic AI agent guardrail blueprints and control matrices from a use case. Use when designing or reviewing agent safety architecture, prompt-injection and tool-misuse defenses, risk-tiered human approval gates, or auditable enterprise guardrail policies using industry patterns across top providers.
安装与使用
请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。
查看来源 ↗使用指南技能说明
guards
Mission
Turn ambiguous "add guardrails" requests into an implementation-ready guardrail architecture. Produce provider-agnostic outputs that application engineers can execute without choosing a model vendor first.
Output Contract
Always return a structured plan plus a control matrix. The response must include these headings in this order:
- Problem Statement
- Success Criteria
- Risk Tier and Enforcement Posture
- Threat Scenarios
- Layered Control Stack
- Control Matrix
- Residual Risks
- Validation and Acceptance Checks
- Rollout and Monitoring
- Rollback and Abort Criteria
- Implementation Brief
Never output provider-specific SDK instructions in default mode.
If a user explicitly requests provider mappings, keep them in a separate appendix titled Provider Mapping (Optional).
Request Contract
Model requests as GuardrailBlueprintRequest v1.
Required fields:
-
use_case: one-sentence workload description -
actor_profile: who can trigger the agent and from where -
tool_surface: tools or side-effecting actions the agent can invoke -
data_sensitivity:public | internal | confidential | regulated -
autonomy_level:assistant | semi_autonomous | autonomous -
regulatory_context: baseline policy context -
risk_tolerance:low | medium | high
Defaults:
-
regulatory_context = US enterprise baseline -
risk_tolerance = medium -
freshness_mode = pattern_only
When required fields are missing, ask only the minimum judgment-call questions needed to classify risk tier and tool boundary.
Control Taxonomy (Fixed)
Map every threat scenario across this layer order:
- Input controls
- Context controls
- Model controls
- Tool pre-call controls
- Tool post-call controls
- Output controls
- Human approval controls
- Audit and traceability controls
Each scenario must include at least one control in every applicable layer.
Enforcement Policy (Risk-Tiered Mixed Mode)
Apply this default policy unless the user overrides it:
-
low: monitored allow with explicit logging and anomaly detection -
medium: allow with guardrails and sampled human review -
high: fail-closed for side-effecting actions unless explicit human approval -
critical: fail-closed by default with mandatory human approval and dual-control where possible
Hard rule:
- High and critical scenarios must not be fail-open.
Workflow
- Normalize the request into
GuardrailBlueprintRequest v1. - Define the system boundary and identify side-effecting tools.
- Classify risk tier by data sensitivity, autonomy level, and blast radius.
- Build 5-12 concrete threat scenarios with attack paths and target assets.
- Map layered controls using the fixed taxonomy.
- Assign enforcement mode and human gate behavior per scenario.
- Produce residual risk register with explicit owners.
- Define acceptance checks and rollback triggers.
- Cross-check control choices against
references/industry_patterns.md. - Emit the final plan and control matrix using the template in
references/blueprint_template.md.
Evidence and Freshness Modes
Use one mode and state it in the output:
-
pattern_only(default): synthesize provider-agnostic industry patterns. -
hybrid: cite sources for high-risk controls and decision-critical claims. -
strict_source_cited: cite sources for all major control recommendations.
When the prompt asks for "latest" provider specifics, verify against primary docs before finalizing.
Quality Gates
Before completing, verify all gates:
- Provider-agnosticity: no vendor-locked implementation steps in the main output.
- Layer coverage: each high-risk scenario includes applicable controls across layers.
- Enforcement correctness: high and critical scenarios include fail-closed behavior.
- Residual risk completeness: each material risk has probability, impact, trigger, and owner.
- Traceability: each major requirement maps to at least one acceptance check.
- Operability: includes monitoring signals plus rollback/abort criteria.
Non-Goals
- No legal opinions or jurisdiction-specific legal advice.
- No guarantee that any control makes compromise impossible.
- No deployment automation scripts or runtime policy engine implementation.
- No provider-specific code generation unless explicitly requested.
Deliverable Checklist
- Structured plan with all required headings.
- Control matrix with standardized columns.
- Residual risk register with explicit ownership.
- Acceptance checks tied to requirements.
- Rollout and rollback criteria.
- Explicit mode declaration (
pattern_only,hybrid, orstrict_source_cited).
Reference
- Template:
references/blueprint_template.md - Pattern baseline:
references/industry_patterns.md
使用示例
查看来源仓库中的使用示例与配置说明。
查看来源 ↗来源历史
- 收录时间
- 2026-03-11
- 索引更新时间
- 2026-03-11
- Branch
- main
收录与同步日期属于本站记录。源码修改历史请查看来源仓库。
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