skills.rest
nsuberi
nsuberiCOMMUNITY
Explore all skills by this author →
GitHub

agentic-harness-configurer

Structure under-specified agent harnesses with validation, guardrails, and retry budgets.

Updated Jul 5, 2025
Search Tags:#input validation#retrieval#agentic#prompt guardrails#confidence thresholds#tool boundaries#retry budgets
One-click install
npx skills add https://github.com/nsuberi/ai-prototype-hub --skill agentic-harness-configurer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agentic-harness-configurer
Source: https://github.com/nsuberi/ai-prototype-hub/tree/main/apps/ai-builders-challenge/.claude/skills/agentic-harness-configurer
Command: npx skills add https://github.com/nsuberi/ai-prototype-hub --skill agentic-harness-configurer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It helps you add missing structure to an under-specified agent harness so the agent stops guessing, respects tool boundaries, and fails safely when information is missing.

Core Features & Use Cases

  • Input validation hardening: Verifies request/session identifiers and message shape so bad inputs become clear, structured client errors instead of silent fallbacks.
  • Tool/function boundary enforcement: Ensures retrieval and tool functions document preconditions and raise typed, non-leaky errors when the knowledge base can’t answer.
  • Reliability guardrails: Introduces confidence thresholds, prompt constraints, and bounded retry budgets to prevent unbounded loops and reduce hallucination risk.

Quick Start

Ask the AI to review your app/agent.py, app/retrieval.py, and the borrower prompts and propose a small set of prioritized diffs that improve validation, tool boundaries, confidence gating, and retry budgets.

Frequently Asked Questions about agentic-harness-configurer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add guardrails to an AI agent to prevent hallucination and unbounded loops?▼

You can add prompt guardrails by introducing confidence thresholds, prompt constraints, and bounded retry budgets. This prevents unbounded loops and reduces hallucination risk by ensuring the agent fails safely when information is missing.

How do I enforce tool boundaries for retrieval functions in a chat-based agent harness?▼

Enforcing tool boundaries requires retrieval and tool functions to document preconditions and raise typed, non-leaky errors. This stops the agent from guessing when the knowledge base cannot answer a property- or id-based user request.

What's the best way to validate inputs for an AI agent handling property or id-based requests?▼

Input validation hardening verifies request and session identifiers and message shape. This turns bad inputs into clear, structured client errors instead of allowing silent fallbacks or scope creep in the agent harness.

How do I stop my AI agent from guessing when the knowledge base lacks information?▼

To stop an agent from guessing, you structure the under-specified agent harness with reliability guardrails and typed retrieval failure modes. This ensures the agent respects tool boundaries and fails safely when information is missing.

Does this agent hardening approach require specific dependencies or frameworks?▼

No specific dependencies are required. The approach applies to chat-based agent systems involving orchestration logic, retrieval lookups, prompt grounding, and tool calls, focusing on structural improvements rather than external libraries.

Related Skills

Explore More Software Engineering Skills→
blocknaviblocknavi
1

convex-component-authoring

Create self-contained Convex components with isolated schemas and exports.

Official
Intermediate
AlejandroFiginiAlejandroFigini

canary

Detect runtime errors and performance regressions in live deployments via Bash probes.

Community
Advanced
SyntaxAsSpiralSyntaxAsSpiral
5

memory-systems

Persist AI agent context across sessions with vector stores and temporal knowledge graphs.

Community
Advanced
breethomasbreethomas
16

agent-workflow

Design AI agent workflows with structured schemas and integration patterns.

Community
Advanced