Build Adaptive Learning Agents
AI agents often repeat weak decisions because they do not retain evaluated reasoning. This skill guides trajectory tracking, verdict scoring, and pattern reuse with AgentDB.
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "reasoningbank-adaptive-learning-with-agentdb" from https://skillstore.io/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb.md and its manifest at https://skillstore.io/api/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Using "reasoningbank-adaptive-learning-with-agentdb". I need a plan for an adaptive learning agent that improves support ticket routing.
Expected outcome:
Using "reasoningbank-adaptive-learning-with-agentdb". I need to track reasoning quality for an existing agent workflow.
Expected outcome:
Using "reasoningbank-adaptive-learning-with-agentdb". I need to know where this skill stops and where engineering work begins.
Expected outcome:
The skill provides workflow guidance, example structures, and evaluation criteria. Teams still need to implement storage, API integration, privacy controls, monitoring, and tests.
All static command findings are Markdown code fences or TypeScript documentation examples, not shell execution. The hardcoded URLs are reference links, and no prompt injection, exfiltration intent, or unauthorized network behavior was found.
Share the versioned assessment report, neutral badge, embed card, and citations. Skillstore reports evidence without deciding whether this Skill is safe.
https://skillstore.io/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb/audits/8?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>DNYoussef. (2026). reasoningbank-adaptive-learning-with-agentdb security audit report (audit version 8) [Author version 1.0.0]. Skillstore. https://skillstore.io/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb/audits/8@techreport{dnyoussef-dnyoussef-reasoningbank-adaptive-learning-with-agentdb-2026,
author = {DNYoussef},
title = {reasoningbank-adaptive-learning-with-agentdb security audit report (audit version 8)},
institution = {Skillstore},
year = {2026},
number = {8},
url = {https://skillstore.io/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb/audits/8},
note = {Author version 1.0.0}
}cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "reasoningbank-adaptive-learning-with-agentdb security audit report (audit version 8)"
version: "1.0.0"
type: report
authors:
- name: "DNYoussef"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/dnyoussef-reasoningbank-adaptive-learning-with-agentdb/audits/8"
identifiers:
- type: other
value: "skillstore:dnyoussef-reasoningbank-adaptive-learning-with-agentdb:audit:8"
description: "Skillstore immutable audit report identifier"
Create an agent workflow that records decisions, outcomes, and reasoning paths for later learning.
Build verdict criteria that compare efficiency, correctness, novelty, success, and reward across trajectories.
Distill successful trajectories into patterns that can improve future decisions.
Use this skill to plan a ReasoningBank and AgentDB setup for my agent. Include trajectory fields, verdict criteria, and success metrics.
Use this skill to design trajectory records for my agent. Include decisions, reasoning, context, outcomes, timestamps, and audit needs.
Use this skill to create a memory distillation plan. Include pattern mining thresholds, pruning rules, confidence scoring, and validation steps.
Use this skill to design an adaptive learning loop that tracks trajectories, judges verdicts, distills patterns, applies learning, and measures improvement.
Author
DNYoussefLicense
MIT
Author version
v1.0.0
Skillstore revision
r1
Ref
72d5025b022c77f7a51bdf5c1637c689c80e89d1
Maintenance freshness
7/20/2026
Usage
3 downloads · 232 views
File structure
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