AI Engineering
LLM integration, prompting, and agent engineering skills.
🔎
3w ago
RAG Onboard Context
RAG Onboard Context probes the indexed knowledge base at the start of a session or after a topic shift. It checks index stats, categories, and a few sample searches so the agent knows what content is available before answering.
AI Engineering
26538
🛡️
3w ago
RAG Security First
RAG Security First routes security questions through the local corpus before external threat-intel lookups. Use it for incident response, MITRE mapping, CVE analysis, detections, and red/blue team research grounded in local playbooks.
AI Engineering
26538
🔎
3w ago
Rag Troubleshoot
Rag Troubleshoot searches the knowledge corpus for prior errors, fixes, runbooks, and incidents before general debugging. Use it when a user reports a bug, exception, stack trace, failed CI run, or unexpected behavior.
AI Engineering
26538
🔎
3w ago
RAG Web Fallback
RAG Web Fallback forces an agent to search the local knowledge base before using external web tools. It is used when a question might be answered from indexed docs and the agent must explain why it escalated if local coverage is missing.
AI Engineering
26538
🧭
3w ago
Agents Md Sync
Agents Md Sync prunes and routes AGENTS.md guidance so inherited context stays small, durable, and useful. Use it when nested agent instructions have drifted, duplicated, or become too broad.
AI Engineering
26440
🧠
3w ago
Dreaming
Dreaming maintains Signet's ontology and memory substrate from transcripts, memory artifacts, source artifacts, notes, summaries, and imported records. Use it when bulk evidence needs to be turned into entities, links, claims, and provenance-tracked maintenance output.
AI Engineering
26440
🧠
3w ago
Dreaming Development
Dreaming Development helps preserve Signet's current Dreaming architecture while making changes. Use it when inspecting source, semantic memory, retrieval, and inference paths to avoid duplicate modules and ad-hoc providers.
AI Engineering
26440
🧭
3w ago
Improve
Improve surveys a codebase and writes prioritized, self-contained implementation plans for another agent to execute. It is read-only on source code and is used for audits, bug triage, roadmap planning, and handoff plans.
AI Engineering
26417
🧠
3w ago
MemoryBench Integration
MemoryBench Integration benchmarks your custom memory system against tools like Supermemory, Mem0, and Zep. Use it to compare accuracy, latency, features, and cost on standard or custom datasets.
AI Engineering
26440
🛡️
3w ago
Prompt Injection Defender
Prompt Injection Defender scans tool outputs for indirect prompt injection attempts and warns Claude about suspicious instructions. Use it when you want to detect override, role-playing, encoding, or context-manipulation patterns in files, web pages, and command results.
AI Engineering
26430
🧠
3w ago
Signet AI
Signet AI installs a persistent memory and secrets layer for AI tools. Use it when you need to set up the Signet daemon, dashboard, and connectors for a supported agent platform.
AI Engineering
26440
🧠
3w ago
Signet Ontology
Signet Ontology helps you navigate reviewed structured facts, claim history, entity dependencies, and graph hygiene from Codex. Use it when working with Signet knowledge graph state and treating raw memory files as evidence.
AI Engineering
26440