Optimization Loop
Autonomous loop that iteratively modifies, evaluates, and selects the best version of any text resource — skills, prompts, or campaigns — using a modify-measure-keep/discard cycle.
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THE AGENSI STORE
355 skills found
Autonomous loop that iteratively modifies, evaluates, and selects the best version of any text resource — skills, prompts, or campaigns — using a modify-measure-keep/discard cycle.
An adversarial reviewer for AGENTS.md and agent instruction files. It flags ambiguous or contradictory rules, missing guardrails, vague tool and scope definitions, and untestable instructions, then returns a PASS / REVISE / BLOCK verdict — before the config drives your agent.
Analyzes AI agents for performance, reliability, security, and optimization opportunities.
by Shippers
Avoid context bloat and high costs with a 3-line verdict on expensive AI operations before you run them.
by Jeet Dhandha
Drive several real Chrome profiles, each with its live Google login, at once via Kimi WebBridge — multi-profile browser automation in your real Chrome, not headless.
Systematic audit for AI prompts to detect security flaws, bias, and cost-inefficiencies with auto-optimization.
by Danejw
Convert product specs into a vertical-slice implementation roadmap with ready-to-use prompts for AI coding agents.
Drastically reduce RAG costs and latency while improving retrieval accuracy through advanced memory architecture.
by Joker
5 realistic visual styles, character modeling, I2V prompts, cinematic shot design, uncanny valley prevention.
Lint the function-calling tool definitions your agent exposes. Flags tools with no description, parameters missing a description or a type, overlapping or near-duplicate tools, too many tools for reliable selection, an unsafe tool exposed without a guard, required parameters missing from the schema, and free-form parameters that should be bounded with an enum. Cleaner tool schemas mean an agent that picks the right tool.
by Zotri
Run Claude Code unattended with a battle-tested safety framework, hardened deny-rules, and a 6-layer rollback ladder.
by Timoranjes
The security auditor for AI agents. Detect prompt injection, secret leaks, and unsafe tool access in SKILL.md files.
An advanced FinOps engine to analyze AI usage, optimize token spend, and reduce LLM costs by up to 60%.
by Shogun Labs
Battle-tested prompting patterns to eliminate LLM output drift. Sandwich structure, few-shot examples, history limits, retry, and token caps — 6 composable layers for production-grade agent reliability.
Runs an ordered evidence-integrity gate over any AI draft — grade sources, ground claims, verify technical assertions, stress-test — then returns one PASS/REVISE/FAIL ship decision.
An iterative agent loop that optimizes any prompt, config, or artifact by making one change at a time, scoring it against a metric, and keeping only the winners.
by Samoxis
Your headless Ollama box crashes at 3am and you find out hours later. OllamaWatch pings your Telegram the instant a model dies, the GPU runs out of memory, or the API hangs — with a fix hint in every alert. One Python file, no SaaS, no dashboards.
by Nex AI
High-reliability Dutch content engine with a Claude-Gemini-Qwen fallback chain and template safeties.
by Nex AI
Generate a production-ready 3D virtual office for AI agents using Next.js and React Three Fiber.
by Nex AI
Deploy a structured, long-term memory palace for AI agents on Raspberry Pi via MCP and ChromaDB.
A structured recovery framework to stop agent loops, handle malformed output, and manage autonomous error escalation.
A structured protocol for AI agents to orchestrate sub-agents with role contracts and disciplined handoffs.
by Nex AI
Maintain 100% uptime with an automated LLM fallback chain that routes from high-tier APIs to local models.
by Nex AI
Deploy a self-hosted, private RAG system with pgvector, Ollama, and a Telegram interface for your personal notes.