weekly cowork system auditor
by LocoLoboZ
A structured governance auditor to optimize AI project instructions, clean up context, and manage workspace health.
Ship better AI in 30 seconds. Browse 2,000+ expert-built and security scanned skills -> Browse skills
THE AGENSI STORE
636 skills found
by LocoLoboZ
A structured governance auditor to optimize AI project instructions, clean up context, and manage workspace health.
by Roy Yuen
Architect durable multi-agent Kanban boards with structured handoffs and role-based task decomposition.
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.
An adversarial senior engineer review gate that audits AI-written code for security gaps and logic errors before shipping.
by servrox
Audit, prune, and secure your AI agent's long-term memory to prevent pollution and data leakage.
by Joker
5 realistic visual styles, character modeling, I2V prompts, cinematic shot design, uncanny valley prevention.
Drastically reduce RAG costs and latency while improving retrieval accuracy through advanced memory architecture.
by Danejw
Convert visual directions and screenshots into a stable design system document for AI coding agents to follow.
by Shippers
Avoid context bloat and high costs with a 3-line verdict on expensive AI operations before you run them.
by Danejw
Convert product specs into a vertical-slice implementation roadmap with ready-to-use prompts for AI coding agents.
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.
One-line summary description Stop your agent from claiming "done" before it's proven. A verification gate that classifies each change by risk (payment, auth, database, user-facing), picks the tests that actually cover it, demands evidence, maps regression risk, and outputs an honest pass/fail report. Turns "looks good to me" into "here's what I ran, and here's what's still unverified."
Systematic audit for AI prompts to detect security flaws, bias, and cost-inefficiencies with auto-optimization.
A structured recovery framework to stop agent loops, handle malformed output, and manage autonomous error escalation.
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%.
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 Nex AI
Generate a production-ready 3D virtual office for AI agents using Next.js and React Three Fiber.
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 Tony Javid
Professional AI-powered redesign and beautification for PowerPoint and PDF slide decks.
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.
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 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.