multi model review router
by LocoLoboZ
Orchestrate independent reviews, adversarial audits, and multimodal analysis via secondary models and external tools.
Ship agent workflows in 30 seconds. Browse 2,000+ expert-built and security scanned skill -> Browse skills
THE AGENSI STORE
355 skills found
by LocoLoboZ
Orchestrate independent reviews, adversarial audits, and multimodal analysis via secondary models and external tools.
by GoldBean
120+ paid AI tool endpoints. Pay per use via x402 micropayments on Base (USDC). No API keys, no subscriptions.
Drive a browser from your agent without the token bloat. Batches navigate/click/type into one call, stays logged in with persistent sessions, and feeds the model compact DOM snapshots instead of giant HTML, so multi-step flows like logins, form-filling, and scraping behind auth stay fast and cheap. Runs on the uBrowser MCP server.
Save a coding agent's full working state to a handoff file before it hits the context limit, then resume in a fresh session without re-explaining everything. Captures the active plan, git branch, uncommitted changes, decisions, blockers, and next steps, so Claude Code or Codex picks up exactly where it stopped instead of starting cold.
by LocoLoboZ
Automate Google NotebookLM research workflows, source ingestion, and study material generation via CLI and Python.
An adversarial gate that audits an AI eval or test suite — LLM-judge rubrics, datasets, regression tests, metrics — for gameable criteria, data leakage, missing edge cases, and non-determinism, then returns one PASS/REVISE/FAIL verdict.
by Shandra
Professional DevOps diagnostics for AI agents to solve failed deployments, Docker crashes, and CI/CD pipeline errors.
An adversarial self-review gate that hunts your agent's weakest claim, overclaims, and missing limitations before a human sees the output.
by Ryan lyell
The intelligent installer for MARM, providing cross-agent persistent memory and shared context via MCP.
by LocoLoboZ
A proactive governance layer that validates MCP tool intent and scope to ensure safe, compliant agent behavior.
by Roy Yuen
Enforce senior-level coding standards (Surgical, Simple, Goal-Driven) on every AI-generated code change.
by Shandra
Converts internal SOPs, policies, checklists, and process notes into structured AI-agent workflows with decision trees, escalation rules, QA checkpoints, and audit-ready outputs.
Audit, verify, and format academic citations across AMA, APA, and Vancouver styles to eliminate AI hallucinations.
by LocoLoboZ
A technical reference and troubleshooting expert for connecting Make.com scenarios to MCP-compatible AI agents.
Lint a prompt template for the issues that cause injection and flaky output. Flags untrusted variables interpolated straight into the instructions (the injection surface), placeholders that are never provided or never used, contradictory instructions, a missing output-format spec where the result is parsed, unbounded context interpolation, and leftover placeholders. It detects problems; it does not write prompts.
A reusable rubric that grades every source by type, recency, authority, independence, and corroboration, then ranks them and resolves conflicts by evidence weight.
An adversarial gate that audits a research brief or AI-generated answer for unsupported claims, weak or outdated sources, missing citations, and one-sided framing — returning a structured TRUST/VERIFY/REJECT verdict with the exact passage quoted and what to verify for each.
by Alvaro
PromptShift is a minimal prompt adapter that preserves intent while improving clarity across AI models.
Audits any AI draft for unsupported claims — flags each one, grades its source, and returns a substantiation report.
by LocoLoboZ
A structured governance auditor to optimize AI project instructions, clean up context, and manage workspace health.
Lint your AGENTS.md (or CLAUDE.md and .cursorrules) for the problems that make a coding agent misbehave. Flags contradictory rules, references to files and commands that no longer exist, overly broad or unsafe instructions, missing sections (build, test, run, conventions), duplicate rules, and the case where you have competing rule files that should be consolidated into one AGENTS.md.
by servrox
Audit, prune, and secure your AI agent's long-term memory to prevent pollution and data leakage.
by Roy Yuen
Architect durable multi-agent Kanban boards with structured handoffs and role-based task decomposition.
by Danejw
Convert visual directions and screenshots into a stable design system document for AI coding agents to follow.