notebooklm research automation
by LocoLoboZ
Automate Google NotebookLM research workflows, source ingestion, and study material generation via CLI and Python.
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THE AGENSI STORE
636 skills found
by LocoLoboZ
Automate Google NotebookLM research workflows, source ingestion, and study material generation via CLI and Python.
by Timoranjes
Maximize AI agent performance with proactive token management, intelligent compaction, and session handoff strategies.
by Timoranjes
Comprehensive security auditing for AI agents, covering prompt injection, tool permissions, and data leakage risks.
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.
An adversarial self-review gate that hunts your agent's weakest claim, overclaims, and missing limitations before a human sees the output.
by LB Creations
Maintain durable, lean, and consistent AI agent memory across sessions while preventing context bloat and data leaks.
by Shandra
Professional DevOps diagnostics for AI agents to solve failed deployments, Docker crashes, and CI/CD pipeline errors.
by Roy Yuen
Enforce senior-level coding standards (Surgical, Simple, Goal-Driven) on every AI-generated code change.
by Alvaro
PromptShift is a minimal prompt adapter that preserves intent while improving clarity across AI models.
by GoldBean
120+ paid AI tool endpoints. Pay per use via x402 micropayments on Base (USDC). No API keys, no subscriptions.
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.
by LocoLoboZ
A proactive governance layer that validates MCP tool intent and scope to ensure safe, compliant agent behavior.
by Ryan lyell
The intelligent installer for MARM, providing cross-agent persistent memory and shared context via MCP.
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.
Audit, verify, and format academic citations across AMA, APA, and Vancouver styles to eliminate AI hallucinations.
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.
Analyzes AI agents for performance, reliability, security, and optimization opportunities.
by LocoLoboZ
A technical reference and troubleshooting expert for connecting Make.com scenarios to MCP-compatible AI agents.
by Kris Kereluk
Automate agent to find and email property strata documents directly from Google Drive to clients or realtors.
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.
Teach your AI agent to read, search, and structure your Obsidian Vault using Wikilinks and Frontmatter standards.
Audits any AI draft for unsupported claims — flags each one, grades its source, and returns a substantiation report.
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.