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THE AGENSI STORE
65 skills found
by Shippers
Devs and PMs lose hours hand-building PowerPoint/Google Slides for demos, design reviews, tech talks and stakeholder upd
by Shippers
Developers waste time re-explaining their project architecture, conventions, and decisions to AI coding agents in every
by Timoranjes
Teaches AI coding agents to self-detect context rot (regression loops, instruction drift, hallucination drift, lost-in-the-middle) during long sessions and execute a structured checkpoint/recovery pro
by Timoranjes
Teaches AI coding agents to systematically verify their own work before declaring "done." Implements a structured five-check verification gauntlet (build/test/lint/git-diff/runtime) that the agent run
by loreto
Builds the organizational memory schema your AI agent needs to answer why — capturing decision provenance, causal chains, and event context that embedding-based retrieval permanently discards.
by loreto
Architects the right retrieval strategy for every query — teaching your agent when to use RAG, a knowledge graph, or a temporal index instead of defaulting to vector search for everything.
by loreto
Evaluates AI coding agent platforms across five structural dimensions that determine real-world performance independently of model quality, so teams select on architectural fit rather than benchmark scores.
by Aman Garg
Stop burning expensive model tokens on repetitive subtasks. This skill delegates mechanical work to cheaper models and writes handoff snapshots so you never lose context switching between sessions.
by Roy Yuen
Enforce explicit context discipline, artifact-gated transitions, and verification evidence for AI agent workflows.
by Roy Yuen
Compress noisy chat logs and logs into durable, high-signal memory reports with built-in duplicate suppression.
by Roy Yuen
A high-precision pre-coding gate that detects conflicting requirements and prevents agents from making wrong assumptions.
Automated security auditing and risk assessment for Model Context Protocol (MCP) servers.
by LocoLoboZ
Build structured, tool-agnostic ransomware incident response playbooks tailored to your SOC and organizational context.
by LB Creations
Review macOS admin scripts for reliable current-user detection and safe session-context handling.
by LB Creations
Review Jamf and Kandji scripts for safer user context, prompts, logging, and rollout readiness.
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.
Drastically reduce RAG costs and latency while improving retrieval accuracy through advanced memory architecture.
Turn prospect notes, quote context, and client objections into quote follow-up scripts, renewal-save messages, CRM notes, and risk-aware broker communication.
A structured WCAG 2.1 AA audit and fix agent for WordPress themes, organized by block theme, Gutenberg, forms, and navigation context, with scored findings and complete before-to-after code patches.
Find the model-version coupling that breaks when you swap LLMs. Flags hardcoded model names and versions, deprecated or renamed parameters (the max_tokens to max_completion_tokens class of change), hardcoded token and context-window limits, response-format parsing tied to one model's output, tool-schema format coupling between providers, and hardcoded per-token cost constants. The patterns load from an editable model-rules table you update as new models ship.
Scaffold a secure, spec-compliant MCP server from a description of the tools you want to expose. Sets up the official SDK (TypeScript or Python/FastMCP), defines tools/resources/prompts with strict JSON Schema, wires the right transport (stdio or Streamable HTTP), adds OAuth 2.1 for remote, and hardens against the MCP-specific footguns — prompt injection via tool output, token passthrough, over-broad scopes, command/path/SSRF injection, leaked secrets — before it ships. Returns a runnable skeleton plus a security checklist. Built by someone who's shipped production MCP servers.
A retrieval architect that diagnoses why RAG returns confident-but-wrong answers, picks the right context architecture (RAG vs knowledge graph vs structured/temporal retrieval) instead of defaulting to vector search, and designs the institutional-memory schema embeddings throw away.
Write and review the docs AI agents actually read — AGENTS.md for your repo and llms.txt for your site. Drafts them from scratch or audits existing ones for completeness, clarity, and wasted context, with a PASS or REVISE verdict.
A professional technical editor's review for your docs. Catches missing context, unclear writing, and unverifiable claims in READMEs, API docs, and changelogs before they ship — with a PASS/REVISE verdict and a prioritized fix list.