karthikrshet — 39 mods

Instructions for karthikrshet/Career-Agents, covering career-agents ai contributor guide, pre-development checklist, strict rules for ai agents and required validation pipeline.

38 yesterday A 609 tokens original MIT

cursorrules

14

karthikrshet/Career-Agents

Cursor rule Cursor

When working in this workspace, you have access to the Career-Agents MCP Server. Use the following tools to assist the user with career strategy, resume optimization, and interview preparation.

38 yesterday A 254 tokens original MIT

ai-forensics

15

karthikrshet/ClaudeMark

Skill Claude CodeCodex

Local-first AI watermark detection, Unicode steganography forensics, document sanitization, and C2PA provenance extraction.

9 7d ago A 28 tokens original MIT

clean-user-facing-text

16

karthikrshet/ClaudeMark

Cursor rule Cursor

Enforce invisible Unicode and steganography hygiene on user-facing text, manuscripts, and documentation.

9 7d ago A 0 tokens original MIT

aiskills AGENTS.md

17

karthikrshet/aiskills

Instructions file CodexOpenCode

AGENTS.md instructions for karthikrshet/aiskills, covering agents.md — aiskills instructions for ai coding agents, what is aiskills?, before you start any task, human approval required and safety rules.

3 11d ago A 979 tokens

agent-design

18

karthikrshet/aiskills

Skill Claude CodeCodex

Use this skill to design single-agent or multi-agent AI systems with defined boundaries, tools, memory, state, planning, and guardrails. Activates when building an AI agent, autonomous workflow, or multi-agent orchestration system. Ensures agent scope, permissions, and failure modes are explicitly designed.

3 11d ago A 66 tokens

ai-security-review

19

karthikrshet/aiskills

Skill Claude CodeCodex

Use this skill to audit an AI system for security vulnerabilities including prompt injection, sensitive data exposure, excessive agent permissions, unsafe tool calls, and insecure output handling. Grounded in OWASP GenAI LLM Top 10 (2026). Activates before production deployment of any LLM-based application, agent, or…

3 11d ago A 74 tokens

concise-mode

20

karthikrshet/aiskills

Skill Claude CodeCodex

Use this skill to enforce high-density, zero-filler, token-efficient communication. Strips conversational fluff, polite preamble, redundant summaries, and repetitive apologies to maximize reasoning density, reduce latency, and conserve context window budget.

3 11d ago A 54 tokens

context-engineering

21

karthikrshet/aiskills

Skill Claude CodeCodex

Use this skill to systematically manage what information goes into an LLM context window — selecting, compressing, and prioritizing content to maximize response quality within token budget constraints. Activates when building or optimizing LLM applications, RAG systems, or agent workflows that face context window…

3 11d ago A 73 tokens

rag-evaluation

22

karthikrshet/aiskills

Skill Claude CodeCodex

Use this skill to evaluate the quality of a RAG pipeline on faithfulness, answer relevancy, context precision, context recall, and hallucination rate. Activates after a RAG system is implemented or when retrieval quality is in question. Produces a structured evaluation report with measurable results.

3 11d ago A 63 tokens

production-readiness

23

karthikrshet/aiskills

Skill Claude CodeCodex

Use this skill to verify that an AI system is ready for production before deployment. Covers model abstraction, cost/latency, retries, fallbacks, structured logging, tracing, observability, evaluation in CI/CD, monitoring, and rollback planning. Activates as a mandatory gate before production deployment of any AI/LLM…

3 11d ago A 74 tokens

rag-architecture

24

karthikrshet/aiskills

Skill Claude CodeCodex

Use this skill to design end-to-end Retrieval-Augmented Generation (RAG) systems including ingestion, chunking, embedding, retrieval, reranking, and context construction. Activates when building a document Q&A system, knowledge base, or any LLM application that retrieves information at query time.

3 11d ago A 65 tokens