Results for “citation-context”

Use when automating research session rituals in Claude Code with hooks, such as session-start context injection, daily research logging, session-end persistence, or pre-commit guards that block secrets and unverified citations.

Capture and maintain a foundational marketing context document covering positioning, messaging, brand voice, target audience, and competitive landscape for consistent use across marketing skills.

Generates a CONTEXT.md routing file for a specified project subdirectory, following the canonical anatomy and ensuring it meets size and content constraints.

Extends effective context capacity through strategic compression, masking, caching, and partitioning techniques.

Compress selected context to a target token budget while preserving decisions, evidence, constraints, and unresolved questions. Use when relevant material is already selected but too long; use context-optimization when selection, deduplication, and ordering are also required.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citatio

Execute this when the user requests code context for a repository, library, or any natural-language code/technology question using DeepWiki, Context7, Exa, git clone, and/or web search+fetch.

Context Management

Distill learnings from a completed repo analysis into reusable knowledge base entries in ~/.copilot/context/. Use after finishing a repo-analysis to make the learnings persistent and searchable.

Search Google Scholar and PubMed for papers, extract accurate metadata, validate citations, and generate properly formatted BibTeX entries.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Rank an existing set of context chunks by relevance, diversity, freshness, and utility. Use when retrieval has already produced candidates that must be scored or reranked; use context-retrieval when the source corpus still needs to be searched.

Breaks down current state, context, user input, and data into a structured assessment before taking action.

Retrieve relevant information from a knowledge base using semantic, keyword, or hybrid search to ground a query. Use when the task starts with a corpus or index that must be searched; use context-ranking when candidate chunks already exist and only need ordering.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Place trusted contextual information into prompts or agent state using explicit boundaries, provenance, and templates. Use when relevant context has already been selected and must be inserted safely; use context-retrieval to find it or context-optimization to choose and order it.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Build students' capacity to place historical documents in their temporal and social context. Use when students read sources without considering what was happening at the time, or know the context but don't deploy it.

Use when context window is filling up, sessions are getting slow, or you need to preserve state across sessions. For context compression, state snapshots, search-first discipline, and cross-session memory management.

Creates or updates a canonical founder context document capturing company, product, market, team, and fundraising facts so downstream workflows operate on concrete data.

Build the smallest, highest-signal context package for an AI coding task — goal, constraints, repo facts, boundaries, and a verification plan. Load when prompts are underspecified, the agent is missing key files or decisions, the user says "use the right context", "here's the repo", or when work is drifting due to missing constraints. Also triggers on "context engineering", "gather context", "what do you need from me", "before you start". Not for cross-session continuity (use memory-startup/memory-recall).

Use this skill for context gathering, file triage, source maps, assumptions, task framing, prompt hygiene. Trigger when the task involves programming work related to Context Engineering, production implementation, audits, debugging, strategy, or validation.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Select evidence-bearing context for a downstream consumer after work when claims, artifacts, validation, unresolved decisions, or omissions must cross a boundary.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

Optimize content for AI search and LLM citations across AI Overviews, ChatGPT, Perplexity, Claude, Gemini, and similar systems. Use when improving AI visibility, answer engine optimization, or citation readiness.

This skill should be used when the user asks to "understand a codebase", "get code context", "research a library", "explore a repository", "find code examples", "look up documentation", asks a natural-language code/technology question (e.g. "how does X work", "X vs Y", "best practice for Z"), or wants to understand how a specific project, library, or concept works before making changes.

Optimize context usage for the session by reducing bloat, improving token efficiency, and focusing on relevant areas. Use when context is growing large, responses are slow, or switching between unrelated tasks. Covers context analysis, compacting, targeted pruning, MCP-first strategies, and focused scoping by area.

Runs Stanford's STORM pipeline to produce Wikipedia-quality research articles with citations, using Claude models and a search engine API.

Search and fetch Notion pages, synthesize findings, and publish structured briefs, summaries, comparisons, or reports with citations and source links.

Creates C4 context-level system documentation including system descriptions, personas, user journeys, external dependencies, and Mermaid context diagrams.