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survival-instructor/references/ai-skills.md
skillfactor-pipeline d8a6dedeff feat: survival-instructor skill package v0.1.0
2026-08-15 16:28:28 +02:00

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External AI agent skills — survival-instructor

Proven, publicly available AI agent skills mapped to this occupation. Nothing is copied from the sources: every entry is a name, a one-line summary and a link to the upstream skill package. Each section names its source repository, commit, license and retrieval date.

Tiers: core = the skill directly exercises a top market hard skill, tool or method (from gated job-ad evidence) or an essential ESCO competence of this occupation; adjacent = plausibly useful, secondary. Entries are capped at 12 per source and 80 in total per occupation (core first, strongest matches survive); everything beyond the caps is excluded and logged in the pipeline audit trail, not in this package.

Matched deterministically (ISCO group + title/competence keywords, tiered against market evidence + ESCO essentials) by pipeline/p5_enrich_ai_skills.py on 2026-07-14.

Source: anthropics/skills

  • Repository: https://github.com/anthropics/skills (commit f6656c1, retrieved 2026-07-14)
  • License: Apache-2.0; the document skills (docx/pdf/pptx/xlsx) are source-available — see the LICENSE.txt in the upstream skill folder
Skill Tier What it adds Upstream
docx adjacent Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to … source
pdf adjacent Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating … source

Source: a5c-ai/babysitter

Skill Tier What it adds Upstream
lms-admin adjacent Configure and manage Learning Management System operations including courses, enrollments, compliance training, and learning analytics source
gas-optimization adjacent Advanced gas optimization techniques for EVM smart contracts. Covers storage packing, memory vs calldata optimization, assembly/Yul, efficient data structures, batch operations, and benchmark-driven optimization strategies. source
lessonly-training adjacent Lessonly (Seismic Learning) training platform integration source

Source: affaan-m/everything-claude-code

Skill Tier What it adds Upstream
documentation-lookup adjacent Use up-to-date library and framework docs via Context7 MCP instead of training data. Activates for setup questions, API references, code examples, or when the user names a framework (e.g. React, Next.js, Prisma). source

Source: AgriciDaniel/claude-blog

Skill Tier What it adds Upstream
blog-discourse core Research what people are actually saying about a topic in the last 30 days across Reddit, X / Twitter, YouTube, Hacker News, dev.to, Medium, and other public discourse platforms. API-free; uses WebSearch with platform-targeted site … source

Source: AIDevGTM/gtm-cofounder

Skill Tier What it adds Upstream
founder-led-content core Build authority by teaching the problem space, not announcing features. Use when the founder finds "marketing" distasteful and does none, publishes only product updates, or wants a sustainable content and GitHub-README strategy that … source

Source: anthropics/claude-plugins-official

Skill Tier What it adds Upstream
example-skill core This skill should be used when the user asks to "demonstrate skills", "show skill format", "create a skill template", or discusses skill development patterns. Provides a reference template for creating Claude Code plugin skills. source

Source: basicmachines-co/basic-memory

Skill Tier What it adds Upstream
memory-ci-capture adjacent Synthesize GitHub delivery context into a concise Basic Memory project update. Use in CI after bm ci collect prepares a ProjectUpdateContext; return only structured AgentSynthesis JSON for bm ci publish. source
memory-research adjacent Research an external subject using web search, synthesize findings into a structured Basic Memory entity. Use when asked to research a company, person, technology, or topic — or when a bare name or URL is provided that implies a research … source
memory-schema adjacent Schema lifecycle management for Basic Memory: discover unschemaed notes, infer schemas, create and edit schema definitions, validate notes, and detect drift. Use when working with structured note types (Task, Person, Meeting, etc.) to … source
memory-continue adjacent Resume prior work by rebuilding context from the Basic Memory knowledge graph — pick up where you left off using memory:// URLs, recent activity, and search. Use when starting a session or when the user says 'continue with...', 'back … source
memory-metadata-search adjacent Structured metadata search for Basic Memory: query notes by custom frontmatter fields using equality, range, array, and nested filters. Use when finding notes by status, priority, confidence, or any custom YAML field rather than free-text … source
memory-notes adjacent How to write well-structured Basic Memory notes: frontmatter, observations with semantic categories, relations with wiki-links, and best practices for building a rich knowledge graph. Use when creating or improving notes. source
memory-onboarding adjacent Guide someone new to Basic Memory through designing and building a complete personal knowledge system — interview them about what they want to track, propose a structure, build it with schemas and instruction notes, teach them to use it, … source
memory-tasks adjacent Task management via Basic Memory schemas: create, track, and resume structured tasks that survive context compaction. Uses BM's schema system for uniform notes queryable through the knowledge graph. source

Source: brycewang-stanford/Auto-Empirical-Research-Skills

Skill Tier What it adds Upstream
markitdown adjacent Convert various file formats (PDF, Office documents, images, audio, web content, structured data) to Markdown optimized for LLM processing. Use when converting documents to markdown, extracting text from PDFs/Office files, transcribing … source

Source: davila7/claude-code-templates

Skill Tier What it adds Upstream
knowledge-distillation core Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. … source
academic-cv-builder core Format CVs for academic positions, including publications, grants, teaching, and research experience. Use when the user mentions academic CV, faculty job, tenure-track, postdoc, PhD, research position, or needs to list publications, … source
code-review-excellence core Transform code reviews from gatekeeping to knowledge sharing through constructive feedback, systematic analysis, and collaborative improvement. source
deadline-prep adjacent Generate a structured demo outline from your session's change log and git history. Reads .claude/critical_log_changes.csv and git log to produce presentation-ready talking points for end-of-day demos, standups, or delivery deadlines. source
gcc adjacent Git Context Controller (GCC) - Manages agent memory as a versioned file system under .GCC/. This skill should be used when working on multi-step projects that benefit from structured memory persistence, milestone tracking, branching for … source
gptq adjacent Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs … source
optimizing-attention-flash adjacent Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster … source
quantizing-models-bitsandbytes adjacent Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit … source
unsloth adjacent Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization source
ai-agents-architect adjacent Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling. source

Source: Devin-AXIS/iPolloWork

Skill Tier What it adds Upstream
linear-project-updates adjacent Produce concise Linear project updates from current milestones, completed and blocked issues, delivery risks, and next actions. source

Source: foryourhealth111-pixel/Vibe-Skills

Skill Tier What it adds Upstream
unsloth adjacent Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization source

Source: giuseppe-trisciuoglio/developer-kit

Skill Tier What it adds Upstream
memory-md-management adjacent Provides comprehensive memory file management capabilities including auditing, quality assessment, and targeted improvements for files such as CLAUDE.md. Use when user asks to check, audit, update, improve, fix, maintain, or validate … source

Source: infrasity-labs/dev-gtm-claude-skills

Skill Tier What it adds Upstream
blog-discourse core Research what people are actually saying about a topic in the last 30 days across Reddit, X / Twitter, YouTube, Hacker News, dev.to, Medium, and other public discourse platforms. API-free; uses WebSearch with platform-targeted site … source
meeting-notes adjacent Structured meeting summaries with action items, decisions, and key discussion points. Use when: taking meeting notes, summarizing discussions, tracking action items, or when user mentions meeting notes, minutes, action items, or needs … source

Source: jeremylongshore/claude-code-plugins-plus-skills

Skill Tier What it adds Upstream
windsurf-cascade-context adjacent Manage Cascade context window and memory for complex projects. Activate when users mention "cascade context", "ai memory", "context management", "large codebase navigation", or "multi-session development". Handles context optimization and … source
serpapi-hello-world adjacent Run your first SerpApi search -- Google, Bing, or YouTube results as JSON. Use when starting with SerpApi, testing search queries, or learning the structured result format. Trigger: "serpapi hello world", "serpapi example", "serpapi first … source

Source: ljagiello/ctf-skills

Skill Tier What it adds Upstream
ctf-ai-ml adjacent Provides AI and machine learning techniques for CTF challenges. Use when attacking ML models, crafting adversarial examples, performing model extraction, prompt injection, membership inference, training data poisoning, fine-tuning … source

Source: microsoft/SkillOpt

Skill Tier What it adds Upstream
skillopt-sleep adjacent Use when the user wants their Claude agent to self-improve from past usage, asks about a nightly/offline 'sleep' or 'dream' cycle, memory/skill consolidation, or says things like 'make my agent better the more I use it', 'review my past … source

Source: mohitagw15856/pm-claude-skills

Skill Tier What it adds Upstream
teaching-lesson-plan core Design a structured lesson plan for any subject, audience, or format. Use when asked to write a lesson plan, course outline, teaching session, workshop curriculum, or training module. Produces a complete lesson plan with learning … source
lesson-plan core Build a complete, standards-aligned lesson plan with clear objectives, a timed activity sequence, differentiation, and assessment. Use when asked to write a lesson plan, plan a class or lesson, design a teaching session, or structure … source
student-feedback core Write constructive, specific feedback on student work that motivates and tells the student exactly how to improve. Use when asked to give feedback on a student's work, write grading comments, respond to an essay or assignment, or coach a … source
roadmap-presentation adjacent Create structured roadmap presentations calibrated to any audience. Use when asked to build a product roadmap, present roadmap to leadership, create a roadmap slide, or communicate quarterly plans to execs, teams, or customers. Produces an … source
candidate-scorecard adjacent Turn interview notes into a structured candidate scorecard and hire recommendation. Use when asked to write an interview scorecard, a candidate evaluation, an interview debrief, or to summarize feedback into a hire/no-hire call. Produces a … source
chart-data-extractor adjacent Extract pixel-level data from an image of a chart or graph and produce a structured data table. Use when asked to extract data from a chart image, transcribe numbers from a graph, digitise a chart, or turn a screenshot of data into a … source
meeting-notes adjacent Structure and format meeting notes following PM best practices. Use when asked to create meeting notes, format discussion notes, capture action items, or document decisions from any meeting type. Produces structured notes with decisions, … source
parent-communication adjacent Draft clear, warm, professional messages to parents or guardians — progress notes, concerns, positive news, behaviour issues, or meeting requests. Use when asked to email a parent, write home about a student, raise a concern with a … source
professional-brain adjacent Maintain a durable, local markdown memory ('brain') of your product context, decisions, hypotheses, and stakeholders that other skills read from and write back to. Use when asked to set up a brain, ingest notes/artifacts into memory, … source

Source: mukul975/Anthropic-Cybersecurity-Skills

Skill Tier What it adds Upstream
detecting-t1003-credential-dumping-with-edr core Detect OS credential dumping techniques targeting LSASS memory, SAM database, NTDS.dit, and cached credentials using EDR telemetry, Sysmon process access monitoring, and Windows security event correlation. source

Source: muratcankoylan/Agent-Skills-for-Context-Engineering

Skill Tier What it adds Upstream
book-sft-pipeline adjacent This skill should be used for book-to-SFT pipelines: ePub extraction, literary segmentation, author-voice dataset construction, style-transfer training, LoRA workflows, and model evaluation for voice replication. source

Source: nexu-io/open-design

Skill Tier What it adds Upstream
html-ppt-zhangzara-daisy-days adjacent A customer-success workshop onboarding users to a project-management app — the first-value path and the habits that retain. Built as a decision-grade professional training deck for new customers, CS team. source
html-ppt-zhangzara-creative-mode adjacent A brand visual-identity system reveal for an outdoor label — logo, color, type, and the rules that keep it consistent. Built as a decision-grade design craft deck for brand team, client. source
html-ppt-zhangzara-retro-windows adjacent An IT security-awareness training on spotting phishing — the tells, the drill, and what to do in the first 60 seconds. Built as a decision-grade professional training deck for all employees. source
hps-bauhaus adjacent A visual-design fundamentals course for new brand designers — grid, type, color, and the exercises that build the eye. Built as a decision-grade professional training deck for junior designers, new hires. source
html-ppt-course-module adjacent A first-30-days onboarding module for new hospitality hires — the behaviors, the practice, the checks, and the manager follow-up. Built as a decision-grade professional training deck for new hires, managers. source
html-ppt-zhangzara-playful adjacent A retail sales-floor training on consultative selling — the flow, the role-plays, and the daily habit that lifts conversion. Built as a decision-grade professional training deck for store associates, floor managers. source
pptx adjacent Read, generate, and adjust PowerPoint slides, layouts, and templates. Useful for executive decks, training material, and product reviews. source

Source: nWave-ai/nWave

Skill Tier What it adds Upstream
nw-stakeholder-engagement adjacent Demonstration preparation, audience-tailored presentations, feedback collection, and business outcome measurement. Load when preparing demos or measuring business value delivery. source

Source: OpenRaiser/NanoResearch

Skill Tier What it adds Upstream
unsloth adjacent Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization source

Source: Orchestra-Research/AI-research-SKILLs

Skill Tier What it adds Upstream
knowledge-distillation core Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. … source
gptq adjacent Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs … source
optimizing-attention-flash adjacent Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster … source
pytorch-fsdp2 adjacent Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with … source
quantizing-models-bitsandbytes adjacent Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit … source
unsloth adjacent Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization source

Source: pedrohcgs/claude-code-my-workflow

Skill Tier What it adds Upstream
respond-to-eval core Turn student course evaluations (free-text + numeric) into an actionable teaching-improvement plan — the teaching analogue of /respond-to-referees. Clusters comments into themes, separates signal from noise, classifies each theme Keep / … source
lit-review adjacent Structured literature search + synthesis with citation extraction, thematic clustering, and gap identification. Use when user says "find papers on X", "do a lit review", "what's the literature on...", "summarize what we know about...", … source

Source: ruvnet/claude-code-flow

Skill Tier What it adds Upstream
Hooks Automation adjacent Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre$post task hooks, session management, Git integration, memory coordination, and neural pattern training … source
dossier-collect adjacent Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel source
research-synthesize adjacent Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations source

Source: ruvnet/ruflo

Skill Tier What it adds Upstream
Hooks Automation adjacent Automated coordination, formatting, and learning from Claude Code operations using intelligent hooks with MCP integration. Includes pre$post task hooks, session management, Git integration, memory coordination, and neural pattern training … source
dossier-collect adjacent Build a graph-structured dossier on a seed entity via parallel fan-out + recursive expansion across web, memory, knowledge-graph, codebase, ADR index, and git intel source
research-synthesize adjacent Synthesize research findings from memory into structured reports with evidence grading, contradiction resolution, and actionable recommendations source

Source: samber/cc-skills-golang

Skill Tier What it adds Upstream
golang-security adjacent Security best practices and vulnerability prevention for Golang. Covers injection (SQL, command, XSS), cryptography, filesystem safety, network security, cookies, secrets management, memory safety, and logging. Apply when writing, … source

Source: silverstein/minutes

Skill Tier What it adds Upstream
minutes-search core Search past meeting transcripts and voice memos for specific topics, people, decisions, or ideas. Use this whenever the user asks "what did we discuss about X", "find that meeting where we talked about Y", "what did Alex say", "did we … source

Source: yaojingang/yao-meta-skill

Skill Tier What it adds Upstream
note-cleanup adjacent Clean messy meeting notes into structured markdown summaries. Use when asked to organize meeting notes, extract action items, separate decisions from open questions, or turn rough notes into a clean recap. source

Source: zechenzhangAGI/AI-research-SKILLs

Skill Tier What it adds Upstream
knowledge-distillation core Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. … source
gptq adjacent Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs … source
optimizing-attention-flash adjacent Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster … source
pytorch-fsdp2 adjacent Adds PyTorch FSDP2 (fully_shard) to training scripts with correct init, sharding, mixed precision/offload config, and distributed checkpointing. Use when models exceed single-GPU memory or when you need DTensor-based sharding with … source
quantizing-models-bitsandbytes adjacent Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit … source
unsloth adjacent Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization source