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Ask HN: How do you manage skills files?

A Hacker News thread debates whether agent skill files are worth managing, citing 2–4x output-token reductions on flagship models in one company's testing.

Commenters argue skills are stored prompts that help less-technical users compensate for weak prompting, while one participant reports company testing found skills reduce flagship-model output tokens by roughly 2–4x, a gap growing with newer models. Others note skills can bundle reusable scripts and inline commands for deterministic context building, and that harnesses now execute backticked commands before the agent sees the skill. Some argue improving model capability makes downloadable skills redundant.

Hacker News · security · 9d agoAI tools & infraHN 303↑ · 271 comments

How well do agents use test/verification techniques?

Dan Luu's eval finds coding-agent testing instructions (TDD, formal methods, PBT, skills) mostly fail to beat defaults on Zstd implementation correctness.

The author ran 26 prompt conditions plus 4 skills on a Zstd-in-Rust implementation eval using codex with GPT-5.6, testing TDD, fuzzing, property-based testing, formal methods (Lean 4, TLA+, Verus, Kani, SMT solvers) and community skills. Nothing dramatically outperformed the default no-instruction condition, which did above average; at xhigh effort, fuzzing and PBT conditions did slightly better than formal methods. Pre-registered predictions included TDD underperforming and popular test skills (ECC, Hegel, Trail of Bits) not outperforming. Results are averages of 80 runs per condition plotted against cost.

Hacker News · security · 7d agoAI researchHN 131↑ · 50 comments

COBRA-Skills: Contextual Bandit-Guided Evolution for Agent Skill Optimization

COBRA-Skills uses contextual bandits to guide LLM agent skill evolution, cutting optimization cost 55-58% versus SkillOpt while topping six agent benchmarks.

COBRA-Skills formulates LLM agent skill optimization as budgeted sequential optimization over a dynamically evolving candidate space. It couples contextual-bandit-guided prioritization with evidence-grounded skill evolution, selectively spending execution-based evaluations on promising candidates while refining skills from feedback. Across six heterogeneous agent benchmarks and three target models, it achieves the strongest average performance while reducing optimization cost by 55-58% relative to SkillOpt using only 50 unique optimization examples per benchmark. The method remains robust to agent harness changes and works when the target model generates its own skills.

Hugging Face daily papers · 6d agoAI research

Beyond Top-k Skill Retrieval: Diversity-Aware Skill Routing for LLM Agents

DSR reranks LLM agent skills with Determinantal Point Processes to favor complementary, non-redundant sets, improving multi-skill query coverage.

The paper proposes Diverse Skill Routing (DSR), a diversity-aware reranking framework for LLM agent skill routing that uses a Determinantal Point Process to balance query relevance and non-redundancy across large skill registries. DSR introduces a query-residual diversity kernel that penalizes redundant skill overlap while avoiding penalties arising only from shared query relevance. On the SkillRouter benchmark, DSR improves recall and full coverage over a strong pointwise reranking baseline, with the largest gains on multi-skill queries. The authors argue skill routing should be treated as complementary set selection, not just relevance ranking.

Hugging Face daily papers · 11d agoAI research

The /wayfinder Skill: Navigating the “Fog of War” of Planning

Matt Pocock released the /wayfinder skill, an orchestrator layer that manages planning sessions, maps, and tickets for AFK coding agents.

Latent Space interviews Matt Pocock, whose AI Skills for Real Engineers project has 220,000+ GitHub stars, about his new /wayfinder skill. The skill manages agent context during ambiguous planning by splitting work into grilling, prototype, research, and task tickets organized under a shared map, enabling overnight AFK agent runs. It uses deliberate terminology like map, ticket, and session to steer agent behavior, and was tested on projects including a personal website rearchitecture.

Latent Space · 26d agoAI tools & infra

AIR raises $50M to help companies vet the skills and add-ons AI agents use

AI security startup AIR exits stealth with $50M across two seed rounds to continuously vet skills, plugins, and MCP servers used by enterprise AI agents.

AIR, founded by Unit 8200 veterans Yair Saban and Niv Hoffman, raised $10 million led by Sequoia and $40 million led by Greenoaks to secure the emerging AI agent software supply chain. Its platform discovers agents in enterprise environments, intercepts their actions, and continuously vets skills, add-ons, and MCP servers against a maintained whitelist, filtering out about 27% of found add-ons. The company claims over 20 customers, roughly a quarter large enterprises, with strong demand in financial services and pharma, and competes with Noma Security, Zenity, Astrix Security, and Operant AI.

TechCrunch · Security · 14d agoAI industry

Cybersecurity job ads demanding AI skills double in a year

AI skill requirements in G7 cybersecurity job postings doubled year-over-year to 28.5%, with AI-skill roles paying a 14.9% salary premium.

Research from the AI Workforce Consortium, Cornerstone and Indeed covering April 2024 to March 2026 found that 28.5% of G7 cybersecurity job postings between October 2025 and March 2026 required AI skills, double the 14.2% a year earlier. Lightcast salary data put median advertised pay for AI-skill postings 14.9% above the overall cybersecurity median in the US. Senior-titled postings grew 65% in six months while junior titles only recently returned to growth, and a Cisco survey of 8,000 security leaders flagged hands-on AI-agent experience and technical depth as the biggest entry-level gaps.

Help Net Security · 22d agoIndustry