Deep dives into working agents.

Anthropic Just Revealed 7 New Rules for Prompting Claude 5 Models

Claude Opus 5 and Fable 5 are trained for end-to-end task execution, which inverts old prompting wisdom. Seven rules from Anthropic's guides and keynotes: (1) give the whole job (job + why + guardrails + done), not step-by-step; (2) use the 'interview me' skill to surface unknowns before complex tasks; (3) prompt the why, not just the what; (4) define what done looks like + output style (long-running models over-produce); (5) swap hard rules for reasoned instructions; (6) avoid double-checking prompts (they self-verify) and drop 'think step-by-step'/CAPS; (7) fix Claude's voice once in global instructions. Golden rule: 'Think of Claude as a brilliant but new employee — show your prompt to a colleague; if they'd be confused, Claude will be too.'

Google's 124 Free AI Powers — Running Them in the Claude App (No Code)

Hyperautomation Labs walks through github.com/google/skills — 124 official Apache-2.0 Agent Skills (18.7k stars) — and runs the best three live in the Claude app with no terminal: a handwritten note turned into a dated table, a Nano Banana Pro image tool producing a real 722KB image from one sentence, and Google's security checklist finding hardcoded keys, eval RCE, no-auth admin, and SQL injection in a real app.

Gemini 3.7 Flash: You're Only Using 20% of Its Prompting Power

BitBiasedAI breaks down how to actually use Gemini 3.7 Flash per Google's docs: retire persona/flattery/temperature tricks (over-engineering makes it worse), use the C.L.E.A.R.E.R. framework, treat coding prompts as engineering tickets ('report the results'), label screenshots observed/inferred/unknown, use reasoning as a dial, and replace 'are you sure?' with an observable audit.

My Honest Advice to CEOs Who Vibe Code

Brainqub3's codebase-audit veteran warns vibe-coding founders: agents output the plausible, not the correct — so treat Claude Code/Codex as an untrusted contractor bound to a 5-element delivery contract (agreed delivery, constraints+guardrails, proof, verification, ownership). Proof and verification are different.

DeepSeek Harness: FREE 1 Hour Course — From Install to Agentic OS

Julian Goldie's full DeepSeek Harness course in three levels: install in 5 minutes + Look/Produce/Rules prompting + trajectory view, then the 'everything is a plugin' architecture with Creator Mode and the hidden .dsh config, and finally the agentic OS — one dashboard with Obsidian as shared plain-text memory. Model + harness = agent.

A Single Claude Code Skill Just Hit #1 on GitHub — 27 Diagram Types

Signal Coders audits the #1 trending repo on GitHub — one person's single diagram skill with 27 types. It breaks the official 100-word description rule (and is right to), nails the three-level loading with a 1:15:45 ratio, and adds two gates the rest of the industry is missing: a style gate that refuses branded work, and a taste gate that asks 'would a table do the same job?'

Anthropic Just Published Official Claude Skills

Signal Coders audits Anthropic's official skills repository: 17 real skills (including the production document skills that power Claude's product features), 70 scripts, a 6-line template, a confession about Claude 'undertriggering' skills, and five lessons on instruction-file craft portable to any agent.

Ultimate Obsidian Agent Guide (OpenClaw + Hermes)

ZazenCodes shows how to manage an Obsidian vault with coding agents across four levels: local Claude Code/Codex, remote control, always-on OpenClaw + Hermes on a VPS, and a custom Pi 'Vault Steward' agent. Git version control, the AGENTS.md file, and Kepano's official Obsidian skills are the backbone.

Nao: Free Open Source AI Data Analyst — Chat With Your Data

A hands-on walkthrough of Nao, the free open-source analytics agent that lets anyone on your team chat with your data warehouse. Build agent context like a file system, unit-test reliability, and deploy a chat UI with your own LLM key — fully self-hosted.

Prime Agent: #1 on GitHub — The Free Claude Code Alternative That Learns From Every Session

Signal Coders' deep code review of Prime Agent, the #1 repo on GitHub: a coding agent that edits its own instructions with an immutable base prompt, one-tool IPython architecture, fire-and-forget sub-agents, four-budget autonomous mode with quality gates, and the most honest sentence in agent documentation this year.

A Formal Language for Writing Agent Instructions: Matt Pocock's Skills v1.2.0

A twelve-minute walkthrough of five new skills and a major infrastructure update for the most-starred agent skills repository on GitHub — now 204K stars, MIT-licensed, and an official Claude Code marketplace plugin alongside new Codex sidecar files. The headliner is /wait-what for Opus verbosity, /grill-me with multi-question dependency graphs, and /wizard for deterministic provisioning — but the skill nobody called exciting is the one worth reading: /writing-for-agents, an 81-line formal language for designing instructions agents consume — context pointers, the two loads, information hierarchy, completion criteria, leading words, negation as a failure mode, and pruning.

Forgetting as the Compression Step: Tencent's Agent Memory Engine, Checked

Tencent open-sourced an MIT agent-memory plugin that improves results by throwing information away: verbose tool logs fold into a Mermaid graph with node_ids you can grep back, and long-term memory climbs an L0-to-L3 pyramid modelled on Tulving's 1972 consolidation arrow. The repo is real (10,811 stars), the architecture is documented, and the benchmark table publishes raw token counts - so the presenter divides them on camera and finds one row that does not reconcile: SWE-bench prints -33.09% but computes to -31.63%. He also flags that every number is vendor-produced with no independent reproduction, and names the open GitHub issue where prompt-cache invalidation claws back part of the saving. The gains shrink as tasks get harder: +51.52% on WideSearch, +9.93% on SWE-bench. The video's own description gets this wrong; the video does not.

Wayfinder: Planning as a Map You Can Leave and Return To

Most agent planning tools die at the edge of a context window, and the real cost is not lost notes but trimmed ambition. Matt Pocock's Wayfinder skill moves the plan out of the session and into the issue tracker as a map of decision tickets, so work outlives any single conversation. Reading the skill source alongside the video surfaces two constraints the video never states: every ticket is either human-in-the-loop or agent-driven, and the skill forbids an agent standing in for the human's side of a discussion — the rule that keeps a decision map from looking complete while encoding nobody's judgement.

System Prompts Leaks GitHub Explained: What AI Agent Prompts Reveal

Alex Hitt breaks down the system_prompts_leaks repository — 43,600+ stars on GitHub — revealing how researchers verify leaked AI system prompts, the four-layer architecture inside commercial models, and why prompt obfuscation as a competitive moat is dead.

Don't Waste Time on Specs — /prototype Instead

Matt Pocock argues that spec-driven AI development wastes effort. His /prototype skill creates throwaway code artifacts at higher fidelity than discussion, letting you iterate on live UIs and logic before handing off to production — bridging the gap between spec and working software.

What Would It Cost to Run Claude Fable 5 Locally?

Kimi K3: An Open Source #1 — Coding Tests vs Fable 5, Opus 4.8 & GPT-5.6 Sol

Codex vs Fable: Which AI Agent Picked the Better Problem?

Nate B Jones gave Fable and Codex the same open brief: inspect his real business and build the automation that matters. Fable chose the higher-leverage strategic problem; Codex chose the safe, finishable one. Neither was wrong — they optimized for different things. The real unlock: letting AI help choose the problem, not just the tool.

I Replaced Hermes Agent And OpenClaw With This

mattpocock/skills: Learn the Whole Flow, End-to-End

First proper tutorial for the 162K-star skills repo (7.5M downloads, 38 skills). Complete main flow walkthrough: install via npx, configure issue tracker (GitHub/Jira/Linear/local), grill-with-docs interview, to-spec compression, to-tickets breakdown (each ticket = one context window), implement with auto code review via sub-agents. Smart zone concept (~140K tokens). Only 660 tokens context load despite 38 skills.

Claude Fable, Claude Tag, and Anthropic's Culture — Cat Wu & Thariq Shihipar ft Simon Willison

Don't Ship Skills Without Evals — Philipp Schmid, Google DeepMind

Philipp Schmid (Staff Engineer, Google DeepMind) reveals that almost none of 50,000+ indexed skills have evals. Covers the full lifecycle: capability vs preference skills, 8 writing tips, a practical eval harness (117 test cases, ~90% accuracy for Gemini Interactions API), and Google DeepMind's CI-style eval workflow where skill changes don't merge without improving tests.

This Skill Makes Claude BRUTALLY Honest About Your Ideas

Brad built a /focus-group skill that clones your real customers into AI agents. Paste any landing page, offer, or email and get honest reactions — not yes-man validation. Two-round system with persistent memory, real customer quotes, and actionable holdout analysis.

12 Hidden Settings to 10x Your Claude Code

Claude Code has hundreds of settings but you only need 12. Notification sounds, mobile push, smart allow lists (/fewer-permission-prompt), deny rules (.env + git push), Opus Plan + Sonnet Build (halve usage), effort level sweet spot (max is a trap), privacy/telemetry off, history retention 365 days, auto-compact at 75%, status line monitoring, prompt stashing (Ctrl+S), and removing AI commit attribution. Plus bonus: the prompting shift from steps to outcomes.