Ranked by score, best first. Every title opens the source in a new tab.
Generated scored by claude-haiku-5-5, takes by claude-opus-5-5RSS
Score 8.0 out of 10
Claude Code 2.1.317 (opens in a new tab)
Worth reading for onFailure: "block": a failing hook now stops the action instead of passing silently. A broken check that fails open was no check at all. Law 4.
why 8.0
Changelog adds an auto-mode subagent check gap notice, a block-on-failure hook option, and a nested session change; harness-level mechanics, new this week.
relevance 8/10 · novelty 8/10
Score 7.0 out of 10
Do Agents Still Follow the Rules? Benchmarking Rule Compliance under Agent Context Compaction (opens in a new tab)
Worth reading. Compaction is lossy replay, and this measures rule loss inside a real harness loop, not in isolation. Pin rules outside the compacted region. Law 1.
why 7.0
Measures rule compliance after context compaction inside a full agent harness; isolates a context failure mode.
relevance 7/10 · novelty 7/10
Score 7.0 out of 10
When Neither Side Confirms: Destructive Tool Approval Across MCP Servers and Hosts (opens in a new tab)
Strong. An estimated 90% of sampled destructive MCP tools lack an approval signal; server and host each assume the other confirms. Audit your host's prompt policy.
why 7.0
Measures MCP destructive-tool approval gaps in source code; permission model finding with concrete numbers.
relevance 7/10 · novelty 7/10
Score 6.0 out of 10
VeriHarm-Bench: Measuring Harmful Success in LLM Coding Agents Verifiably (opens in a new tab)
Useful. Task success hides collateral damage from shell access. A benchmark that verifies harm separately from the goal check is the right shape. Law 4.
why 6.0
Measures harmful side effects of coding agents with shell access; a measured failure mode.
relevance 6/10 · novelty 6/10
Score 6.0 out of 10
MCP Tool Poisoning in Agentic AI Frameworks: A Cross-Framework Measurement Study (opens in a new tab)
Solid. Tool descriptions and responses enter context unvalidated; this confirms real execution across frameworks, not just model compliance. Every MCP server you add is untrusted text.
why 6.0
Cross-framework measurement of MCP tool poisoning with real execution; measured failure mode in agent harnesses.
relevance 6/10 · novelty 6/10
Score 6.0 out of 10
Optimize the Harness, Not the Model: Fitting a Minimal Agent to a Self-Hostable LLM for Investigative Analysis (opens in a new tab)
Good method. Admit a tool or loop component only if it measurably improves accuracy on expert-validated data. Same model, different harness, different agent. Law 3.
why 6.0
Fits minimal agent harness components to a self-hosted model; shows which loop parts matter.
relevance 6/10 · novelty 6/10
Score 6.0 out of 10
Harvesting SWE Benchmarks from Wild Vibe Coding Sessions (opens in a new tab)
Practical. Turning your own agent session logs into executable tasks gives you evals on your repo instead of public benchmarks. The hard part is untangling evolving requirements.
why 6.0
Builds SWE benchmarks from vibe-coding session logs; a concrete eval technique for coding agents.
relevance 6/10 · novelty 6/10
Nothing of this kind on this day.