Found-Issues plugin logs bugs Claude ignores while working on other tasks

Found-Issues is a Claude Code plugin that solves a specific blindspot: coding agents (Claude included) often notice real bugs — missing null checks, leaked tokens, race conditions — while working on an unrelated task, then move on. The plugin logs those observations so they don't get lost.
How it works
The agent maintains a docs/found-issues.md file in each repo. When it spots something out of scope, it appends a one-line entry like:
- [open] 2026-05-08 src/auth.ts:88 — leaks token in error (suggested: redact)
- [fixed] 2026-05-06 lib/foo.py:42 — null check missing (PR: org/repo#41)The closure loop is fully automated. Hooks detect when a PR addresses a logged entry and annotate it. When the PR merges, a background sync flips [open] to [fixed]. If a referenced line gets deleted, tombstone detection auto-closes it. The open-issue count appears at session start and in your statusline — no manual bookkeeping.
Installation
In Claude Code, run:
/plugin marketplace add AltDoug/claude-plugins
/plugin install found-issuesThen start a new session and run /found-issues:setup — it walks you through wiring the statusline counter so the open-issue count is always visible.
Who it's for
Developers who use AI coding agents and want to catch bugs the agent notices but doesn't fix because they're out of scope.
📖 Read the full source: r/ClaudeAI
👀 See Also

Claude Code Hooks Implementation Project Covers All 23 Hooks
A developer has built a project entirely with Claude code that implements all 23 Claude code hooks, with a video explaining each hook's use case and a GitHub repository available.

Cowork Chrome Extension Automates Personal Data Removal from Data Brokers
A Reddit user reports that using the Cowork Chrome extension with a Gmail connection automated filling forms, writing emails, and verifying removal requests to delete personal data from major data providers in just a few hours.

agentcache: Python Library for Multi-Agent LLM Prefix Caching
agentcache is a Python library that enables multi-agent LLM frameworks to share cached prompt prefixes, achieving up to 76% cache hit rates and cutting inference time by more than half in tests with GPT-4o-mini.

Time Complexity MCP: Static Analysis Tool Feeds Big-O Complexity to AI Coding Agents
Time Complexity MCP is an open-source MCP server that performs static code analysis to detect Big-O complexity, feeding the results directly to AI coding agents like Claude Code or Copilot without token consumption. It supports JavaScript, TypeScript, Python, Java, Kotlin, and Dart.