243 results in Hooks, Identity, Evals, Observability · page 7 of 11
HooksPreview
format-python-files
Automatically format Python files after any Edit operation using black formatter. This hook runs 'black' on any .py file that Claude modifies, ensuring consistent Python code formatting. Requires black to be installed ('pip install black'). The command includes error suppression (2>/dev/null || true) so it won't fail if black is not installed.
Automatically stage changes in git after file modifications for easier commit workflow. This hook runs 'git add' on any file that Claude edits or writes, automatically staging changes for the next commit. Includes error suppression so it won't fail in non-git repositories. Helps streamline the development workflow by preparing files for commit.
Automatically send Claude Code conversation traces to LangSmith for monitoring and analysis. Prerequisites: jq (brew install jq on macOS or sudo apt-get install jq on Linux), curl and uuidgen (usually pre-installed), LangSmith account and API key. Configuration: Install langsmith-tracing setting (npx claude-code-templates@latest --setting telemetry/langsmith-tracing) or manually add to .claude/settings.local.json the following environment variables: TRACE_TO_LANGSMITH=true, CC_LANGSMITH_API_KEY=lsv2_pt_..., CC_LANGSMITH_PROJECT=project-name, CC_LANGSMITH_DEBUG=true (optional). How it works: Runs in background on Stop event after each Claude response, reads conversation transcript, converts to LangSmith format, sends to LangSmith API, groups by thread_id for session continuity. Debugging: Check logs at ~/.claude/state/hook.log. Privacy note: System prompts not included in traces.
Open-source, OpenTelemetry-compliant LLM observability tool by Scale3Labs. It traces calls to all major LLM providers and frameworks with a self-hostable UI.
Literal AI is an observability and evaluation platform for conversational AI. It captures multi-step threads, scores responses, and integrates with Chainlit.
Open-source LLM observability and prompt management platform. It tracks conversations, errors, costs, and user feedback for production AI applications.
Maxim AI is an evaluation and observability platform for AI agents. It supports multi-step trace analysis, prompt testing, and production quality monitoring.
Hook bundle: Reference lifecycle hook definitions for ECC memory persistence. The production hook graph is hooks/hooks.json.. Use to persist and reload agent session state across compaction.
New Relic AI Monitoring instruments LLM calls end-to-end. It traces model invocations, measures token costs, and surfaces anomalies via the New Relic platform.
Enforce Next.js best practices, proper file structure, component patterns, and TypeScript usage with automated code reviews and suggestions. Validates Next.js App Router conventions, Server/Client component patterns, proper imports, and TypeScript usage. Provides real-time feedback on code quality and adherence to Next.js best practices.
Show notification before any Bash command execution for security awareness. This hook displays a simple echo message '🔔 About to run bash command...' before Claude executes any bash command, giving you visibility into when system commands are about to run. Useful for monitoring and auditing command execution.
Monitor bundle size and Core Web Vitals metrics during development, blocking deployments that exceed performance budgets with detailed reports. Automatically analyzes Next.js build output, checks bundle sizes against predefined budgets, and provides optimization recommendations. Hook triggers on PostToolUse for build-related operations and file changes that could affect performance.
Planning gate that warns when editing production code without an approved specification. Checks for recent .spec.md files in the project directory (last 14 days). If no spec is found, shows a warning suggesting to create one first. Non-blocking (exit 0) — acts as a reminder, not a hard gate. Supports 16 programming languages. Part of the Spec-Driven Development (SDD) methodology where every implementation should be backed by an approved specification.