Hooks: Automating Reactions To Tool Calls

Hooks let you run scripts before or after Claude Code does anything. They're how you turn 'guidance' into 'enforcement' — or how you debug what the agent is doing.

10 min · Reviewed 2026

What hooks are

A hook is a small script Claude Code runs at a defined point in its lifecycle — before a tool call, after a tool call, when a session starts, when it stops. The hook can read what the agent is about to do, transform it, log it, or block it. Hooks are how you turn project rules from optional suggestions into enforced behavior.

The lifecycle events

Event	Fires when	Use it for
PreToolUse	Before any tool call	Block, transform, or log
PostToolUse	After any tool call	Validate result, audit
UserPromptSubmit	When you submit a message	Inject context, log queries
SessionStart	On `claude` start	Pull in project state
Stop	Session end	Cleanup, summary, audit log

Three hooks worth building

PreToolUse blocking destructive bash: refuse `rm -rf`, `git push --force`, `db:reset` unless explicit confirmation
PostToolUse format-on-edit: run Prettier or Biome after every Edit so files always land formatted
UserPromptSubmit context injection: pre-pend the result of `git status` so every prompt has fresh repo state

{ "hooks": { "PreToolUse": [ { "matcher": { "tool": "Bash" }, "command": "./scripts/block-destructive.sh" } ], "PostToolUse": [ { "matcher": { "tool": "Edit" }, "command": "pnpm prettier --write $CLAUDE_TOUCHED_FILE" } ] } }A minimal hooks block. The matcher decides which tool calls fire the hook; the command runs the script.

Where hooks beat CLAUDE.md

CLAUDE.md says 'don't push to main directly.' A hook BLOCKS pushes to main, period. Anywhere the cost of a mistake is high enough that 'usually respects' isn't good enough, a hook is the right answer. The model is no longer the only line of defense.

The big idea: prompts persuade, hooks enforce. Build hooks for the rules you actually need to hold.

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-claude-code-hooks-creators

What is the main idea of "Hooks: Automating Reactions To Tool Calls"?
1. Hooks let you run scripts before or after Claude Code does anything.
2. Use AI as the final authority for the whole decision
3. Avoid checking the answer once it sounds polished
4. Focus only on speed instead of judgment
Which concept is most central to "Hooks: Automating Reactions To Tool Calls"?
1. PreToolUse
2. hook
3. PostToolUse
4. lifecycle event
Which use of AI fits this topic best?
1. Let the AI decide what matters without your review
2. Use the answer before checking whether it fits the situation
3. PreToolUse blocking destructive bash: refuse `rm -rf`, `git push --force`, `db:reset` unless explicit confirmation
4. Treat the AI output as automatically correct
What should a careful learner remember about "Configured in settings.json"?
1. Use AI to draft or organize ideas about hook, then verify before acting.
2. Skip the context so the tool can guess faster
3. Treat the output as private even after sharing it online
4. Use the answer without checking the source
You want to use AI after this lesson. What is the safest next step?
1. Act immediately because the AI answer is written clearly
2. Use AI for drafting and comparison, but verify before publishing or relying on it.
3. Hide uncertainty so the final answer looks cleaner
4. Use private or sensitive details before checking permission
How should AI output about hook be treated?
1. As proof that no other source is needed
2. As a replacement for context, consent, or expert review
3. As a draft or helper output that still needs human judgment and verification
4. As something that becomes correct when it sounds confident
Name one way to verify an AI answer about hook.
Which action would help you apply "Hooks: Automating Reactions To Tool Calls" responsibly?
1. Use the tool to avoid thinking through the tradeoff
2. Keep going even if the output conflicts with a trusted source
3. Treat the AI output as automatically correct
4. PostToolUse format-on-edit: run Prettier or Biome after every Edit so files always land formatted

← Back to interactive lesson

Tendril · Creators · Tools Literacy

Hooks: Automating Reactions To Tool Calls

Hooks let you run scripts before or after Claude Code does anything. They're how you turn 'guidance' into 'enforcement' — or how you debug what the agent is doing.

10 min · Reviewed 2026

What hooks are

The lifecycle events

Event	Fires when	Use it for
PreToolUse	Before any tool call	Block, transform, or log
PostToolUse	After any tool call	Validate result, audit
UserPromptSubmit	When you submit a message	Inject context, log queries
SessionStart	On `claude` start	Pull in project state
Stop	Session end	Cleanup, summary, audit log

Three hooks worth building

PreToolUse blocking destructive bash: refuse `rm -rf`, `git push --force`, `db:reset` unless explicit confirmation
PostToolUse format-on-edit: run Prettier or Biome after every Edit so files always land formatted
UserPromptSubmit context injection: pre-pend the result of `git status` so every prompt has fresh repo state

{ "hooks": { "PreToolUse": [ { "matcher": { "tool": "Bash" }, "command": "./scripts/block-destructive.sh" } ], "PostToolUse": [ { "matcher": { "tool": "Edit" }, "command": "pnpm prettier --write $CLAUDE_TOUCHED_FILE" } ] } }A minimal hooks block. The matcher decides which tool calls fire the hook; the command runs the script.

Where hooks beat CLAUDE.md

The big idea: prompts persuade, hooks enforce. Build hooks for the rules you actually need to hold.

End-of-lesson check

8 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-claude-code-hooks-creators

What is the main idea of "Hooks: Automating Reactions To Tool Calls"?
1. Hooks let you run scripts before or after Claude Code does anything.
2. Use AI as the final authority for the whole decision
3. Avoid checking the answer once it sounds polished
4. Focus only on speed instead of judgment
Which concept is most central to "Hooks: Automating Reactions To Tool Calls"?
1. PreToolUse
2. hook
3. PostToolUse
4. lifecycle event
Which use of AI fits this topic best?
1. Let the AI decide what matters without your review
2. Use the answer before checking whether it fits the situation
3. PreToolUse blocking destructive bash: refuse `rm -rf`, `git push --force`, `db:reset` unless explicit confirmation
4. Treat the AI output as automatically correct
What should a careful learner remember about "Configured in settings.json"?
1. Use AI to draft or organize ideas about hook, then verify before acting.
2. Skip the context so the tool can guess faster
3. Treat the output as private even after sharing it online
4. Use the answer without checking the source
You want to use AI after this lesson. What is the safest next step?
1. Act immediately because the AI answer is written clearly
2. Use AI for drafting and comparison, but verify before publishing or relying on it.
3. Hide uncertainty so the final answer looks cleaner
4. Use private or sensitive details before checking permission
How should AI output about hook be treated?
1. As proof that no other source is needed
2. As a replacement for context, consent, or expert review
3. As a draft or helper output that still needs human judgment and verification
4. As something that becomes correct when it sounds confident
Name one way to verify an AI answer about hook.
Which action would help you apply "Hooks: Automating Reactions To Tool Calls" responsibly?
1. Use the tool to avoid thinking through the tradeoff
2. Keep going even if the output conflicts with a trusted source
3. Treat the AI output as automatically correct
4. PostToolUse format-on-edit: run Prettier or Biome after every Edit so files always land formatted

← Back to interactive lesson