Tool Call Hooks

Tool Call Hooks provide fine-grained control over tool execution during agent operations. These hooks allow you to intercept tool calls, modify inputs, transform outputs, implement safety checks, and add comprehensive logging or monitoring.

Overview

Tool hooks are executed at two interception points:

Point	When	Hook receives
`PRE_TOOL_CALL`	Before every tool execution	`ToolCallHookContext`
`POST_TOOL_CALL`	After every tool execution	`ToolCallHookContext` (with results set)

Write them with the @on decorator. The legacy @before_tool_call / @after_tool_call decorators keep working unchanged — both styles register on the same engine and run in one ordered chain.

Hook Signature

python

from crewai.hooks import on, HookAborted, InterceptionPoint, ToolCallHookContext

@on(InterceptionPoint.PRE_TOOL_CALL)
def before_hook(ctx: ToolCallHookContext) -> None:
    # Mutate ctx.tool_input in place, or
    # raise HookAborted(reason, source) to block the call
    ...

@on(InterceptionPoint.POST_TOOL_CALL)
def after_hook(ctx: ToolCallHookContext) -> str | None:
    # Return a string to replace ctx.tool_result
    # Return None to keep the original result
    ...

Unlike the boundary and step points, the tool-call points pass the rich ToolCallHookContext directly as the hook argument (there is no separate ctx.payload): mutate ctx.tool_input in place before the call, and return a string to replace the result after it.

When a call is blocked, the tool does not run and the agent receives "Tool execution blocked by hook. Tool: <name>" as the result — the run continues. POST_TOOL_CALL hooks still fire on blocked calls, so monitoring hooks see every attempt.

Tool Hook Context

The ToolCallHookContext object provides comprehensive access to tool execution state:

python

class ToolCallHookContext:
    tool_name: str                    # Name of the tool being called
    tool_input: dict[str, Any]        # Mutable tool input parameters
    tool: CrewStructuredTool          # Tool instance reference
    agent: Agent | BaseAgent | None   # Agent executing the tool
    task: Task | None                 # Current task
    crew: Crew | None                 # Crew instance
    tool_result: str | None           # Agent-facing result string (POST_TOOL_CALL only)
    raw_tool_result: Any | None       # Raw Python result (POST_TOOL_CALL only)

For typed tool outputs, tool_result is the string the agent sees. By default, this is JSON. If the tool uses custom formatting, it can be Markdown or another string. Use raw_tool_result when your hook needs the typed object or dictionary; it is not affected by result replacement.

The context also exposes request_human_input(prompt, default_message), which pauses live console updates and collects input from the terminal — useful for approval gates.

Modifying Tool Inputs

Important: Always modify tool inputs in-place:

python

# ✅ Correct - modify in-place
@on(InterceptionPoint.PRE_TOOL_CALL)
def sanitize_input(ctx: ToolCallHookContext) -> None:
    ctx.tool_input['query'] = ctx.tool_input['query'].lower()

# ❌ Wrong - replaces dict reference; the tool never sees it
@on(InterceptionPoint.PRE_TOOL_CALL)
def wrong_approach(ctx: ToolCallHookContext) -> None:
    ctx.tool_input = {'query': 'new query'}

Registration Methods

1. Global Hooks

Apply to all tool calls across all crews. Use tools= / agents= filters to scope a hook:

python

from crewai.hooks import on, HookAborted, InterceptionPoint

@on(InterceptionPoint.PRE_TOOL_CALL)
def log_tool_call(ctx):
    print(f"Tool: {ctx.tool_name}, input: {ctx.tool_input}")

@on(InterceptionPoint.PRE_TOOL_CALL, tools=["delete_file", "drop_table"])
def block_destructive(ctx):
    raise HookAborted(reason=f"{ctx.tool_name} is not allowed", source="safety-policy")

@on(InterceptionPoint.POST_TOOL_CALL, tools=["web_search"], agents=["Researcher"])
def log_search_results(ctx):
    print(f"search returned {len(ctx.tool_result or '')} chars")

2. Crew-Scoped Hooks

Apply the same decorator to a method inside a @CrewBase class to scope the hook to that crew only:

python

from crewai.hooks import on, InterceptionPoint

@CrewBase
class MyProjCrew:
    @on(InterceptionPoint.PRE_TOOL_CALL)
    def validate_tool_inputs(self, ctx):
        # Only applies to this crew
        if ctx.tool_name == "web_search" and not ctx.tool_input.get("query"):
            raise HookAborted(reason="empty search query", source="input-validation")

    @crew
    def crew(self) -> Crew:
        return Crew(agents=self.agents, tasks=self.tasks, process=Process.sequential)

Common Use Cases

1. Safety Guardrails

python

@on(InterceptionPoint.PRE_TOOL_CALL)
def safety_check(ctx: ToolCallHookContext) -> None:
    destructive = {'delete_file', 'drop_table', 'remove_user', 'system_shutdown'}
    if ctx.tool_name in destructive:
        raise HookAborted(reason=f"{ctx.tool_name} is destructive", source="safety-policy")

2. Human Approval Gate

python

@on(InterceptionPoint.PRE_TOOL_CALL, tools=["send_email", "make_purchase", "delete_file"])
def require_approval(ctx: ToolCallHookContext) -> None:
    response = ctx.request_human_input(
        prompt=f"Approve {ctx.tool_name}?",
        default_message=f"Input: {ctx.tool_input}\nType 'yes' to approve:",
    )
    if response.lower() != 'yes':
        raise HookAborted(reason="denied by operator", source="approval-gate")

3. Input Validation and Sanitization

python

@on(InterceptionPoint.PRE_TOOL_CALL, tools=["web_search"])
def validate_query(ctx: ToolCallHookContext) -> None:
    query = ctx.tool_input.get('query', '')
    if len(query) < 3:
        raise HookAborted(reason="search query too short", source="input-validation")
    ctx.tool_input['query'] = query.strip().lower()

@on(InterceptionPoint.PRE_TOOL_CALL, tools=["read_file"])
def validate_path(ctx: ToolCallHookContext) -> None:
    path = ctx.tool_input.get('path', '')
    if '..' in path or path.startswith('/'):
        raise HookAborted(reason="invalid file path", source="input-validation")

4. Result Sanitization

python

import re

@on(InterceptionPoint.POST_TOOL_CALL)
def sanitize_sensitive_data(ctx: ToolCallHookContext) -> str | None:
    if not ctx.tool_result:
        return None
    result = re.sub(
        r'(api[_-]?key|token)["\']?\s*[:=]\s*["\']?[\w-]+',
        r'\1: [REDACTED]',
        ctx.tool_result,
        flags=re.IGNORECASE,
    )
    return re.sub(
        r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b',
        '[EMAIL-REDACTED]',
        result,
    )

5. Tool Usage Analytics

python

import time
from collections import defaultdict

tool_stats = defaultdict(lambda: {'count': 0, 'total_time': 0})

@on(InterceptionPoint.PRE_TOOL_CALL)
def start_timer(ctx: ToolCallHookContext) -> None:
    ctx.tool_input['_start_time'] = time.time()

@on(InterceptionPoint.POST_TOOL_CALL)
def track_tool_usage(ctx: ToolCallHookContext) -> None:
    start_time = ctx.tool_input.pop('_start_time', time.time())
    tool_stats[ctx.tool_name]['count'] += 1
    tool_stats[ctx.tool_name]['total_time'] += time.time() - start_time

6. Rate Limiting

python

from collections import defaultdict
from datetime import datetime, timedelta

tool_call_history = defaultdict(list)

@on(InterceptionPoint.PRE_TOOL_CALL)
def rate_limit_tools(ctx: ToolCallHookContext) -> None:
    now = datetime.now()
    history = tool_call_history[ctx.tool_name]
    history[:] = [t for t in history if now - t < timedelta(minutes=1)]
    if len(history) >= 10:
        raise HookAborted(reason=f"rate limit exceeded for {ctx.tool_name}",
                          source="rate-limiter")
    history.append(now)

Hook Management

python

from crewai.hooks import (
    InterceptionPoint,
    clear_all_hooks,
    clear_hooks,
    get_hooks,
    unregister_hook,
)

# Unregister a specific hook
unregister_hook(InterceptionPoint.PRE_TOOL_CALL, my_hook)

# Clear one point, or everything (e.g. between tests)
clear_hooks(InterceptionPoint.POST_TOOL_CALL)
clear_all_hooks()

# Inspect what's registered
print(len(get_hooks(InterceptionPoint.PRE_TOOL_CALL)))

The legacy management API (register_before_tool_call_hook, unregister_before_tool_call_hook, clear_before_tool_call_hooks, clear_all_tool_call_hooks, get_before_tool_call_hooks, and their after_ counterparts) operates on the same underlying registries, so either API can manage hooks registered by the other.

Legacy Decorators

The original per-point decorators keep working unchanged and run in the same registration-order chain as @on hooks:

python

from crewai.hooks import before_tool_call, after_tool_call

@before_tool_call
def block_dangerous_tools(context):
    if context.tool_name in ('delete_database', 'drop_table'):
        return False  # Block execution
    return None

@after_tool_call(tools=["web_search"])
def sanitize_results(context):
    if context.tool_result and "password" in context.tool_result.lower():
        return context.tool_result.replace("password", "[REDACTED]")
    return None

Differences from @on:

Blocking is return False from a before hook — equivalent to raising HookAborted, but without a custom reason or source for telemetry. The agent sees the same "Tool execution blocked by hook" message.
Signatures are point-specific: before hooks return bool | None, after hooks return str | None. The context object is the same ToolCallHookContext.
Filters and crew-scoping work the same way: @before_tool_call(tools=[...], agents=[...]), and applying the decorator to a @CrewBase method scopes it to that crew.

Prefer @on for new code; keep the legacy style where it is already in use — there is no behavioral penalty.

Best Practices

Keep hooks focused and fast — they run on every tool call
Modify in-place — always mutate ctx.tool_input, never replace the dict
Prefer filters over conditionals — tools= / agents= keep hook bodies small
Abort loudly — raise HookAborted with a meaningful reason and source; any other exception is swallowed (fail-open)
Use type hints — annotate with ToolCallHookContext for IDE support
Clear hooks in tests — call clear_all_hooks() between test runs

Troubleshooting

Hook Not Executing

Verify the hook is registered before crew execution
Check whether an earlier hook blocked the call (subsequent pre hooks don't run)
Check tools= / agents= filters against the actual tool name and agent role

Input Modifications Not Working

Use in-place modifications: ctx.tool_input['key'] = value
Don't replace the dict: ctx.tool_input = {}

Result Modifications Not Working

Return the modified string from a POST_TOOL_CALL hook
Returning None keeps the original result

Tool Blocked Unexpectedly

Check all pre hooks for HookAborted / return False conditions
The abort reason and source appear on the HookDispatchedEvent telemetry

Overview

Hook Signature

Tool Hook Context

Modifying Tool Inputs

Registration Methods

1. Global Hooks

2. Crew-Scoped Hooks

Common Use Cases

1. Safety Guardrails

2. Human Approval Gate

3. Input Validation and Sanitization

4. Result Sanitization

5. Tool Usage Analytics

6. Rate Limiting

Hook Management

Legacy Decorators

Best Practices

Troubleshooting

Hook Not Executing

Input Modifications Not Working

Result Modifications Not Working

Tool Blocked Unexpectedly

Related Documentation