agentleFS
arcjetarcjet/skills/integrate-arcjet-guard-strands-agents-py/SKILL.md

integrate-arcjet-guard-strands-agents-py

Skill4 starsChanged 6 months agoApache-2.0View on GitHub

Integrate Arcjet Guard into Python Strands Agents — wrap authored @tool with guard_tool, and put guard_hooks on Agent(hooks=) for unwrapped / MCP tools via BeforeToolCallEvent.cancel_tool. Use when asked to add Arcjet to strands / strands-agents, rate limit those tools, screen inbound messages, or block prompt injection / PII. This is Python strands, not JS @strands-agents/sdk.

  • Installs packages

The file

We split this skill into the rules it gives an agent

8 rules. About 0 are common, 3 are distinctive, and 5 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Do not invent a second example name.

    line 44
  2. Distinctive:

    Ask only what you cannot infer from the code.

    line 73
  3. Very specific:

    Default: none. Put the conversation / session id you already have on invocation_state *and* on guard_hooks(...).

    line 80
  4. Very specific:

    This is not JS @arcjet/guard/strands-agents/v1: Import arcjet.guard.strands_agents.

    line 91
  5. Very specific:

    Fail closed = always set cancel_tool on error: Do not raise and do not leave it unset.

    line 97
  6. Very specific:

    Correlation is read, never minted: Never trace_id, never agent.id, never SessionManager auto-ids.

    line 99
  7. Distinctive:

    If the agent has no guard client yet, launch one once at module scope:

    line 117
  8. Very specific:

    Do not invent a second example name.

    line 227

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Integrate Arcjet Guard into Python Strands Agents

arcjet.guard.strands_agents wraps the agent's existing Arcjet client. It never talks to the Arcjet API itself. Shared Guard fundamentals (client, rules, labels, decisions, capture, registration) live in ../arcjet/references/guards_python.md. Load that reference for anything that is not Strands-specific.

Official Python strands / strands-agents>=1.11.0,<2 only — not JS @arcjet/guard/strands-agents/v1 (docs https://docs.arcjet.com/guards/strands-agents/), not community forks. Importing arcjet.guard.strands_agents does not load LangChain, CrewAI, or JS @arcjet/guard/strands-agents/v1. Unlike CrewAI (no extra), the arcjet[strands-agents] extra exists at the pin (strands-agents = ["strands-agents>=1.11.0,<2"] in pyproject.toml). The extra is safe (no chromadb).

Exports: guard_tool, guard_hooks, strands_agent_context. Authored @tool plus Agent(hooks=) / add_hook.

Three surfaces, one decision rule:

  • An authored @tool → guard_tool. Hand the agent the copy this returns — the original stays unguarded.
  • Unwrapped / MCP tools → guard_hooks. Gate is per-tool BeforeToolCallEvent.cancel_tool (True or str). Already-wrapped tools are skipped so Guard is not called twice.
  • Correlation → strands_agent_context reads a caller-owned id from invocation_state. It never mints. It never reads trace_id.

Docs: https://docs.arcjet.com/guards/strands-agents/. Example: examples/fastapi-strands-agents-guard. Do not invent a second example name.

The gate is per-tool BeforeToolCallEvent.cancel_tool

guard_hooks registers on that event so the tool never runs on DENY (or unevaluated Guard under the default on_guard_error="deny"). A string is the cancel message (JSON of ArcjetDenialResult); True uses Strands' default message and drops the fields. Fail closed: always set cancel_tool on error — do not leave it unset and do not raise. Same fail-closed default as #196: only "allow" fails open; a DENY always blocks. Core guard() still fails open (has_failed_open()).

event.interrupt() is not a policy gate

BeforeToolCallEvent.interrupt() / resume is human-in-the-loop. Same trap as CrewAI human_input, JS humanInTheLoopMiddleware, LangGraph interrupt(), OpenAI Agents needsApproval, and Genkit interrupt(). There is no inbound helper and no approval helper.

Screen inbound before Agent(...) / __call__ / stream_async

There is no inbound helper. Call aj.guard(...) in the application and act on the decision. Core guard() fails open: ALLOW is not proof the rules ran. Gate on decision.has_failed_open() if this call site must fail closed; guard_tool / guard_hooks already default to that.

Questions to ask the human first

Ask only what you cannot infer from the code; suggest defaults.

  1. Which tools are risky (external side effects, irreversible, spends money, sends messages)? Those get guard_tool. MCP / unwrapped tools you did not author get guard_hooks.
  2. What limits? (e.g. "10 lookups/min per user" → TokenBucket.)
  3. Who is the user for metadata — an opaque user/tenant ID (never PII)? Default: none. Put the conversation / session id you already have on invocation_state and on guard_hooks(...). That id is the correlation id, not the user.
  4. Is an Arcjet outage unacceptable? Every helper defaults to on_guard_error="deny". Ask explicitly about inbound screening before the agent runs: failing closed there means the agent does not run, so "allow" is a routine and legitimate choice at that one call site.

The things readers get wrong

  1. This is not JS @arcjet/guard/strands-agents/v1. Import arcjet.guard.strands_agents.
  2. There is no inbound helper. Screen with core guard() before Agent(...) / __call__ / stream_async.
  3. event.interrupt() is HITL, not policy. Deny is cancel_tool (True or str).
  4. Fail closed = always set cancel_tool on error. Do not raise and do not leave it unset.
  5. Correlation is read, never minted. Never trace_id, never agent.id, never SessionManager auto-ids.
  6. Already-wrapped tools are skipped by guard_hooks so Guard is not called twice. Hand the agent the copy guard_tool returns.
  7. Key rate limits on the authenticated caller, not a model-supplied order id.
  8. Do not hand-wrap every Strands tool with raw guard().
  9. inputs= is accepted. A missing decision is not a denial — verify in Console/CLI.

Step 1: Install and find the guard client

Requires PyPI arcjet 1.1.0 (the extra is not in 1.0.0):

pip install "arcjet[strands-agents]"

If the agent has no guard client yet, launch one once at module scope:

import os
from arcjet.guard import launch_arcjet

aj = launch_arcjet(key=os.environ["ARCJET_KEY"])

Step 2: Gate authored tools — guard_tool

from strands import Agent, tool
from arcjet.guard import DetectPromptInjection, TokenBucket, launch_arcjet
from arcjet.guard.strands_agents import guard_hooks, guard_tool, strands_agent_context

aj = launch_arcjet(key=os.environ["ARCJET_KEY"])
lookup_limit = TokenBucket(
    label="order.looked-up",
    bucket="lookups",
    refill_rate=10,
    interval_seconds=60,
    max_tokens=10,
)
mcp_limit = TokenBucket(
    label="mcp.invoked",
    bucket="mcp-access",
    refill_rate=20,
    interval_seconds=60,
    max_tokens=20,
)
inbound = DetectPromptInjection()
user_id = authenticated_user_id

@tool  # event.interrupt() is HITL — not this policy gate
def lookup_order(order_id: str) -> dict:
    """Look up an order by ID."""
    return {"order_id": order_id, "status": "shipped"}

lookup_order = guard_tool(
    guard=aj,
    tool=lookup_order,
    action="order.looked-up",
    rules=[lookup_limit(key=user_id, requested=1)],
    on_guard_error="deny",
)

Step 3: Gate unwrapped / MCP tools — guard_hooks

mcp_tools = []  # from an MCP client you did not wrap with guard_tool
agent = Agent(
    tools=[lookup_order, *mcp_tools],
    # The agent-wide gate for tools guard_tool did not wrap.
    # Already-wrapped tools are skipped, so Guard is not called twice.
    # BeforeToolCallEvent.cancel_tool is True or a str (JSON of the payload).
    hooks=[
        guard_hooks(
            guard=aj,
            action="mcp.invoked",
            rules=[mcp_limit(key=user_id, requested=1)],
            session_id=conversation_id,
            on_guard_error="deny",
        ),
    ],
)

Step 4: Screen inbound before the agent runs

invocation_state = {"sessionId": conversation_id}
derived = strands_agent_context(invocation_state)
decision = await aj.guard(
    label="message.received",
    rules=[inbound(user_text)],
    correlation_id=derived.correlation_id,
)
if decision.conclusion == "DENY":
    raise RuntimeError("message blocked")
if decision.has_failed_open():
    raise RuntimeError("inbound guard unavailable")

agent(user_text, invocation_state=invocation_state)

There is no inbound helper.

Step 5: Correlation

strands_agent_context reads a caller-owned id from invocation_state: correlationId, then sessionId, then requestId. It never mints an id. It never reads trace_id. It never reads agent.id or SessionManager auto-ids. Do not invent a correlation id per turn. Put the same id on the invocation and on guard_hooks(...).

Verify the integration

  1. python -m py_compile (or the project's type-check) passes.
  2. Exercise inbound PI (before the agent runs), a guard_tool deny, a guard_hooks deny on an unwrapped tool (cancel_tool is True or a str), a rate limit, and fail-closed (an unreachable guard). Confirm event.interrupt() is never called as the gate.
  3. Confirm in the Arcjet Console / CLI that decisions share the caller-owned session / request id — not a trace_id or agent.id.
  4. Manual E2E with a real ARCJET_KEY is still-to-verify until you run it.

Worked example: examples/fastapi-strands-agents-guard. Do not invent a second example name. Do not add an example in this skills repo.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.