Have you ever shipped something an agent said it had finished, and only found out weeks later that nothing had actually run? I have. The failures that cost me time were never the crashes: a crash is a gift, because CI sees it. The expensive ones exit 0, print nothing unusual, and quietly skipped the work.

So instead of trusting exit codes I went looking for them in recorded traffic. Everything below is measured: one small agent task — fetch headlines, write a draft, verify it through a tool — running in three frameworks behind a single recording proxy that keeps every attempt. Aggregating that recording, the failures all wore one of three shapes:

• the verification never ran
• an invented argument got accepted
• the answer was empty

Code, traces and the analysis scripts are on GitHub:

# one venv per framework (Python 3.12 - CrewAI requires <3.14)
uv venv .venv-strands   --python 3.12 && uv pip install --python .venv-strands/bin/python   "strands-agents[litellm]"
uv venv .venv-langgraph --python 3.12 && uv pip install --python

Shape 1: the verification never ran, and the run still said success

I removed an argument from the verification tool so that it returned a static count instead of checking the draft. Nothing errored. The tool ran, answered, and the run reported success with a draft that was never verified.

• Strands: all 3 runs exited 0. Verifications actually executed: 0/3
• CrewAI: all 3 runs exited 0. Verifications actually executed: 0/3
• LangGraph: all 3 runs stopped with a hard error (its tool calls live in code)

LangGraph is the only one that cannot slip through silently: its structure cannot step over a broken tool.

There is a nastier variant, where the tool did answer with an error and the process still exited 0.

Strands, argument-type level:
  tool error responses = 2, 1, 5 (three runs)
  process exit code    = 0, 0, 0

Those are not schema rejections. The call was well-formed; the tool answered with a processing error — "document 88 not found" — and every run still finished green.

Shape 2: the model invented a required argument, and the tool accepted it

I added a new required argument to the verification tool and never mentioned it in the prompt.

• Strands: all 3 runs had a plausible invented value accepted (0 errors)
• CrewAI: all 3 runs accepted (0 errors) — and all three invented the same sentence
• LangGraph: never reached the tool

The tool's only validation was "non-empty string".

Strands, 3 runs: "Check word count of AI agents news digest"
                 "AI agents digest word count check"
                 "Word count check for AI agents digest"
CrewAI,  3 runs: "Draft digest summarizing the five headlines into a flowing narrative"

Six fabricated values went straight through, and the recording is the only thing that shows where they came from.

That contrast is not purely a framework property, though: the two frameworks advertised the new parameter differently on the wire, and they did not sample the same way (see limitations).

Shape 3: the run said "done", and the answer was empty

This one only appeared in the model-driven frameworks.

Finish reason was stop, the visible answer was empty, and the draft was sitting inside the last tool-call argument.

• Strands: 2 runs (the content was in the tool argument: 100 and 106 words)
• LangGraph / CrewAI: 0 runs

A framework whose output node is the deliverable cannot produce this shape.

Where the evidence lives

  what the process reports           what actually happened
  ┌────────────────┐                ┌──────────────────────────────┐
  │ exit 0         │                │ tool call #1  → error        │
  │ "done" banner  │       ≠        │ tool call #2  → static stub  │
  └────────────────┘                │ verify        → never ran    │
                                    └──────────────────────────────┘
        evidence lives here  →       at the tool boundary (wire)

The error responses existed on the wire, and the tool layer even counted them. The process just never looked.

The evidence of a failure survives only outside the framework, at the tool boundary.

Invisible failures still cost money

A failure that gets reported as success keeps racking up wasted runs while nobody notices.

In a separate experiment (approval gates, crash recovery, duplicate execution, same proxy), it showed up in three ways:

• On crash recovery, the framework without state recording re-ran the whole task (2 LLM calls). The one with a checkpointer resumed with 0.
• An irreversible operation (in that experiment, publishing) executed twice under two different call IDs, and both returned success.
• Even the "did nothing" failure burned LLM calls: CrewAI 6, 5, 4; Strands 4, 5, 4.

Duplicates do not show up in the framework's own trace, either. Every duplicated call carried a different call ID, so on the wire they look like two unrelated requests.

And if the retry only rewords the same intent, an idempotency ledger keyed on the argument bytes cannot tell it apart:

  call ID: X ──> ledger ──> publish executes ──> success
  call ID: Y ──> ledger ──> publish executes ──> success
                   ↑ keys differ, so it doesn't look like a duplicate
  result: the side effect runs twice (both return success)

How to prevent it: the smallest check per situation

• Hobby pipeline → assert the deliverable is not empty
• In CI → assert the expected tool was actually called (never 0 times)
• Writing data → validate values (type, enum, known set)
• Handling approvals or billing → record approval and execution as separate states
• Need an audit → record at the boundary (the framework's own trace cannot reconstruct it)

The hobby case is the one I keep running into. Nothing errors, the log is calm, the artifact is empty or unverified — and you find out weeks later. If three lines of assertion catch that, I see no reason to leave them out.

The CI case is the same failure one layer up. If the only contract is the exit code, a skipped verification is invisible by construction.

"Did the verification tool run?" is a different question from "did the process succeed?"

For tools that write data, the invented argument is the dangerous one, because the value is well-formed. That no human ever wrote it is something only the wire recording can show.

And on approvals: approved once is not executed once. In these runs the same logical operation was settled twice under two different call IDs, and both returned success.

The two checks I actually use

Before anything downstream consumes the output, I assert exactly two things: the deliverable is not empty, and the tool I expected to run did actually run. Boring, a few lines each, and they would have caught every failure in this post.

Keys, ledgers and approval binding are for the moment the action touches money or another person. My honest read: most hobby pipelines do not need a ledger. They need the non-empty check and an exit signal they can trust.

Honest limitations

• 3 runs per cell. A trend, not a statistical claim.
• One model across all runs; a different model may reword or fabricate differently.
• The irreversible operation is simulated; whether a gate held is read from the recorded traffic.
• Fine instruction-following differences are hard to separate from the schema change itself.
• One framework sampled at temperature 0, and the parameter descriptions were not identical between the two — so the "varied vs repeated" contrast has at least two plausible causes.

This is a personal OSS project with no warranty. Use it at your own risk, and issues are welcome.