Your Agent Isn't "Occasionally Wrong" — It's Quietly Burning Money Every Day

The request returns 200. The JSON parses cleanly. Every field is there. But the output is already wrong — the model mangled a tool argument, called a tool it should never have called, or "finished" inside a truncated response. One step more hidden: silent provider downgrade, where high-peak traffic quietly gets routed to a cheaper model, responses keep coming back, quality slides, and the bill does not move.

The most expensive failure is not the one that errors. It is the one that doesn't. It happens in the moment every real request arrives — and your logs, dashboards, and bill all look perfectly normal.

1. The most expensive failure doesn't report an error

Three silent shapes, and any real agent can hit them:

• Mangled tool arguments. The model flips to and from; the call succeeds, returns 200, and the email goes to the wrong person. Nobody sees an error, because the program "worked."
• Truncation that pretends to finish. The output is cut off, and the model wraps up into a clean-looking ending instead of telling you it didn't finish. You assume completion; the second half of the task never ran.
• Silent provider downgrade. You pay flagship prices; at peak traffic your calls get routed to a cheaper model. Responses keep returning, quality drifts down, the bill does not.

These shapes are not guessed. We catalogued them on a dataset anyone can download and check line by line: Correctover-CCS-20K-Verification-Subset.jsonl.gz in the ccs-v1.0 release of the GitHub repo Correctover/standards — 20,000 real LLM API traces across 13 providers and 33 models. This is not a claim we ask you to take on faith.

2. Why a single call never looks wrong

A test runs once. It executes against a frozen snapshot in a sandbox, and then it stops caring. Runtime faces every real call. An agent's behavior is not a fixed code path; it is a negotiation between a model and a set of tools, and which tool it reaches for on a given request cannot be fully predicted at build time.

Silent failures happen in the moment a real request arrives — in the tool the model actually chose, in the response it actually returned. Every single call looks fine, because the anomaly is never inside "this call." It lives in the gap between what was actually invoked and the contract you declared. You cannot test a gap; only a check that is present on every call can see it.

3. Do the math: what a month of silent failure costs

I am not going to put a number here, because only you know your call volume. Fill in three of your own:

Input	Your value
N: agent calls per month	____
M%: retry rate caused by low-quality / downgraded output (0 if unknown)	____%
C: cost per call (¥)	____

Waste per month from silent failure ≈ N × M% × C.

That number comes from your inputs, not our estimate, and nobody filled it in for you. Once you have it, look at the price: ¥0.7 per scan, ¥7 for 10. If your waste number is bigger than ¥7, what you need is not 10 scans — it is scanning this whole agent once.

4. The only way to make silent failure visible

One method makes these failures surface: at the moment each call lands, compare the actual invocation against the declared contract — which model actually ran, which tool was called, whether the arguments were right, whether the response went out of bounds, whether it faked completion.

Logs and dashboards miss this, because they record exactly the side that "looks normal." The 26 vulnerability patterns exist for this comparison: each one points at an observable deviation in a real call, not an abstract warning.

5. Results in 30 seconds

Your skill code, or a call record, can be scanned right now. Paste it in, all 26 patterns run, and you get a CCS compliance report. The first segment is free — see what it flags; if you want the detail behind a CRITICAL finding, the complete report is ¥0.7 (~$0.10). Less than a coffee, to know whether your agent is burning money today.

Do this now: 30 seconds

Export the trace from your most recent agent session, paste it in, and hit scan. The summary is free; the full report is ¥0.7.

Start here: register a free key at https://correctover.com/rating/register (5 free scans included) → paste the trace → scan.

What you'll see:

• Free segment: the titles of the first few findings, so you know immediately whether the first one is CRITICAL
• The sting: a hit shows "attack path located," with the detail locked in the full report
• Unlock: the first findings are free; the rest, including the full attack path — ¥0.7

Sources in this post:

• 20,000 traces / 13 providers / 33 models → Correctover/standards release ccs-v1.0 (public, verifiable line by line)
• 26 vulnerability patterns / ¥0.7 / ¥7 for 10 → product configuration
• The three silent-failure shapes → the failure taxonomy built on that same trace dataset