assurance-budget
Your agent didn't fail. It just kept going.
The expensive runs are rarely the ones that crash. They are the ones that retried the same failing call fourteen times, or spent nineteen model calls summarising something nobody read, and finished with a plausible answer and a bill.
Point this at a run log and find out which ones did that.
pip install assurance-budget
assurance-budget runs.jsonl
On a system Python you may hit
error: externally-managed-environment(PEP 668). That is your OS protecting its packages, not this failing:python3 -m venv .venv && .venv/bin/pip install assurance-budget
1 of 4 runs hit a limit — 1 was going nowhere first — 1 ran past the clock
r-002
Stopped: 3 rounds repeating fetch(url=api/invoices) and failing the same way (timeout)
with nothing new read and no part of the goal closer.
r-003
Stopped after 20 frontier calls
r-004
Ran 660s against a 600s cap
Not tested by this log: iterations, retries. The log carries no events of that kind, so this
is silence rather than a pass.
That last paragraph is the part most tools leave out. A limit your log cannot exercise has not passed — it has not been tested, and reporting those the same way is how a green check comes to mean nothing.
A limit a caller can raise is a suggestion
The ceilings are constants in the library, and every budget is clamped to them at construction. Ask for more and you do not get more:
assurance-budget runs.jsonl --tool-calls 5000 --json | grep tool_calls
# "tool_calls": 40
It clamps rather than erroring, on purpose. A caller asking for 5000 is expressing a preference the runtime declines — that is not a reason to abort somebody's task. Lower values pass straight through, because a caller may always be more conservative: that is how a cheap plan or an untrusted worker gets a shorter leash.
Raising a ceiling is a deliberate edit to a source file, which is the point.
The log
JSONL, one event per line. Field names are matched loosely — run/run_id/session,
action/tool/name, and so on — so most existing logs work without being rewritten.
{"run": "r-002", "action": "fetch(url=api/invoices)", "error": "timeout", "kind": "tool", "ts": 41.0}
kind is one of tool, frontier, retry, iteration and defaults to tool. Anything else is
refused rather than counted as something it isn't.
As a library — the half that prevents rather than reports
The audit tells you it already happened. This stops it happening:
from assurance_core.run_budget import Budget, ProgressWatch, Progress, Spend
spend = Spend(budget=Budget.allowing(tool_calls=20))
watch = ProgressWatch()
for step in range(100):
stopped = spend.charge_tool_call()
if stopped:
print(stopped.message)
break
stalled = watch.observe(Progress(action="fetch(url=api/invoices)", error="timeout"))
if stalled:
print(stalled.message)
break
assert spend.tool_calls <= 20
Two different stops, and the difference matters. Exhausted means the budget ran out.
Stalled means budget remains and spending it is the mistake — three rounds repeating the same
action, failing the same way, with nothing new read and no part of the goal closer.
In a pipeline
assurance-budget runs.jsonl --fail-on-exhausted
| exit | means |
|---|---|
0 |
audited, and nothing hit a limit or stalled |
1 |
audited, and --fail-on-exhausted found a run that did |
2 |
refused — the log could not be read, so there is no audit |
Honest limits
- It reads what your log records. A run that burned money in a way the log does not mention is invisible here, and no amount of analysis fixes that.
- There is no dollar limit. Frontier calls are the cost proxy. Prices change per model, per provider and per week; a number that goes stale silently is worse than a count that does not pretend to be money.
- Stall detection needs three rounds and both halves — identical action, error and result, and flat progress. A repeated action while evidence accumulates is a loop doing work, and stopping that would be the bug.
As an agent skill
skills/run-budget/ — drop it in and an agent reads your run logs the
right way. Its real content is that a limit the log cannot exercise has not passed, and that a
run which stalled is an agent bug while one which was exhausted may just be a job too big.
Where the rules live
assurance_core.run_budget, in assurance-core — pure
Python, no dependencies, no model involved in any of it. This package reads logs and calls it.
Licence
Apache-2.0.
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