Claude Agent Cost Audit · $1,500 flat
Your Claude agents now have
a separate bill.
On June 15, 2026, Anthropic moved programmatic Claude usage — the Agent SDK, claude -p, Claude Code GitHub Actions, third-party agents — off your subscription's limits and onto a separate monthly credit, metered at full API rates, with no rollover. If you run Claude agents in production, the question stops being “does it work” and becomes “what does each run cost, and what halts when the credit runs out.” This audit answers both, with numbers from your actual code.
Flat fee, no surprises · Baselined from your real metered usage · NDA-friendly
What changed June 15
The facts, so we're working from the same page:
- A separate credit pool — agent and automation traffic stops drawing from your Pro/Max subscription and starts drawing from a dedicated monthly credit: about $20 on Pro, $100 on Max 5x, $200 on Max 20x.
- Metered at API rates — the credit is dollar-denominated and burns at standard API pricing, so model choice and prompt size now translate directly into money.
- No rollover — unused credit doesn't carry to the next month.
- Hard stop or overflow — when the credit is gone, automated requests are rejected, unless you've enabled overflow billing, in which case they bill at API rates without a ceiling you've designed for.
- Interactive use is unaffected — typing into Claude or Claude Code yourself stays on the subscription. It's the unattended, programmatic traffic that moves.
Who this hits
Agents on cron or CI
Scheduled jobs, GitHub Actions, pipelines calling claude -p — the quiet automations nobody has priced per-run.
Products on the Agent SDK
If your product's features run on Agent SDK calls, your unit economics change on the 15th — whether you've modeled it or not.
Agencies running client automations
Each client workload now has its own meter. Margins that worked under a flat subscription may not survive API rates.
Anyone who got the claim email
Anthropic is emailing subscribers to claim their credit. If you're not sure what it means for your stack, that's the audit's first question.
What the audit covers
A focused pass over the code that runs your agents, with the June 15 economics applied to it:
- Per-run cost model — what each agent, job, and pipeline actually costs at metered rates, from your real prompts and call patterns — not a guess from a pricing page.
- Model-tier fit — which steps genuinely need a frontier model and which run identically on one that costs a tenth as much.
- Prompt & caching waste — repeated context, missing prompt caching, oversized system prompts, retries that double-bill.
- Exhaustion behavior — what halts mid-month when the credit empties, what that does to your product or clients, and the budget gates and fallbacks that should exist before it happens.
- Overflow exposure — if you enable overflow billing, what an unbounded month looks like, and the alerting that keeps it bounded.
- Architecture options — where batching, queueing, or restructuring an agent loop cuts spend without cutting capability.
Why it's different
We run agent fleets ourselves
This studio runs on its own AI workforce — agents on schedules, budget gates, cost tracking, the lot. The audit applies operating experience, not a framework skim.
Every finding verified
Each finding is checked against your real code — file, line, and symbol confirmed to exist — by a deterministic gate before it's allowed into the report. No hallucinated problems.
A senior signs off
Twenty years of engineering reviews, prioritizes, and stands behind every finding. You're not getting raw model output — you're getting a senior engineer's audit, accelerated.
What you get
- A cost model of your actual usage — per agent and per run, at the post–June 15 metered rates, with the monthly total against your credit tier.
- Impact-ranked findings — each with its location in the code, the dollars or risk attached, and a concrete fix or next step.
- An exhaustion plan — what to gate, what to alert on, and what should degrade gracefully instead of halting when the credit empties.
- A 60-minute readout call — we walk the report together and I answer whatever comes up.
- In days, not weeks — and it's a diagnosis, not a rewrite pitch. If your setup already survives the change, you'll hear that.
A finding looks like this
Daily digest re-sends the full document corpus on every run
What: The scheduled digest agent rebuilds its prompt from scratch each morning — ~180k input tokens of unchanged reference documents — with no prompt caching and a frontier-tier model doing summarization a mid-tier model handles identically.
Impact: At metered API rates this one cron job consumes roughly half of a Max 5x monthly credit by itself. Under the subscription it was invisible; after June 15 it starves every other automation by mid-month.
Fix: Cache the static corpus with prompt caching, send only the day's delta, and drop the summarization step one model tier. Same output, ~90% lower per-run cost; add a per-job budget gate so a regression like this pages someone instead of draining the pool.
Illustrative example — shown to give you the format and depth, not a real client's finding.
Want to see the audit format end-to-end? Two real reports: one that found & fixed a live command-injection → and one that found & fixed a ReDoS →. Every finding mechanically verified against the source.
Price & terms
One fixed fee agreed up front — no hourly drift, no scope games. With the change now live, an audit produces an exact picture from your actual metered usage — no more estimating, the numbers are on your statement. Your code stays yours, an NDA is welcome before the first call, and nothing you share is ever used to train any AI model. If the audit points to work worth doing, it folds cleanly into a Sprint — but there's no obligation, and no upsell baked into the findings.
Common questions
What changed on June 15, 2026?
Anthropic moved programmatic Claude usage — the Claude Agent SDK, claude -p, Claude Code GitHub Actions, and third-party agents — off your subscription's usage limits onto a separate monthly credit (about $20 on Pro, $100 on Max 5x, $200 on Max 20x), metered at standard API rates with no rollover. When the credit is exhausted, automated requests stop — unless overflow billing is enabled, in which case they bill at API rates.
What do you need from me to start?
Read access to the code that runs your agents — a GitHub or GitLab invite, or a zip — and recent usage numbers if you have them. That's enough to begin.
Can you still audit agents now that the change is live?
Yes — and now the data is real. With the billing change live, an audit produces an exact cost picture from your actual metered usage: per-run cost at the new rates, model-tier fit, caching and prompt waste. No more estimating — the numbers are on your statement.
What if my setup is already fine?
Then you get a short report saying so, with the numbers to prove it — documented confidence instead of a background worry. The audit is a diagnosis, not a rewrite pitch.
Is my code kept confidential?
Yes. I'm happy to sign your NDA before the first call, your code is never used to train any AI model, and access is removed once the audit is delivered.
Book the cost audit
Know your number before the meter starts.
Send the repo that runs your agents and a sentence on what they do. You'll have the per-run economics, the risks, and the fixes — in days.