Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/understudylabs/understudy-agent-tools/lower-anthropic-billnpx skills add understudylabs/understudy-agent-tools --skill lower-anthropic-billgit clone --depth 1 https://github.com/understudylabs/understudy-agent-toolsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/understudylabs/understudy-agent-tools/lower-anthropic-bill)<a href="https://agentmods.dev/skills/understudylabs/understudy-agent-tools/lower-anthropic-bill"><img src="https://agentmods.dev/badge/skills/understudylabs/understudy-agent-tools/lower-anthropic-bill.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00000 | $0.01547 |
| Opus 5 | $0.00000 | $0.00773 |
| Sonnet 5 | $0.00000 | $0.00309 |
| Haiku 4.5 | $0.00000 | $0.00155 |
Grade A, and why
lower-anthropic-bill scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Lower Anthropic Bill
Use this worker for the installer happy path and for any developer who arrives with a Claude bill, Anthropic usage export, or codebase that calls the Messages API. The first deliverable is a local audit: call-site inventory, current price assumptions, tokenizer re-baseline risk, cache-hit opportunities, batchability, and route candidates. Do not edit code during the audit.
Safety Gates
- Local-first. Static repo inspection and local usage-export parsing are the default. Do not upload source, prompts, traces, completions, datasets, repo paths, secrets, or private notes without explicit approval for that exact action.
- No provider spend without a named surface, model, data class, row count, and dollar envelope. Token-counting, cache probes, OpenAI migration tests, and GEPA reflection all need approval if they call a provider. Recommend the decision-sized test and explain its expected savings, time, and confidence; one approval may cover the named bounded test matrix.
- No silent source edits. Adding
cache_control, changing model strings, rewriting prompts, or adding an OpenAI route is a follow-up change after the audit report is reviewed. - Treat dollar values as estimates until backed by usage exports or measured
runs. Savings claims require the normal
claim.jsonevidence path from../optimize-workload/SKILL.md.
Intake
Default to the current repo. Ask for at most one missing input:
- a path to the app or service that calls Anthropic;
- an Anthropic usage export, gateway capture directory, or sampled response
usageblock; - monthly call volume per route if no export exists.
If the installer prompt set the lower-Anthropic-bill goal, assume the objective is cost reduction with no quality regression. Ask only for the target repo or usage export if you cannot infer it.
If the developer asks to inspect billing email, invoices, receipts, or an
authenticated billing website, route that optional evidence source through
../inspect-billing-sources/SKILL.md
before estimating hotspots from bill data.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 127 lines · 0 tokens per session scan A afd50db24654
lower-anthropic-bill is a skill published in the GitHub repository understudylabs/understudy-agent-tools (16 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,547 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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