Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add understudylabs/understudy-agent-tools/plugin install understudyWrote 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/ramp-and-verify)<a href="https://agentmods.dev/skills/understudylabs/understudy-agent-tools/ramp-and-verify"><img src="https://agentmods.dev/badge/skills/understudylabs/understudy-agent-tools/ramp-and-verify.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 | $0.00096 | $0.02096 |
| Opus 5 | $0.00048 | $0.01048 |
| Sonnet 5 | $0.00019 | $0.00419 |
| Haiku 4.5 | $0.00010 | $0.00210 |
Grade A, and why
ramp-and-verify 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 6d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ramp and Verify
Every successful journey through this library ends the same way: a candidate
won on a frozen eval and a route decision says ship it. This worker owns the
last mile — taking that candidate from 0% to 100% of live traffic on the
gateway dial without trusting a single lab number, and producing the measured
before/after that makes any savings statement honest. It starts where
../compare-model-sweep/SKILL.md and
../use-understudy-gateway/SKILL.md
stop.
Resolve CLI
Prefer the installed understudy binary. If it is unavailable inside a repo
checkout, run through the package script:
npm run build
node dist/bin.js status --json
Safety Gates
- Every traffic change is an explicit, approved action. Name the workload,
the model id, the old and new percentage, and get approval in the current
thread before each
routes set. Never ramp two tiers in one step. - Disclose capture-on-by-default. Setting a model route enables request capture for that workload unless capture is explicitly disabled — tell the developer this before the first route write and confirm the capture setting they want. The hosted capture behavior is documented at docs.understudylabs.com/concepts/capture.
- Snapshot before every change. The CLI writes a route snapshot before
route writes; verify it exists so
routes rollbackhas something to restore. - No savings claim without a claim packet. Measured routed-vs-passthrough
deltas go into the evidence contract from
../optimize-workload/SKILL.md(claim.json); a tier that "looks cheaper" is not a claim. - Captures contain raw request/response bodies. Read them through the CLI's redacted, metadata-first views; full payload export is opt-in, file-only, and approval-gated.
Pre-ramp gates (all must pass)
- Frozen-eval verdict exists — a sweep/optimization result on frozen
splits with the incumbent baseline recorded, or a
passlaunch verdict from../simulate-before-launch/SKILL.mdfor the specific change being ramped (its contract axes — schema validity, tool-call validity — are the same ones step 3 verifies from captures). - Repeat-replay stability. Re-run the candidate on the frozen rows in
incremental batches. Three repeats may serve as a plumbing smoke, but size N
for the agreed instability tolerance and increase it when results sit near
the threshold or vary across batches. Bucket each row: all-repeats-match /
some / none (the procedure lives in
../compare-trajectories/SKILL.md). Rows that never repeat are stochastic pockets — assign each a disposition: fallback (route to incumbent), shadow (observe, don't serve), or requires-fresh-traffic. Stop if >~5% of rows are unstable. - Fallback exists. The non-routed remainder passes through to the
incumbent by construction; confirm the workload's passthrough path works
(
gateway probe) before sending anything to the candidate.
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.
- 6d ago First seen · 163 lines · 96 tokens per session scan A 1871510414a8
ramp-and-verify is a skill published in the GitHub repository understudylabs/understudy-agent-tools (16 stars, last pushed 4d ago), licensed MIT. It adds 96 tokens to every session and 2,096 once invoked, about $0.0005 per session on Opus 5. 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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