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/simulate-before-launchnpx skills add understudylabs/understudy-agent-tools --skill simulate-before-launchgit clone --depth 1 https://github.com/understudylabs/understudy-agent-toolsWhat 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 | $0.00078 | $0.02083 |
| Opus 5 | $0.00039 | $0.01042 |
| Sonnet 5 | $0.00016 | $0.00417 |
| Haiku 4.5 | $0.00008 | $0.00208 |
Grade A, and why
simulate-before-launch 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 2d 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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Simulate Before Launch
Live monitoring watches latency and HTTP errors; a contract regression returns
HTTP 200 with the wrong shape. A routed model that answers a
response_format: json_schema request with a fenced ```json code block instead
of an enforced structured object shows zero errors and great latency while
one in five downstream parses fails. This worker is the offline gate between "a
change exists" and "traffic moves": replay the workload's frozen tasks through
the same serving path with the change applied, score quality and output
contracts over repeated rollouts, and emit a launch verdict — before any
traffic, capture, or customer sees the change.
Checked against existing skills: design-simulated-environment owns building
the seeded environment and validator — this skill runs an existing eval
surface as a ship/no-ship gate. capture-evidence owns the frozen
harness/metric/splits/baseline this gate refuses to run without.
compare-model-sweep owns choosing among many candidates — this skill judges
one proposed change against the incumbent. ramp-and-verify owns live traffic
and consumes this skill's verdict as its "frozen-eval verdict exists"
pre-ramp gate. check-routing-health owns post-ship live diagnostics.
optimize-workload / optimize-agentic-workload own making the workload
better — this gate only judges a change, it never optimizes.
Safety Gates
- Read-only toward production. No route writes, no traffic changes, no
capture-setting changes. The only side effects are local artifacts under
.understudy/simulate-before-launch/and the inference calls of the replay itself. - Name the spend before running. The gate replays N rollouts × M tasks × 2 arms through a serving path that may bill. State the rollout count and a cost estimate, and get approval when the run is not local-only.
- No verdict on stale artifacts. The verdict binds to the
harness_sha256/metric_sha256/splits_sha256triple fromcapture-evidence. If any hash no longer matches, refuse and route to re-baseline — a verdict against a moved target is noise wearing a badge. - Synthetic examples only in public. Verdicts and replay rows built from real captures stay local; anything committed uses synthetic fixtures.
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.
- 2d ago First seen · 151 lines · 0 tokens per session scan A 35716e299806
simulate-before-launch is a skill published in the GitHub repository understudylabs/understudy-agent-tools (16 stars, last pushed 3d ago), licensed MIT. It adds 78 tokens to every session and 2,083 once invoked, about $0.0004 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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