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/optimize-workloadnpx skills add understudylabs/understudy-agent-tools --skill optimize-workloadgit 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 | $0.00079 | $0.03183 |
| Opus 5 | $0.00039 | $0.01591 |
| Sonnet 5 | $0.00016 | $0.00637 |
| Haiku 4.5 | $0.00008 | $0.00318 |
Grade A, and why
optimize-workload 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 — 261 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Optimize Workload
Use this worker only after the workload has fresh local artifacts from
capture-evidence. Validation and optimization must be evidence-led and
split-safe.
Safety Gates
Default to the intervention with the highest expected progress toward the
objective under hard constraints, not the cheapest rung. State the expected
quality gain, time, spend envelope, and evidence before execution; follow
../understudy/reference.md → Outcome-first spend
posture. A developer action that launches a named bounded optimization plan
authorizes its declared model calls, uploads, hosted work, evaluation, receipts,
and cleanup. Do not pause for phase-by-phase confirmation. Ask again only if the
plan expands its displayed data, destination, spend, retention, download, or
production-impact envelope. Follow the repo public boundary in
../../docs/privacy-and-data-boundaries.md
for prompts, completions, traces, labels, datasets, repo paths, secrets, and
private notes.
Refusal Gate
Refuse to optimize unless all required artifacts are present and fresh:
.understudy/capture-evidence/harness.json
.understudy/capture-evidence/metric.json
.understudy/capture-evidence/splits.json
.understudy/capture-evidence/baseline.json
Fresh means generated for the same workload, metric, split contract, and
incumbent baseline in the current task context. Freshness is hash-bound:
baseline.json must include harness_sha256, metric_sha256, and
splits_sha256, and those values must match the current harness.json,
metric.json, and splits.json. If freshness is ambiguous or hashes do not
match, route back to
../capture-evidence/SKILL.md instead
of optimizing.
Split Rules
- GEPA is train/dev-only.
- Prompt, route, parser, renderer, and candidate selection changes may use train and dev only.
- Never mutate holdout rows, labels, validators, thresholds, or sampling after optimization begins.
- Holdout is only for final validation after the candidate is frozen.
- If holdout is touched accidentally, mark the result contaminated and create a new split contract before claiming progress.
What ships with it
7 files 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 · 261 lines · 79 tokens per session scan A 1678f8d62cf6
optimize-workload is a skill published in the GitHub repository understudylabs/understudy-agent-tools (16 stars, last pushed 2d ago), licensed MIT. It adds 79 tokens to every session and 3,183 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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