Repeatability
Medium
The general patterns — tree-shaking, lazy requires, streaming large files, timeout wrappers — are repeatable. But the specific tradeoffs depend on the existing codebase structure, which varies each time and requires reading actual code before acting.
Ambiguity Tolerance
Medium
Some success criteria are crisp (package size reduction, timeout handling present/absent), but 'before/after cold-start metrics' is only meaningful if the agent can actually deploy and measure — otherwise it's fabricated or estimated, which is a real failure mode.
Data & Tool Availability
Low
The agent needs the existing Lambda source code, package.json, AWS credentials, deployment tooling, and the ability to invoke the function under load to produce real metrics. Most agent environments won't have all of this wired up, making the benchmark requirement nearly impossible to fulfill honestly.
Error Cost
High
A production Lambda serving 500 requests/day is live infrastructure. A bad deployment — broken image processing logic, misconfigured timeout, or corrupted package — causes real user-facing failures and potential data loss. Reversibility depends on whether rollback is configured.
Human Judgment Required
Medium
Choosing between Sharp vs. Jimp, deciding acceptable quality/compression tradeoffs for images, and setting timeout thresholds that balance UX against cost involve product judgment. These aren't purely technical decisions and benefit from a human who knows the business context.