---
name: rlaope/ulw-perf
source: https://app.decimal.ai/s/rlaope-ulw-perf@2/SKILL.md
source_sha256: d244fdc72100
---

# Ultraperf

This is a Hermes-native `ultraperf` workflow skill.

## Why This Exists

`ultraperf` exists because most performance work starts unlocalized: something is slow, leaking, or expensive and nobody knows where. It forces measurement before edits, one hypothesis at a time, executor-owned changes, and a regression budget, so an optimization loop cannot end in unverified claims.

## Do Not Use When

- Metric, baseline, budget, and benchmark command are already declared for one measurable goal; use `performance-goal`.
- The ask is to judge code quality, structure, or correctness rather than measured cost; use `code-review`.
- The ask is to score model or agent output quality on a task suite; use `agent-evaluation`.
- The request is a settings-only change, one bounded edit that is explicitly low-risk and has a direct owner and verification path, or one already-identified slow query or hotspot fix; handle it directly instead of opening a performance loop.

## Examples

Good example:

- Prompt: $ultraperf checkout feels slow and the worker memory keeps climbing - find where and fix it
- Expected behavior: Audit the baseline, name the evaluator command, rank hot-path hypotheses, hand the smallest reversible fix to the selected executor, re-measure, and state the budget delta.
- Why: The problem is real but unlocalized across more than one domain.

Bad example:

- Prompt: $ultraperf make the recommender p95 under 200ms; baseline 340ms, benchmark is 'make bench'
- Expected behavior: Route to `performance-goal`, which owns a declared metric/baseline/budget/benchmark goal.
- Why: A single declared measurable goal does not need a discovery loop.

## Completion Checklist

- Baseline, workload, environment, and evaluator command are recorded before any edit is proposed.
- Each accepted fix names the measured hot path, the reversible change, and its owner.
- Re-measured deltas cite observed evidence; unmeasured steps stay not_observed.
- The regression budget and the gate that enforces it are stated with the tolerance.

## Recovery Notes

- If no evaluator command exists, stop the loop and produce one before touching code.
- If the re-measure does not move, revert the change and re-rank hypotheses instead of stacking fixes.
- If the goal turns out to be one declared metric with a budget, hand off to `performance-goal`.

## Workflow Lane

- Current lane: **Intent -> plan** (`oh-my-hermes`, `meta-router`, `deep-interview`, `context`, `plan`, `ralplan`, `codebase-onboarding`, `codegraph-refresh`, `+4 more`) - clarify, plan, ship, or loop goals.
- If intent belongs to another lane, hand back to `oh-my-hermes` or name the adjacent workflow.
- Shared product, routing, compatibility, and evidence rules: `omh-routing/references/skill-common-rail.md`.

## Use When

Use when performance problems are suspected but not yet localized, or when several cost hotspots across domains need a measured inspect-and-fix loop.

    Strong routing signals: `ultraperf`, `$ultraperf`, `ulw-perf`, `performance audit`, `performance bottleneck`, `find the bottleneck`, `profile the hot path`, `memory leak investigation`, `token cost hotspot`, `storage footprint audit`, `rendering jank`, `model inference hotspot`, `slow ci pipeline`, `query performance audit`, `성능 병목`, `메모리 누수`, `느려진 원인`, `성능 전반 점검`

## Catalog Metadata

Category: `optimization`
Phase: `measured-optimization-loop`
Hermes role: `tracker`
Quality tier: `measurement-gated`
Reasoning demand: `heavy`

Quality bar:

- Record a baseline and name the evaluator command before proposing any optimization edit.
- Attack only a hot path shown by a measurement or profile; never micro-optimize unmeasured code.
- Keep every fix the smallest reversible change and route code edits to the selected executor.
- Re-measure after each change and report deltas only from observed evidence.
- Never present a restart, cache flush, or resource bump as a leak fix; prove causation by revert-verify.
- Set the regression budget as baseline x (1 + tolerance) and name the CI gate that enforces it.

Handoff policy:

Hermes owns the audit, baseline, hypothesis, budget, and status; every optimization code edit becomes a selected executor/runtime handoff and returns as observed re-measurement.

Required inputs:

- symptom or suspected slow surface
- workload or reproduction
- runnable evaluator or measurement command
- acceptable tolerance

Expected outputs:

- baseline record
- ranked hot-path hypotheses
- smallest reversible fix handoff
- re-measured delta
- regression budget and gate

Artifact expectations:

- baseline measurement record
- final profile or benchmark evidence
- budget delta with tolerance

Safety rules:

- Do not claim a profile, benchmark, measurement, or CI budget gate ran without observed evidence.
- Do not begin optimization edits before an evaluator command and its pass/fail contract exist.
- Ask for the workload, environment, and acceptable tolerance before declaring a budget.

## Runtime Evidence

Preferred harness for this skill: `goal-execution`.

```sh
omh runtime record --skill ultraperf --harness goal-execution --status started
```

Record observed delegation results; otherwise return `not_available` or `not_observed`.
Prepared OMH routing is not execution, review, CI, merge-readiness, or merge evidence.
- Treat wrapper memory/context summaries as advisory local context, not proof of opaque Hermes memory reads or changes.
Preserve workflow intent and stop conditions; verify before claiming completion.

Use Hermes-native subagent/delegation features when available: native subagents -> Hermes delegation when available, otherwise sequential lanes.

Shared product, compatibility, topology, memory, harness, and execution rules: `omh-routing/references/skill-common-rail.md`. Load it when applicable; otherwise name an unavailable capability.