perfgraph git:20261020.fa9b65eA

Immutable. This exact content never changes and is served at /api/v1/blob/20323ec34af61425.

---
name: perfgraph
description: Analyze web performance URLs with the PerfGraph CLI and interpret its deterministic reports, causal chains, and prioritized remediation data. Use when the request names perfgraph, or asks to measure or diagnose loading speed, Core Web Vitals, Lighthouse performance, bottlenecks, or web performance regressions.
metadata:
  short-description: Run PerfGraph CLI and explain performance findings
---

# PerfGraph CLI

Use this skill when the task requires a fresh synthetic performance analysis or
interpretation of an existing PerfGraph run. The CLI is the execution layer;
the skill explains how to invoke it and how to read its artifacts.

## Run an analysis

Prefer the installed `perfgraph` command:

```bash
perfgraph run --url <url> --output ./perfgraph-output --pretty
```

Use `--runs 1` for a quick look, and `--runs 3` when the question is why
something is slow. The first run is often an outlier — a cold JIT, a cold
DNS, a cold connection — so a single run can be several times worse than the
page normally is, and a fix aimed at that outlier is aimed at nothing. The
per-run metrics and their spread land in `runs-summary.json` next to the run
directories, with min, max, mean, median and standard deviation. Quote the
median. Use `--device "iPhone 13"` for mobile emulation. Optional collectors can be
disabled with `--no-lighthouse`, `--no-coverage`, `--no-console`, and `--no-dom`.

If the command is not installed but this repository is available, use the
already-built local entry point `node dist/index.js run ...`. Do not install
packages as an implicit fallback. A missing Chromium binary is an environment
setup failure, not a performance finding.

Give the shell command enough time for browser startup, navigation, collection,
and Lighthouse. A full run takes about three minutes — a Lighthouse audit runs
in the same browser, so a shorter timeout kills the run before it produces
anything. If it exits non-zero, inspect stderr and do not produce a
performance verdict.

## Read results progressively

After a successful run, locate the output directory from the CLI output and
read artifacts in this order:

1. `manifest.toon` — confirm what was actually produced and its suggested order;
2. `insights.toon` — compact triage metrics, LCP element, render-blocking
   resources, critical path, warnings, and top recommendations;
3. `report.toon` — authoritative `summary`, `issues`, `chains`, and
   `recommendations`;
4. `report.md` — human-readable fallback when it makes the chain easier to scan;
5. `graph.toon`, `network-summary.toon`, `lighthouse-summary.toon`, and
   `coverage-summary.toon` only for a targeted deep dive;
6. `lcp.json` for the raw LCP entry, `context.json` for the run environment,
   and `trace.json`, `network.json`, `lighthouse.json` only when the compact
   artifacts lack the evidence needed for the question.

`insights.toon` carries two metric blocks. `metrics` holds the values measured
in the PerfGraph run (the run described by `runContext`); `lighthouse` holds
the values from Lighthouse's own throttled run. They are different runs and
must not be merged. Cite each one with its source.

`.toon` files are text in Token-Oriented Object Notation. Read them as text;
do not assume they are JSON or call `JSON.parse` on them.

## Interpret the result

The final response should contain:

1. a short status with `summary.score`, Lighthouse Performance when available,
   issue counts, and the main conclusion;
2. the 1–3 highest-priority causal chains;
3. an ASCII causal degradation graph for those chains;
4. three to five actions ordered by likely impact;
5. evidence, confidence, warnings, missing data, and a repeat-measurement plan.

For each selected chain distinguish the observed metric, likely bottleneck,
and user-facing impact. Group duplicate issues that belong to one chain instead
of presenting them as independent root causes.

Use each chain path node's `basis`: `observed` means supported by a measured
metric or direct evidence; `inferred` means produced by a causal rule. Keep the
impact node separate from the measured signal, and do not present an inferred
bottleneck as a directly observed fact.

Never invent a metric, URL, selector, byte count, or expected impact. A causal
impact such as `Possible INP delay` is not a directly measured INP value. Weak
or medium confidence requires an explicit qualification. A failed collection,
network denial, missing Lighthouse result, or warning is a data-quality issue,
not evidence that the page is slow.

Before interpreting a causal chain, apply a resource sanity check. A TTFB signal
does not prove CSS discovery, render blocking, image delay, or JavaScript work.
Require matching resource/timing evidence for those nodes. A document request is
not a render-blocking stylesheet or script. If all Core Web Vitals are green and
only a borderline TTFB warning exists, describe it as a qualified observation;
do not call the page moderately degraded without independent user-impact data.

Treat `report.toon` as the authoritative causal output and compare its score and
counts with `insights.toon`. If they disagree, report the inconsistency as a
data-quality issue and avoid a confident verdict. Lab and field values from
different runs are not interchangeable; preserve their source, timestamp, and
measurement context.

Use [references/interpretation.md](references/interpretation.md) for the output
template, metric-specific vectors, and ASCII graph rules.

## Additional report semantics

When `criticalPath` is present, use `elapsedCriticalPathMs` for the longest
dependency path and `aggregateRequestDurationMs` for the sum of request work.
The aggregate value includes parallel branches and must not be described as
user wait time. Compare it with `pageLifecycleMs` when available.

Treat `mainThreadBlocking.tbtMs` as measured TBT only when its status is
available. `busyMs` is main-thread activity, not TBT, and must be described as
a proxy or limitation when measured TBT is unavailable.

Use `thirdParty.byOwnership` to distinguish `first-party`, `first-party-cdn`,
`third-party-vendor`, `external-cdn`, and `unknown`. Do not call a known
first-party CDN a third-party vendor. If `renderBlocking.sourceConflict` is
true, show both source counts and qualify any savings or LCP attribution.
Use `--owned-domain <host>` for organization-controlled asset hosts that are
not inferable from the target URL.

Every issue and chain node has `basis` and `findingStatus`. Every
recommendation should be reported with applicability, evidence, expected
impact and expected-impact status, and a verification step. Use impact surface
to distinguish initial viewport, LCP, interaction, and total-page work. For a text LCP element, prioritize render
delay, main-thread work, and blocking styles/scripts; do not recommend image
format or image priority changes without image evidence.

The LCP element comes from the browser itself: `insights.lcpElement.source` is
`performance-api`, `lighthouse` or `trace`, and `type` is `text` or `image`.
Only an image LCP carries an `lcpElementUrl` and resource load timings, and
that URL may be an inline `data:` URI — nothing to download, preload or
re-encode. When the element is unknown, report the LCP as a single render
delay instead of naming a resource. Never present the largest downloaded
image as the LCP element. The traced lab LCP and the Lighthouse LCP come from
two different runs — report both with their source instead of merging them.

When `insights.criticalPath.documentChain` is present, the browser loaded more
than one document: it navigated away from a page it had already received.
Report `wastedServerMs` as the server work nobody used and `contentAtMs` as
when the content arrived. A single run cannot separate the cost of the chain
from the cost of the load, so do not present it as a measured delay.

`insights.documentResponse` carries the headers of the document the visitor
received — cache status, cache-control, content encoding, alt-svc. Use them
before blaming the server: a document that is fetched from the origin on every
visit because of `cf-cache-status: DYNAMIC` and `max-age=0` is a caching
problem, not a slow backend. Do not fetch the page again with curl to learn
these.

`insights.lighthouse.failedAudits` lists the Lighthouse audits that did not
pass, with their values — they carry findings the causal rules cannot derive,
such as forced reflows or main-thread work.