## Thinking Path > - Paperclip contributors wait for CI before delivering changes. > - Build still finishes last after #16460. > - CI already downloads the public npm graph while the build runs. > - Bundled-package preparation ignores that cache and downloads the same archives again. > - Reuse the existing cache and overlap independent runtime checks while preserving fresh installs, integrity, offline lifecycle and admission verification. > - Measure staging and the full workflow separately. ## Linked Issues or Issue Description Refs #16460 and #16434. This is a focused follow-up to merged #16460, now based directly on master. **Current behavior:** The Build workflow warms `PAPERCLIP_PUBLIC_INSTALL_NPM_CACHE`, but `startBundledInstalls` inherits the host's default npm cache. Server staging took 31.17 seconds in the latest passing run, before packing and the clean consumer install. **Proposed behavior:** Pass the verifier environment, including the explicitly configured warm cache, to the three existing staging children. Without an explicit shared cache, keep the usual producer npm configuration. **Alternatives considered:** Copying an installed dependency tree would bypass normal fresh installation. Adding jobs would add setup cost. This change reuses only npm's integrity-checked download cache. It does not remove coverage or change product behavior and does not overlap a roadmap feature. Open PR title search found no equivalent cache wiring change. ## What Changed - Initialize the existing consumer cache before package staging and expose it to producer npm only when explicitly configured. - Pass that environment to the existing bundled-install children. - Extend the child orchestration check to verify cache propagation and document the cache boundary. - Start Pi setup after the offline lifecycle, in its own download sandbox, while Codex and Grok probes run in separate offline sandboxes. Join successful Pi setup before lock verification and Pi admission. Name and clean up only the verifier-owned setup container. ## Verification - 33 focused public-install, closure and child-orchestration tests pass on Node 24.21.0. - A real server dependency staging experiment used `prepare-bundled-package.mjs`, its actual manifests, provider overrides and release patches. Built application payloads were omitted from this dependency-only measurement. - Cold cache: **16.139s**. After the actual CI warm-up script: **6.980s**. A fully warm producer cache took **6.127s**. These are local sequential measurements, not a CI wall-clock claim; filesystem warmth and registry timing vary. - All **28,329 files/links**, including both lockfiles, were byte-identical between the cold output and the actual-workflow-warm output. - The warm-up itself took 49.631s; CI already runs it during Rust restore/build. This change adds no warm-up operation. - First follow-up run [passed all 48 jobs](https://github.com/paperclipai/paperclip/actions/runs/38791277425), and Greptile gave the cache-only head 5/5. Server staging fell **31.172s → 17.565s** and total staging **70.169s → 54.869s**. But complete CI was **8m20s**, slower than the parent's 8m04s; longer Codex/Pi probe times outweighed that saving. This is not a full-run speed improvement claim. - The next revision overlaps the independent probes instead of serializing Pi setup behind them. All 46 focused sandbox, staging, closure and process-supervision tests pass, including failed background children, parent exit and cancellation. Pre-retarget head `590873a44` passes all 48 jobs and Greptile 5/5 with no review findings. After #16460 merged, head `fe4f8d38e` incorporates master and retargets this PR directly to master. Its diff remains only four optimization/documentation/test files; 46 focused checks pass again. Fresh full CI and review are pending. The unchanged parent conflict-resolution run passed all 48 jobs in 8m04s: https://github.com/paperclipai/paperclip/actions/runs/38789785045. Final paired runs against the same updated master, both on `m7i-flex.xlarge`: | Measurement | Parent #16460 | This PR | | --- | ---: | ---: | | Bundled server staging | 22.220s | 14.202s | | All package staging | 61.277s | 48.304s | | Clean consumer install | 67.617s | 73.490s | | Pi setup remaining wait | 25.428s (serial setup) | 20.719s | | Build job | 385s | 368s | | Build start after workflow creation | 23s | 136s | | Entire workflow, including admission and aggregates | 452s (7m32s) | 552s (9m12s) | [Parent run](https://github.com/paperclipai/paperclip/actions/runs/38792983313), [final run](https://github.com/paperclipai/paperclip/actions/runs/38792986392). Build execution improved by **17s (4.4%)** in this pair. The total workflow did **not** improve: it waited 113 seconds longer to start Build, and other lanes/aggregates also contribute. The overlapping setup ran for 25.667s while Codex/Grok took 4.946s, leaving 20.719s to wait. Actual installed Codex, Grok and Pi checks all passed with zero provider calls. These are individual samples with filesystem/network/CPU variance, not a claimed steady-state average. The earlier slower cache-only run is retained above. No tests were removed and no jobs were added. ## Risks Shared-cache contention can reduce the benefit if warm-up is still running. npm handles concurrent content-addressed cache writers and checks integrity; misses still download normally. Two runtime containers can now overlap and contend for host resources; the full CI run measures that tradeoff. They retain separate network policies and per-container bounds. Pi writes only its provider assets and a private receipt; the other probes inspect Codex/Grok. No installed tree, lock, test result or build output is reused. The consumer still starts empty and performs the full lifecycle and runtime checks. Normal unconfigured producer cache behavior is preserved. ## Model Used OpenAI GPT-6 through Codex, with repository inspection, execution and GitHub tools. The serving model suffix and context capacity are not exposed to this session. ## Checklist - [x] I have included a thinking path that traces from project context to this change - [x] I have specified the model used (with version and capability details) - [x] I have checked ROADMAP.md and confirmed this PR does not duplicate planned core work - [x] I have searched GitHub for duplicate or related PRs and linked them above - [x] I have either linked existing issues or described the issue in this PR - [x] I have not referenced internal or instance-local Paperclip issues or links - [x] My branch name describes the change and contains no private ticket identifier - [x] I have run tests locally and they pass - [x] I have added or updated tests where applicable - [x] I have updated relevant documentation - [x] I have considered and documented the risks - [ ] All Paperclip CI gates are green (prior head passed; rerunning after master merge) - [ ] Greptile is 5/5 with no open P2s, recommendations or follow-ups (prior head 5/5; current head pending) - [x] I will address all Greptile and reviewer comments before requesting merge --------- Co-authored-by: Paperclip <noreply@paperclip.ing>
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Profile the complete PR suite
Add the profile-ci label to a PR authored by a CI CODEOWNER. Adding the label starts a fresh PR workflow
run. Further pushes while the label remains also run with profiling enabled.
The run is named CI profile · PR #number. It runs all lanes of the main PR
suite, including middle-of-stack and release-notes-only PRs that normally skip
most lanes.
After the run finishes, open its Summary and follow Open the Honeycomb waterfall. The separate CI profile workflow exports the trace after all jobs finish. Its summary has the exact time range, job/span counts, and coverage warnings. Keep the label on the PR and its head unchanged until export finishes. Remove the label to stop profiling subsequent pushes. To profile the same revision again, remove and re-add the label or rerun all jobs.
The PR author, original workflow actor, and rerun actor must all be individual
users in the trusted master branch's .github/** CODEOWNERS rule. GitHub user
IDs are resolved from that rule; PR edits to CODEOWNERS cannot grant access.
A label on an outside contributor's PR does not enable profiling, even when a
maintainer applies it. The PR still runs normal CI and needs no Honeycomb
access. Failed identity lookups disable profiling.
Ordinary PRs do not write timing artifacts or export traces. The exporter job is skipped for ordinary run names. Adding another label does not run the CI matrix.
Profiling preserves the existing trusted AWS runner routing. Eligible PR jobs
use paperclip-public-pr-x64; the routing gate uses paperclip-ci-routing-x64.
The existing fail-closed GitHub-hosted fallback still applies if AWS routing
cannot be authorized. Only the separate post-run Honeycomb exporter uses
ubuntu-latest directly; it is outside the measured PR suite.
Read the waterfall
The workflow root measures elapsed time from run creation to the last job's
completion. For reruns, it starts at that attempt's run_started_at instead of
the original creation time. Every job is a child on the same wall clock, with
its steps and available test details beneath it. All spans use a sample rate of
one. There is no sampling within the selected attempt. For a compact Gantt view,
open a job row's menu and choose Collapse spans at this depth. Expand an
individual job to inspect its steps and test files.
The expandable hierarchy is workflow → job → step → test filename → tests.
Vitest, Playwright, and Node file rows use repository-relative filenames, also
available in test.file. Separate files retain their own children even when
individual test names repeat across files.
Honeycomb shows only the 32,000 spans closest to the root in a very large trace.
All file rows are near the root, but the chart can omit some individual test
rows. Use View events to query all recorded test spans. Test names are
limited to 256 characters in the trace; file paths remain intact.
- Compare the jobs that finish last (
ci.finishes_last) with other overlapping work. A long job that finishes early is not necessarily delaying CI. - Expand setup, dependency installation, cache restore, Rust compilation, builds, and tests to find repeated or slow work.
ci.execution_msmeasures a job's execution.ci.start_offset_msshows when it started relative to the whole run. Do not add parallel job durations to calculate elapsed time.- Waiting spans cover job creation to runner start. Dependency waits can occur before GitHub creates a job, so they appear as gaps from the workflow start. GitHub does not expose a separate ready timestamp; do not interpret every gap as runner queue time or claim this is a computed dependency critical path.
GitHub job/step timestamps have second precision. Vitest and Playwright record
test timestamps at the runner. Node's test reporter records completion receipt
time and duration (test.clock=reporter-receipt); buffered IPC delivery can shift
those small test spans. Vitest file spans include its test/hook execution and
carry collection/setup durations as fields. Playwright file spans cover the
first through last test attempt in that file. Rust and standalone script checks
retain their full job/step timings; stable libtest does not expose per-test wall
timestamps. The trace is CI timing data, not application tracing.
Scope includes all main PR lanes: policy, typecheck/release registry, general and serialized tests, Runner checks, Docker context checks, build, canary dry run, browser E2E, and aggregate checks. Separate Storybook, image, deployment, release, and live-provider eval workflows are outside this trace.
Failure, coverage, and reruns
The exporter uses GitHub's attempt-specific job API and paginates jobs and
artifacts. It includes failed and cancelled jobs and uploads available test
timings with always(). A force-cancelled or failed setup job may leave no
artifact. Coverage warnings and ci.profile_complete=false make missing
artifacts, interrupted reporters, rejected data, and absent test details visible.
Test launchers write an expected-invocation record before starting each Vitest,
Playwright, or Node process. Each reporter must write matching start/end records,
so a missing reporter cannot hide behind another successful invocation in the
same job. Direct package scripts can start a reporter without the launcher;
their start/end pair proves collection. Compare ci.expected_invocations with
ci.reported_invocations.
Failed or cancelled workflows are conservatively incomplete because a failed
command can prevent later tests or steps from running.
Each attempt gets a different trace ID. Rerunning failed jobs alone produces an
attempt trace for those jobs; it does not replay completed jobs. Reruns are marked
ci.partial_rerun=true conservatively. Use a fresh label-triggered run for an
unambiguous full-suite baseline. GitHub may carry earlier successful jobs into
the new attempt's job inventory. Jobs completed before the new attempt started
are excluded and counted in ci.carried_job_count.
The exporter sends bounded batches with pauses and retries only events that Honeycomb rejects temporarily. If export still fails, inspect CI profile before rerunning it. A partial HTTP export may already have sent some spans; reruns use the same IDs but the Events API does not promise deduplication. Timing artifacts remain available for 14 days. Invalid/oversized artifacts stop export instead of silently truncating the suite. No logs, environment dumps, error messages, stack traces, or credentials are included in the exported field allowlist.
Operator setup and activation
Use the existing Honeycomb paperclip team, test environment, and a separate
service dataset named paperclip-ci. Create GitHub environment ci-profiling with Selected branches and tags:
allow only the branch master, with no PR-ref or tag patterns. Store environment
secret HONEYCOMB_CI_API_KEY with a dedicated ingest-only key for the Honeycomb
test environment. Do not create a repository- or organization-level secret of
that name: the environment restriction prevents in-repository PR workflows from
requesting the key. Tests still execute the PR branch; only the separate exporter
runs from master. It needs event
ingest permission; dataset creation permission is needed only if the dataset
has not been created yet. Do not store the environment configuration key in CI.
Create the repository label profile-ci if it does not exist.
ci-profile.yml runs from the trusted default-branch revision. It checks out only
the exporter, installs no dependencies, and parses PR artifacts as bounded JSON
without extracting or executing their contents. The PR jobs never receive the
Honeycomb key. The exporter independently verifies CI CODEOWNER identities,
the current label, repository, and exact tested PR revision before reading
artifacts or sending data. Its credential is sent only in an HTTPS header to
api.honeycomb.io; redirects are rejected. Exported fields are allowlisted.
CODEOWNERS also covers scripts/ci-profile/**, so changes to the privileged
exporter require infrastructure-owner review.
The new trusted workflow and routing definitions must merge to master before
the label-triggered journey is active. A PR uses pr-trusted.yml@master and
ci-routing.yml@master; do not change those trust references just to test this
feature before merge.
Local qualification
node --test .github/scripts/tests/ci-profile.test.mjs .github/scripts/tests/ci-routing.test.mjs
node --test scripts/ci-profile/reporters.test.mjs
actionlint .github/workflows/{pr,pr-trusted,ci-routing,ci-profile}.yml
node scripts/ci-profile/export.mjs --run-id=RUN_ID --attempt=1 --historical --dry-run --output=/tmp/ci-trace.json
--historical is local-only and permits a deliberate export of an existing
unlabeled run. It has complete GitHub job/step timing but cannot reconstruct
test details that were never recorded. Omit --dry-run and supply
HONEYCOMB_CI_API_KEY to send the selected baseline to Honeycomb. It is labeled
as historical/incomplete test coverage; it is not proof of the label-triggered
workflow.
References: Honeycomb trace fields, Events API, large trace display limit, GitHub workflow_run.
Qualify reductions in CI work
For changes to the stable test launcher, dependency setup, or the large Git and
readiness fixtures, profile-ci also runs CI work benchmark. It uses one
GitHub-hosted runner without secrets or AWS access. It compares the unchanged
PR base and candidate sequentially. It records complete command times, test
inventories, revisions, and failure logs in the ci-work-benchmark artifact.
The complete general-server shard must retain the same cases. The fixture comparison retains
the database contract and splits large Git scanning from bounded staging.
These command timings exclude queue time and setup; use the full Honeycomb
waterfall to assess the complete CI critical path.
The benchmark also exercises cold dependency setup and a real materialized cache restore after removing the installed directories. Its two qualification entries are scoped to the PR merge ref and a separate checkout path. They cannot populate master's caches. Normal PR lanes restore only; the exact canonical master push in release verification is the normal cache writer.
Materialized dependency keys include every tracked package manifest, lockfile, workspace configuration, patches, repository scripts, Node version/ABI, platform, architecture, libc, pnpm version, store location, and physical checkout path. There are no prefix restores. An input change takes the normal install path. A stale lockfile uses the existing resolution fallback but cannot publish an entry. An additional workspace install/prepare hook disables materialized reuse until its inputs are modeled. Shared/SDK build outputs have a separate key that also includes both packages' source/configuration and the build verifier. The existing verifier checks source and output fingerprints and rebuilds incomplete or changed output. Tests and their results are never cached or omitted by this mechanism.
Serialized shards share one Vitest controller with forks, isolate, one
worker, and file parallelism disabled. Each file gets a separate process and
test home/configuration. The isolation regression runs files in both orders and
checks process IDs, environment, globals, fake timers, and filesystem state.
The readiness regression uses a real one-second PostgreSQL idle timeout and verifies that the backend connection changes while the parent write can commit. Its configured readiness window stays long. The Git regression keeps all four filename lanes above 32 MiB, while the staging case transfers and deletes 4,000 files whose filename list exceeds 2 MiB. It still checks every staged file, unusual names, snapshot ownership, cleanup, and bounded command lengths.
The Linux public-install check serves metadata read from the actual packed archives through a temporary loopback registry inside its download container. This avoids npm's file-spec manifest extraction of every archive before the real install. npm still verifies each archive's SHA-512 and installs the same packed bytes into an empty consumer. Other dependency metadata redirects to the public npm registry; public tarball URLs remain unchanged. The temporary registry closes before the existing offline lifecycle rebuild and runtime probes. No lifecycle, network-isolation, lock-preservation or provider checks are skipped. Native ARM and Mac qualification keep their existing file installs.
The Linux verifier also shares PAPERCLIP_PUBLIC_INSTALL_NPM_CACHE with the
producer installs that prepare bundled dependencies. These run after the existing
cache warm-up and reuse its downloaded archives instead of populating a second
host cache. Each producer still installs into a separate empty directory, applies
the release patches, and packs fresh output. npm resolution and integrity checks
remain enabled; cache misses download normally. Without an explicit shared cache,
producer installs keep their normal npm cache configuration.
After the offline lifecycle finishes, Pi setup runs in its own download sandbox
while the independent Codex/Grok probes run offline. Pi admission still waits
for successful setup and an unchanged consumer lock. The setup container has a
unique verifier-owned name and is removed on early failure as well as completion.
pi_setup_prefetch_ms measures setup wall time; pi_setup_wait_ms measures only
the remaining wait after the other probes. These overlapping durations must not
be added when interpreting total verification time.