fornida-dev/fornida-claude-plugins/benchmark-e2e

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End-to-end benchmark suite for vercel-plugin. Runs realistic projects through skill injection, launches dev servers, verifies everything works, analyzes conversation logs, and produces an improvement report for overnight self-improvement loops.

Install

npx vskill@latest install fornida-dev/fornida-claude-plugins/benchmark-e2e

SKILL.md

The same SKILL.md was published earlier as agents-store/codex-plugins/benchmark-e2e.

Benchmark E2E

Single-command pipeline that creates projects, exercises skill injection via claude --print, launches dev servers, verifies they work, analyzes conversation logs, and generates actionable improvement reports.

Quick Start

bash
# Full suite (9 projects, ~2-3 hours)
bun run scripts/benchmark-e2e.ts
# Quick mode (first 3 projects, ~30-45 min)
bun run scripts/benchmark-e2e.ts --quick

Options:

FlagDescriptionDefault
--quickRun only first 3 projectsfalse
--base <path>Override base directory~/dev/vercel-plugin-testing
--timeout <ms>Per-project timeout (forwarded to runner)900000 (15 min)

Pipeline Stages

The orchestrator chains four stages sequentially, aborting on failure:

  1. runner — Creates test dirs, installs plugin, runs claude --print with VERCEL_PLUGIN_LOG_LEVEL=trace
  2. verify — Detects package manager, launches dev server, polls for 200 with non-empty HTML
  3. analyze — Matches JSONL sessions to projects via run-manifest.json, extracts metrics
  4. report — Generates report.md and report.json with scorecards and recommendations

Contracts

run-manifest.json

Written by the runner at <base>/results/run-manifest.json. Links all downstream stages to the same run.

typescript
interface BenchmarkRunManifest {
runId: string; // UUID for this pipeline run
timestamp: string; // ISO 8601
baseDir: string; // Absolute path to base directory
projects: Array<{
slug: string; // e.g. "01-recipe-platform"
cwd: string; // Absolute path to project dir
promptHash: string; // SHA hash of the prompt text
expectedSkills: string[];
}>;
}

The analyzer and verifier read this manifest to correlate sessions precisely instead of guessing from directory listings.

events.jsonl

The orchestrator writes NDJSON events to <base>/results/events.jsonl tracking pipeline lifecycle:

jsonc
// Each line is one JSON object:
{ "stage": "pipeline", "event": "start", "timestamp": "...", "data": { "baseDir": "...", "quick": false } }
{ "stage": "runner", "event": "start", "timestamp": "...", "data": { "script": "...", "args": [...] } }
{ "stage": "runner", "event": "complete", "timestamp": "...", "data": { "exitCode": 0, "durationMs": 120000 } }
// On failure:
{ "stage": "verify", "event": "error", "timestamp": "...", "data": { "exitCode": 1, "durationMs": 5000, "slug": "04-conference-tickets" } }
{ "stage": "pipeline", "event": "abort", "timestamp": "...", "data": { "failedStage": "verify", "exitCode": 1, "slug": "04-conference-tickets" } }
report.json

Machine-readable report at <base>/results/report.json for programmatic consumption:

typescript
interface ReportJson {
runId: string | null;
timestamp: string;
verdict: "pass" | "partial" | "fail";
gaps: Array<{
slug: string;
expected: string[];
actual: string[];
missing: string[];
}>;
recommendations: string[];
suggestedPatterns: Array<{
skill: string; // Skill that was expected but not injected
glob: string; // Suggested pathPattern glob
tool: string; // Tool name that should trigger injection
}>;
}

Overnight Automation Loop

Run the pipeline repeatedly with a cooldown between iterations:

bash
while true; do
bun run scripts/benchmark-e2e.ts
sleep 3600
done

Each run produces timestamped report.json and report.md files. Compare across runs to track improvement.

Self-Improvement Cycle

The pipeline enables a closed feedback loop:

  1. Run — bun run scripts/benchmark-e2e.ts exercises the plugin against realistic projects
  2. Read gaps — report.json lists which skills were expected but never injected, with exact slugs
  3. Apply fixes — Use suggestedPatterns entries (copy-pasteable YAML) to add missing frontmatter patterns; use recommendations to fix hook logic
  4. Re-run — Execute the pipeline again to verify the gaps are closed
  5. Compare — Diff report.json across runs: verdict should trend from "fail" → "partial" → "pass"

For overnight automation, combine with the loop above. Wake up to reports showing exactly what improved and what still needs work.

Prompt Table

Prompts never name specific technologies — they describe the product and features, letting the plugin infer which skills to inject.

#SlugExpected Skills
01recipe-platformauth, vercel-storage, nextjs
02trivia-gamevercel-storage, nextjs
03code-review-botai-sdk, nextjs
04conference-ticketspayments, email, auth
05content-aggregatorcron-jobs, ai-sdk
06finance-trackercron-jobs, email
07multi-tenant-blogrouting-middleware, cms, auth
08status-pagecron-jobs, vercel-storage, observability
09dog-walking-saaspayments, auth, vercel-storage, env-vars

Cleanup

bash
rm -rf ~/dev/vercel-plugin-testing

Security

  • Security scanPassed, 90 of 100Pattern checks on the skill's files.
  • Model reviewPassed

Quality evaluation

  • Task evaluationNot runNo evaluation yet. Run one in Skill Studio.

Source

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