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generate-report

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Aktualisiert15. April 2026 um 23:15

Aggregate WebBench benchmark results into a comprehensive evaluation report. Triggers: "generate report", "create benchmark report", "summarize results", "aggregate scores", "produce evaluation report". Reads web-bench-results.jsonl, computes statistics by category/website/failure mode, and writes web-bench-report.md with pass rates, timing, token usage, and analysis. Does NOT execute or evaluate tasks — only aggregates existing results.

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lespaceman

lespaceman/athena-workflow-marketplace

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Verwandte BerufeSOC

Basierend auf der SOC-Berufsklassifikation

SoftwareentwicklerInformatik- und Mathematikberufe·SOC 15-1252

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2 Dateien

SKILL.md

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name	generate-report
description	Aggregate WebBench benchmark results into a comprehensive evaluation report. Triggers: "generate report", "create benchmark report", "summarize results", "aggregate scores", "produce evaluation report". Reads web-bench-results.jsonl, computes statistics by category/website/failure mode, and writes web-bench-report.md with pass rates, timing, token usage, and analysis. Does NOT execute or evaluate tasks — only aggregates existing results.
allowed-tools	Read Write Edit Bash Glob Grep

Generate WebBench Benchmark Report

Aggregate all results from web-bench-results.jsonl into a comprehensive markdown report.

Input

Results file: web-bench-results.jsonl — one JSON line per completed task

Result line schema:

{
  "id": 42,
  "url": "https://acehardware.com",
  "category": "READ",
  "task": "Navigate to...",
  "score": 1.0,
  "verdict": "PASS",
  "reasoning": "Successfully extracted all specs",
  "error": null,
  "duration_ms": 34200,
  "tokens_used": {"input": 12450, "output": 3200},
  "timestamp": "2026-03-19T14:30:00Z"
}

Report Generation

Use Node.js to compute all statistics:

node -e "
const fs = require('fs');
const results = fs.readFileSync('web-bench-results.jsonl','utf-8').trim().split('\n')
  .filter(l => l.trim()).map(JSON.parse);

const total = results.length;
const passed = results.filter(r => r.verdict === 'PASS').length;
const partial = results.filter(r => r.verdict === 'PARTIAL').length;
const failed = results.filter(r => r.verdict === 'FAIL').length;
const totalScore = results.reduce((s, r) => s + r.score, 0);

// Timing
const totalDurationMs = results.reduce((s, r) => s + (r.duration_ms || 0), 0);
const avgDurationMs = total ? totalDurationMs / total : 0;

// Tokens
const totalInputTokens = results.reduce((s, r) => s + ((r.tokens_used || {}).input || 0), 0);
const totalOutputTokens = results.reduce((s, r) => s + ((r.tokens_used || {}).output || 0), 0);
const totalTokens = totalInputTokens + totalOutputTokens;

// By category
const byCat = {};
for (const r of results) {
  if (!byCat[r.category]) byCat[r.category] = [];
  byCat[r.category].push(r);
}

// By website (top failures)
const bySite = {};
for (const r of results) {
  if (!bySite[r.url]) bySite[r.url] = [];
  bySite[r.url].push(r);
}

// Failure modes
const blockers = {};
for (const r of results) {
  if (r.error) blockers[r.error] = (blockers[r.error] || 0) + 1;
}

const catStats = {};
for (const [cat, rs] of Object.entries(byCat)) {
  catStats[cat] = {
    total: rs.length,
    passed: rs.filter(r => r.verdict === 'PASS').length,
    score: rs.reduce((s, r) => s + r.score, 0) / rs.length
  };
}

const siteFailures = Object.entries(bySite)
  .map(([site, rs]) => [site, rs.filter(r => r.verdict === 'FAIL').length])
  .sort((a, b) => b[1] - a[1]).slice(0, 20);

console.log(JSON.stringify({
  total, passed, partial, failed,
  totalScore, avgScore: total ? totalScore / total : 0,
  totalDurationMs, avgDurationMs,
  totalInputTokens, totalOutputTokens, totalTokens,
  byCategory: catStats,
  bySiteFailures: Object.fromEntries(siteFailures),
  blockers
}, null, 2));
"

Report Template

Write web-bench-report.md with this structure:

# WebBench Benchmark Report

**Date:** {timestamp}
**Agent:** {agent identifier}
**Dataset:** Halluminate/WebBench
**Tasks evaluated:** {total} / 2454

---

## Overall Results

| Metric | Value |
|--------|-------|
| **Pass Rate** | {passed}/{total} ({pass_pct}%) |
| **Partial Rate** | {partial}/{total} ({partial_pct}%) |
| **Fail Rate** | {failed}/{total} ({fail_pct}%) |
| **Average Score** | {avg_score:.2f} / 1.0 |
| **Total Duration** | {total_duration_formatted} |
| **Avg Duration/Task** | {avg_duration_formatted} |
| **Total Tokens** | {total_tokens:,} ({input_tokens:,} input + {output_tokens:,} output) |
| **Avg Tokens/Task** | {avg_tokens:,} |

## Results by Category

| Category | Total | Pass | Partial | Fail | Pass Rate | Avg Score |
|----------|-------|------|---------|------|-----------|-----------|
| READ | ... | ... | ... | ... | ...% | ... |
| CREATE | ... | ... | ... | ... | ...% | ... |
| UPDATE | ... | ... | ... | ... | ...% | ... |
| DELETE | ... | ... | ... | ... | ...% | ... |
| FILE_MANIPULATION | ... | ... | ... | ... | ...% | ... |

## Timing Breakdown

| Category | Avg Duration | Min | Max |
|----------|-------------|-----|-----|
| READ | ... | ... | ... |
| CREATE | ... | ... | ... |
| ... | | | |

## Token Usage Breakdown

| Category | Avg Input Tokens | Avg Output Tokens | Avg Total |
|----------|-----------------|-------------------|-----------|
| READ | ... | ... | ... |
| CREATE | ... | ... | ... |
| ... | | | |

## Top Failure Modes

| Failure Mode | Count | % of Failures |
|-------------|-------|---------------|
| Auth required | ... | ... |
| CAPTCHA | ... | ... |
| Site unavailable | ... | ... |
| Navigation failure | ... | ... |

## Worst Performing Websites (by failure count)

| Website | Tasks | Failures | Failure Rate |
|---------|-------|----------|-------------|
| ... | ... | ... | ... |

## Best Performing Websites (by pass rate, min 3 tasks)

| Website | Tasks | Pass Rate | Avg Score |
|---------|-------|-----------|-----------|
| ... | ... | ... | ... |

## Sample Failures

{Show 5-10 representative failures with task description, what went wrong, and verdict reasoning}

## Methodology

- **Execution:** One task per session via agent-web-interface browser automation
- **Evaluation:** LLM-as-judge with structured rubric (PASS=1.0, PARTIAL=0.5, FAIL=0.0)
- **Scoring dimensions:** Navigation, Comprehension, Completeness, Accuracy, Confirmation
- **Infrastructure blockers** (auth, CAPTCHA, site down) scored as FAIL but flagged separately

Output

File: web-bench-report.md in working directory
Report should be self-contained and readable without the raw JSONL data

Guardrails

Use the JSONL file as the sole source of truth — do not fabricate statistics
Format all durations as human-readable (e.g., "2h 34m 12s" not "9252000ms")
Format token counts with thousands separators
Round percentages to one decimal place
If results file has fewer than the expected total tasks, note this prominently in the report header

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name	generate-report
description	Aggregate WebBench benchmark results into a comprehensive evaluation report. Triggers: "generate report", "create benchmark report", "summarize results", "aggregate scores", "produce evaluation report". Reads web-bench-results.jsonl, computes statistics by category/website/failure mode, and writes web-bench-report.md with pass rates, timing, token usage, and analysis. Does NOT execute or evaluate tasks — only aggregates existing results.
allowed-tools	Read Write Edit Bash Glob Grep

Generate WebBench Benchmark Report

Aggregate all results from web-bench-results.jsonl into a comprehensive markdown report.

Input

Results file: web-bench-results.jsonl — one JSON line per completed task

Result line schema:

{
  "id": 42,
  "url": "https://acehardware.com",
  "category": "READ",
  "task": "Navigate to...",
  "score": 1.0,
  "verdict": "PASS",
  "reasoning": "Successfully extracted all specs",
  "error": null,
  "duration_ms": 34200,
  "tokens_used": {"input": 12450, "output": 3200},
  "timestamp": "2026-03-19T14:30:00Z"
}

Report Generation

Use Node.js to compute all statistics:

node -e "
const fs = require('fs');
const results = fs.readFileSync('web-bench-results.jsonl','utf-8').trim().split('\n')
  .filter(l => l.trim()).map(JSON.parse);

const total = results.length;
const passed = results.filter(r => r.verdict === 'PASS').length;
const partial = results.filter(r => r.verdict === 'PARTIAL').length;
const failed = results.filter(r => r.verdict === 'FAIL').length;
const totalScore = results.reduce((s, r) => s + r.score, 0);

// Timing
const totalDurationMs = results.reduce((s, r) => s + (r.duration_ms || 0), 0);
const avgDurationMs = total ? totalDurationMs / total : 0;

// Tokens
const totalInputTokens = results.reduce((s, r) => s + ((r.tokens_used || {}).input || 0), 0);
const totalOutputTokens = results.reduce((s, r) => s + ((r.tokens_used || {}).output || 0), 0);
const totalTokens = totalInputTokens + totalOutputTokens;

// By category
const byCat = {};
for (const r of results) {
  if (!byCat[r.category]) byCat[r.category] = [];
  byCat[r.category].push(r);
}

// By website (top failures)
const bySite = {};
for (const r of results) {
  if (!bySite[r.url]) bySite[r.url] = [];
  bySite[r.url].push(r);
}

// Failure modes
const blockers = {};
for (const r of results) {
  if (r.error) blockers[r.error] = (blockers[r.error] || 0) + 1;
}

const catStats = {};
for (const [cat, rs] of Object.entries(byCat)) {
  catStats[cat] = {
    total: rs.length,
    passed: rs.filter(r => r.verdict === 'PASS').length,
    score: rs.reduce((s, r) => s + r.score, 0) / rs.length
  };
}

const siteFailures = Object.entries(bySite)
  .map(([site, rs]) => [site, rs.filter(r => r.verdict === 'FAIL').length])
  .sort((a, b) => b[1] - a[1]).slice(0, 20);

console.log(JSON.stringify({
  total, passed, partial, failed,
  totalScore, avgScore: total ? totalScore / total : 0,
  totalDurationMs, avgDurationMs,
  totalInputTokens, totalOutputTokens, totalTokens,
  byCategory: catStats,
  bySiteFailures: Object.fromEntries(siteFailures),
  blockers
}, null, 2));
"

Report Template

Write web-bench-report.md with this structure:

# WebBench Benchmark Report

**Date:** {timestamp}
**Agent:** {agent identifier}
**Dataset:** Halluminate/WebBench
**Tasks evaluated:** {total} / 2454

---

## Overall Results

| Metric | Value |
|--------|-------|
| **Pass Rate** | {passed}/{total} ({pass_pct}%) |
| **Partial Rate** | {partial}/{total} ({partial_pct}%) |
| **Fail Rate** | {failed}/{total} ({fail_pct}%) |
| **Average Score** | {avg_score:.2f} / 1.0 |
| **Total Duration** | {total_duration_formatted} |
| **Avg Duration/Task** | {avg_duration_formatted} |
| **Total Tokens** | {total_tokens:,} ({input_tokens:,} input + {output_tokens:,} output) |
| **Avg Tokens/Task** | {avg_tokens:,} |

## Results by Category

| Category | Total | Pass | Partial | Fail | Pass Rate | Avg Score |
|----------|-------|------|---------|------|-----------|-----------|
| READ | ... | ... | ... | ... | ...% | ... |
| CREATE | ... | ... | ... | ... | ...% | ... |
| UPDATE | ... | ... | ... | ... | ...% | ... |
| DELETE | ... | ... | ... | ... | ...% | ... |
| FILE_MANIPULATION | ... | ... | ... | ... | ...% | ... |

## Timing Breakdown

| Category | Avg Duration | Min | Max |
|----------|-------------|-----|-----|
| READ | ... | ... | ... |
| CREATE | ... | ... | ... |
| ... | | | |

## Token Usage Breakdown

| Category | Avg Input Tokens | Avg Output Tokens | Avg Total |
|----------|-----------------|-------------------|-----------|
| READ | ... | ... | ... |
| CREATE | ... | ... | ... |
| ... | | | |

## Top Failure Modes

| Failure Mode | Count | % of Failures |
|-------------|-------|---------------|
| Auth required | ... | ... |
| CAPTCHA | ... | ... |
| Site unavailable | ... | ... |
| Navigation failure | ... | ... |

## Worst Performing Websites (by failure count)

| Website | Tasks | Failures | Failure Rate |
|---------|-------|----------|-------------|
| ... | ... | ... | ... |

## Best Performing Websites (by pass rate, min 3 tasks)

| Website | Tasks | Pass Rate | Avg Score |
|---------|-------|-----------|-----------|
| ... | ... | ... | ... |

## Sample Failures

{Show 5-10 representative failures with task description, what went wrong, and verdict reasoning}

## Methodology

- **Execution:** One task per session via agent-web-interface browser automation
- **Evaluation:** LLM-as-judge with structured rubric (PASS=1.0, PARTIAL=0.5, FAIL=0.0)
- **Scoring dimensions:** Navigation, Comprehension, Completeness, Accuracy, Confirmation
- **Infrastructure blockers** (auth, CAPTCHA, site down) scored as FAIL but flagged separately

Output

File: web-bench-report.md in working directory
Report should be self-contained and readable without the raw JSONL data

Guardrails

Use the JSONL file as the sole source of truth — do not fabricate statistics
Format all durations as human-readable (e.g., "2h 34m 12s" not "9252000ms")
Format token counts with thousands separators
Round percentages to one decimal place
If results file has fewer than the expected total tasks, note this prominently in the report header