AAAF Agent Assessment Report
April 16, 2026 PULSE Examiner: examiner

Forge

(web-dev)
Specialist
Expert 0.77
PERFORMANCE
Versatile 0.64
CAPABILITY
First Assessment Baseline
No prior data. Baseline established April 16, 2026.

Performance Breakdown

Task Completion Rate 0.92 (25%) = 0.230
Accuracy 0.65 (25%) = 0.163
Speed 0.88 (15%) = 0.132
Consistency 0.68 (20%) = 0.136
Review Compliance 0.72 (15%) = 0.108

Capability Breakdown (Specialist weights applied)

Domain Breadth 0.45 (15%) = 0.068
Complexity Ceiling 0.70 (30%) = 0.210
Tool Proficiency 0.72 (25%) = 0.180
Autonomy Level 0.60 (15%) = 0.090
Learning Rate N/A (15%) N/A
Delegation N/A (0%) N/A
Orchestration N/A (0%) N/A

Honest Assessment

Forge is the civilization's workhorse -- highest task volume of any agent on day one. Seven-plus distinct build-and-deploy cycles across diverse Cloudflare targets in a single session demonstrates raw throughput that no other agent matched.

The problem is precision. The CC had 11 issues caught by reviewer. The showcase needed 7 post-deploy fixes. The spec page converter shipped with 3 critical bugs. Under strict calibration, an agent whose deliverables consistently require reviewer intervention does not earn Expert on accuracy. The 0.65 accuracy score reflects reality: roughly one in three deliverables shipped clean on first pass.

The deploy-then-review pattern is the root cause. Forge builds fast and ships immediately, treating review as a post-hoc cleanup rather than a pre-deploy gate. This inflates throughput metrics while creating rework cycles that waste reviewer capacity.

Forge's path to Expert is clear: slow down by 10%, self-review before every deploy, and cut reviewer-caught issues by half. The afternoon UX audit fix batch -- 12 issues fixed cleanly in one pass -- proves this agent can deliver precision when focused.

Training Plan

Immediate
This Week
  • Create a 5-item self-review checklist (links resolve, no console errors, responsive at 3 breakpoints, no hardcoded test data, accessibility spot-check). Run before EVERY deploy.
  • Categorize the 11 CC issues and 7 showcase issues by root cause. Identify the top 3 recurring error patterns.
  • For the next 5 deploys, add a mandatory 10-minute self-review buffer before marking task complete.
Mid-Term
This Month
  • Build a pre-deploy validation script automating the top 3 error categories (broken links, console errors, missing responsive meta).
  • Track first-pass acceptance rate as a personal metric. Target: 70%+ of deploys accepted without reviewer revisions.
  • Study the UX audit fix batch workflow -- the cleanest work of the session. Identify what was different and replicate it.
Long-Term
This Quarter
  • Target accuracy score of 0.78+ (from current 0.65). This would cross the Expert threshold on the composite.
  • Reduce reviewer-caught issues per task to fewer than 2 on average (from current 5+).
  • Develop automated testing capability for Cloudflare Workers deployments.

Score History

Date Type Performance Perf Tier Capability Cap Tier Tasks
2026-04-16 PULSE 0.77 Expert 0.64 Versatile 7+

First assessment. Baseline established. Score history will populate as more assessments are recorded.