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Files added by PR #2008 that were not in main were dropped during the merge. Restore all src/, docs/, and scripts/ files from the pre-merge PR head. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Maximizing Agent Autonomy & Superpowers
The Foundational Insight
Autonomy comes from self-correction, not from getting it right the first time. The power isn't in the initial generation — it's in iteration speed and feedback signal quality.
The Essential Tool Arsenal
| Category | Tools | Why |
|---|---|---|
| Execution Environment | Terminal, filesystem, git, package manager | Closes the write → run → debug → verify loop |
| Verification | Test runner, linter, type checker, security scanner | Ground truth over self-assessment |
| Observation | Logs, browser/renderer, performance profiler | Sees what users would see |
| Exploration | Code search, documentation lookup, web research | Self-directed learning |
| Recovery | Git revert, branch management, checkpoints | Safety net that enables boldness |
Self-Verification Architecture
Every task completion should self-evaluate against a checklist:
- Does the code compile?
- Do all existing tests still pass?
- Do new tests pass?
- Does the application actually start?
- Can I exercise the feature and see expected behavior?
- Does this match acceptance criteria point by point?
Debugging Superpowers
- Temporary instrumentation: Add logging, remove after diagnosis
- Bisection: Walk back through changes to find where regression was introduced
- Minimal reproduction: Strip away everything except exact conditions that trigger failure
- Exploratory tests: Quick throwaway scripts to test hypotheses
Meta-Cognitive Layer
- Scratchpad: External reasoning space to track hypotheses, attempts, and outcomes
- Stuck detection: After N failed attempts, trigger step-back with fresh context and explicitly different approach
- Structured escalation: "Here's what I'm trying, here's what I've tried, here's what I think the issue is, here's what I need from you"
The Philosophy
You're not trying to build an agent that doesn't make mistakes. You're building one that catches and fixes its own mistakes faster than a human would notice them. Not intelligence — closed-loop execution with rich feedback.