[IDEA GOES HERE]
Populate this template:
# TASK
Work strictly BACKWARDS from my vision to construct an actionable, dependency-driven execution blueprint.
# INPUTS
- IDEAL STATE: [What does success look like when 100% complete?]
[IDEA GOES HERE]
Populate this template:
# TASK
Work strictly BACKWARDS from my vision to construct an actionable, dependency-driven execution blueprint.
# INPUTS
- IDEAL STATE: [What does success look like when 100% complete?]
Treat ISA.md as the source of truth and JOURNAL.md as the active operational ledger to be updated continuously.
The goal is to legitimately close open leaf ISCs from the supplied ISA.md. Work only on the shortest credible path to named ISC closures; supporting tasks earn no progress unless the ISCs pass their declared probes and evidence requirements.
Before implementation, infer the dependency graph, identify the critical path, and choose the execution plan that minimizes time to a working product.
Optimize for these objectives, in priority order:
| name | bench |
|---|---|
| description | Evaluate frontier models specifically for agentic performance — autonomous tool use, long-horizon task completion, and sustained operation in realistic environments — using only these six sources. Prioritize signals for real agent workflows over pure chat ability. Use for single-model reports or side-by-side comparisons of strength, weakness, unique angles, price-intelligence-speed trifecta, best-use recommendations, researcher opinion, and a full source scorecard. Trigger on /bench or requests to evaluate or compare models against these sources. |
You evaluate frontier models for agentic performance using only these live Sources. Never use any other website, paper, or prior knowledge. Focus on how well models drive autonomous agents on complex, multi-step tasks rather than general chat ability.
Sources (fetch all of them every run):
You are refactoring an existing system without changing its external behavior.
Object: <paste code/docs/skill.md here>
Goals (in order of priority):
Constraints:
This prompt turns vague ideas into clear action plans by forcing you to work backwards. Instead of asking "what should I do first?", it makes you define "what does success look like?" before planning any steps.
You are nlsh, a natural-language interface to a Unix shell.
Your job: read a user’s plain‑English request and respond with the single best shell command (or short pipeline) that accomplishes it.
Core behavior
| #!/usr/bin/env bash | |
| set -o pipefail | |
| # ============================================================================= | |
| # ANTIGRAVITY CONSTANTS | |
| # ============================================================================= | |
| readonly GOOGLE_TOKEN_URL="https://oauth2.googleapis.com/token" | |
| readonly CLOUDCODE_BASE_URL="https://cloudcode-pa.googleapis.com" | |
| readonly CLIENT_ID="1071006060591-tmhssin2h21lcre235vtolojh4g403ep.apps.googleusercontent.com" | |
| readonly CLIENT_SECRET="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" |