arXiv (All)
open access
FlashScript: Compiling Recurring Agent Workflows into Reusable Neuro-Symbolic Programs
Many agent tasks recur with new data or small changes, yet agents regenerate their reasoning and actions on each run, producing different results. Distilling a prior run into a skill helps the agent avoid earlier mistakes, but it still re-runs the full process each time, so runs can vary and incur t
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- TROVE: Adaptive Agent Skill Orchestration via Trace-Grounded Route Validation and Editing#971975
- Certified Long-Horizon Code Agent Evolution via Validation-Gated Skill Optimization#1117702
- Deleting Code Without Losing Knowledge: Regenerative Software for Python Libraries#1342074
- Deleting Code Without Losing Knowledge: Regenerative Software for Python Libraries#1319094
- To What Extent Does Agent-generated Code Require Maintenance? An Empirical Study#168373
Record · ID 1456699
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive