Individual skill
query-loop-implementation
Implement a production-ready LLM query loop / agent loop for AI applications. Use this skill whenever the user wants to add tool calling, ReAct-style reasoning-action-observation cycles, function calling loops, query engines, agent runtimes, tool_result feedback, max-turn exits, or Claude Code-like Agent Loop behavior to their own product or codebase.
skills/query-loop-implementation/SKILL.md
Source commit e5ba66cac91c857dce254dc6b6195d52201068d8
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- Yes
- Observed behavior
- Not checked yet
- Last checked
- Nov 11, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 203
- Repository last updated
- Aug 26, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- agent-skills Repository topic
- agentskills Repository topic
- anthropic Repository topic
- anthropic-claude Repository topic
- growth-investing Repository topic
- investing Repository topic
- skills Repository topic
- stock-analysis Repository topic
- book2skills Repository topic
- investing-skills Repository topic
- engineering Derived category
- engineering-web Derived category
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
LICENSEasset · 626 bytesREADME.mddoc · 2,182 bytesSKILL.mdcore · 5,671 bytesagents/openai.yamlasset · 253 bytesquery-loop-implementation.zipasset · 7,006 bytesreferences/query-loop-patterns.mddoc · 2,492 bytes
Read excerpt
# Query Loop Implementation
## Core Idea
Build the loop as product infrastructure, not prompt glue:
```text
ConversationManager -> QueryLoop -> ToolRuntime
```
- `ConversationManager` owns durable state: session id, messages, user settings, budget, persistence.
- `QueryLoop` owns one task turn: call model, detect tool calls, execute tools, append tool results, repeat.
- `ToolRuntime` owns registered tools: schemas, permission checks, execution, error formatting.
