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license: mit
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---
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license: mit
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language:
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- en
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tags:
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- agents
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- llm
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- mcp
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- reliability
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- agent-stack
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- npm
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- pypi
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- typescript
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- python
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- anthropic
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- openai
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- tool-use
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library_name: agent-stack
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---
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# agent-stack
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Six small, single-concern reliability libraries for production LLM agents — published independently to **npm**, **PyPI**, and the **Model Context Protocol** registry. Each library is zero-dependency, under 500 LOC, and addresses one specific failure mode that production agent teams have to handle.
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## Paper
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Backed by a peer-reviewable artifact paper with a DataCite DOI:
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- **DOI:** [10.5281/zenodo.20074702](https://doi.org/10.5281/zenodo.20074702)
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- **Title:** _Six Reliability Primitives for LLM Agents: An Artifact Pattern for Stackable, Single-Concern Libraries_
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- **Status:** Under review at ASE 2026 Tools track.
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## The six primitives
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| Library | Concern | Failure mode it addresses |
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| --- | --- | --- |
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| **AgentFit** | Context-window fitting | Token-aware truncation with multiple strategies. Pluggable tokenizers for OpenAI / Anthropic / open models. |
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| **AgentGuard** | Network egress allowlisting | Blocks the "agent suddenly POSTs PHI / secrets to attacker.com" failure mode. |
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| **AgentSnap** | Snapshot tests for tool-call traces | Catches silent regressions when a model's tool-call shape changes between deploys. |
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| **AgentVet** | Tool-arg validation | Throws a `ToolArgError` carrying an LLM-friendly retry hint, so the next turn can self-correct. |
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| **AgentCast** | Structured-output validate-and-retry | Bring-your-own-LLM JSON validator + retry loop. |
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| **AgentBudget** | Per-run token + dollar caps | Hard cap with hook for early termination. Prevents runaway loops billing $1000 on a single query. |
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Each ships in three runtime forms: **TypeScript on npm**, **Python on PyPI**, and an **MCP-server variant** callable from Claude Desktop, Cursor, Continue, or any MCP client.
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## Install
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### TypeScript (npm)
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```bash
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npm i @mukundakatta/agentvet @mukundakatta/agentguard @mukundakatta/agentbudget
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```
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### Python (PyPI)
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```bash
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pip install agentvet agentguard agentbudget
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```
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### MCP server (Claude Desktop config)
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```json
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{
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"mcpServers": {
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"agentvet": { "command": "npx", "args": ["-y", "@mukundakatta/agentvet-mcp"] },
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"agentguard": { "command": "npx", "args": ["-y", "@mukundakatta/agentguard-mcp"] }
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}
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}
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```
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## Source
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Umbrella repo: [github.com/MukundaKatta/agent-stack](https://github.com/MukundaKatta/agent-stack)
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Per-library repositories (TS + Python + MCP variants) — search GitHub topic [`agent-stack`](https://github.com/search?q=user%3AMukundaKatta+topic%3Aagent-stack) for the full list.
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## Why it exists
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Reliability concerns for LLM agents are typically bundled into one heavy framework that asks you to adopt prompting, tool routing, and runtime governance as a single dependency. agent-stack inverts that: each concern is a separate library you can adopt à la carte without buying into a programming model.
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The artifact paper documents the six primitives, the cross-cutting invariants the design enforces, the trade-offs of single-concern packaging, and the operational questions that emerge when reliability is split across many small dependencies.
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## Citation
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```bibtex
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@misc{katta2026agentstack,
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author = {Katta, Mukunda Rao},
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title = {Six Reliability Primitives for LLM Agents:
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An Artifact Pattern for Stackable, Single-Concern Libraries},
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year = {2026},
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publisher = {Zenodo},
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doi = {10.5281/zenodo.20074702},
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url = {https://doi.org/10.5281/zenodo.20074702}
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}
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```
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## License
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MIT.
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