Fixing AI Tool Calling Context Bloat
LLM agents rely on tool calls — but tool responses are huge. Gmail, CRMs, and APIs return bloated JSON LLMs choke on large responses You only need 2–3 fields, but frameworks give you zero control Toolflow is an AI-native framework to fix this: * Filter tool responses before they hit the LLM * Context modes: `minimal`, `full`, `custom`, or `ai` * Composable TypeScript tool registry GitHub: [https://github.com/dksingh1997/toolflow](https://github.com/dksingh1997/toolflow) Would love feedback — especially from those building with LLMs in production.
Fixing AI Tool Calling Context Bloat launched on June 18, 2025 with 5 votes and more than 75% of that year's launches. The site was still online in September 2026, 1 year on.
What it does
Manage tool responses in AI agents. Works with Composio, Pipedream, Custom APIs - dksingh1997/Toolflow
AI-Native Tool Calling Framework — Build intelligent agents that interact with tools via natural language, with minimal context bloat and full developer control. Modern AI agents rely heavily on tool calling to fetch data or perform actions. But in practice: "Fetching Gmail emails returns hundreds of fields. I just need subject, from, and snippet!" – Every AI dev, ever { "data": { "messages": [ { "from": "Dheeraj Kumar", "subject": "Repo check", "snippet": "Hi Dheeraj, Does this repo makes sense ?", "date": "Tue, 17 Jun 2025 12:01:00 +0200" } ], "nextPageToken": "16428802254119354251", "resultSizeEstimate": 201 }, "error": null, "successfull": true, "successful": true, "logId":…from github.com
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