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KikoCis
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KikoCis
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A repository-exploration subagent for coding agents. Invoked on demand by your main agent, it fires parallel read-only tool calls (READ / GLOB / GREP) across a repo and returns only the file paths + line ranges that matter, as compact context. Your frontier coding agent stops wasting its context window (and your bill) crawling the file tree.
Microsoft's (now-deleted) announcement reported ~60% fewer tokens from the main coding agent and +5.5% on SWE-bench — their figures; the source no longer exists to cite.
Architecture: plain Qwen3ForCausalLM dense 4B — 36 layers, 256K native context. No exotic modules; loads with standard transformers.
python
from transformers import AutoModelForCausalLM, AutoTokenizerm = AutoModelForCausalLM.from_pretrained("KikoCis/FastContext-1.0-4B-SFT", torch_dtype="bfloat16", device_map="auto")tok = AutoTokenizer.from_pretrained("KikoCis/FastContext-1.0-4B-SFT")
Don't want 8 GB? Grab the GGUF quants (1.96–2.5 GB, long-context imatrix, retrieval-validated 30/30 vs this bf16): 👉 KikoCis/FastContext-1.0-4B-longctx-imatrix-GGUF
Model, weights, training: © Microsoft (MIT). This is a preservation mirror sourced via the ShaunGves/FastContext-1.0-4B-SFT re-upload after microsoft/FastContext-1.0-4B-SFT was removed. Nothing modified. Quantized companion + validation: KikoCis.