/p/2026-10-13 · explainer
Paper explainer · 2610.13889 · Chen and Liao

The retriever ranked the dead tool first.

A tool index ranks on how well a description matches the request, which says nothing about whether the tool answers when it is called. Switch off 30% of the pool mid-run and an embedding retriever keeps sending 86.2% of selections to a tool that is down, because a dead tool is still the best semantic match. Keeping one success-or-error bit per tool, and letting it re-rank the top ten, takes that to 2.9% for 0.17 ms a call.

01 · The problem

Similarity cannot tell you what answers

share of the tool pool that is down

02 · The mechanism

Three terms, one of which knows what happened

03 · The loop

One bit per call, discounted

04 · Why I care

The number that moves is the one nobody logs

how much of the pool is down

05 · Apply it

What a success bit is worth in your tool layer illustrative

Results

What the paper actually measured

What it does not show

In practice