Author
Ren builds agent infrastructure and writes copy-paste tutorials for engineers shipping LLM tool-use systems.
The beeai-framework docs say onlySuccessInvocations affects forceAtStep. It also silently scopes maxInvocations, consecutiveAllowed, minInvocations and onlyAfter. Measured end to end on 0.1.31, with a control arm on every group.
On @langchain/langgraph 1.4.19 the package root's type declarations export 212 names and its runtime exports 95. Ten of the gap are classes, tsc compiles the broken import without complaint, and one of the imports that fails is copied verbatim from the vendor's own JavaScript documentation.
On @inngest/agent-kit 0.13.2 the option maxIter exists on both Agent.run() and createNetwork(), both default to 0, and 0 means exactly one inference in the first and no limit at all in the second. A harness that measures both with no API key.
On @langchain/langgraph 1.4.19 a DeltaValue field replays checkpointed writes through your reducer in larger batches than your graph produced. If the reducer reads the batching, the resumed state is not the state you ran, and nothing errors. Three runnable scripts: a ten-line invariance check, a run where six turns become one, and a sweep showing the damage sits in the tail.
A suspended workflow can only resume if its state was written somewhere. On @voltagent/core 2.11.0 there are three states, not two: no workflowMemory fails even in the same process, the in-memory adapter dies at process exit, and only a durable adapter survives a restart.
A Mastra output processor that implements only processOutputResult does run on agent.stream(), but it runs after every chunk has been delivered. The redaction lands on result.text and never reaches the reader. Measured on @mastra/core 1.72.0 with no API key.
Measured on @voltagent/core 2.11.0: the first agent call lazily starts three setInterval timers that are never unref'd, so your Node process stays alive forever. Two of them poll 20 times a second. Here is the reproduction, the cause and the fix.
On ai 7.0.116, generateText and streamText run exactly one step by default. Pass tools without stopWhen and the model calls a tool, your tool runs, and you get an empty string with no error. The same package defaults ToolLoopAgent to twenty. Measured on the wire, with the bundle lines that cause it.
The Anthropic provider decides your max_tokens, whether temperature is sent at all, and the whole shape of a generateObject request, from a case-sensitive substring test on your model id. Reproduced first-party on ai 7.0.113 with a local capture server and no real API key.
You gave your agent a shell tool, used execFile so there is no shell, and allowlisted the programs. It is still not safe. If the agent controls the argument array, tar's own --checkpoint-action=exec runs any command with no metacharacters. Here is the reproduction and the per-binary argument policy that stops it, measured on Node 24.8.0.
Agent frameworks build the request for you, then show you a summary of it. Here is a 60-line local server that records the exact JSON body your SDK sends, with no API key, no proxy and no certificate, plus the CI assertion a proxy cannot give you.
The SDK chooses reasoning.effort and text.verbosity from how your model name is spelled, not from what the model supports. Measured on the wire on 0.18.0, including what it does to a custom gateway deployment name.
