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Python dictionary key order, by itself, does not explain why an agent field disappeared at 400 characters. Python preserves dictionary insertion order in supported versions, and its JSON module preserves order by default. But the incident’s root cause and what “400 characters” measures are not verified by the available evidence. To find the fault, trace the field through serialization, transport, parsing, schema handling, and the agent’s final input.
Can dictionary key order make a JSON field disappear?
Not in the ordinary sense of changing the order of keys. Python guarantees dictionary insertion order starting with Python 3.7; check the interpreter actually running the affected code before relying on that guarantee. The Python tutorial documents this behavior.
Python’s json module documentation says its encoders and decoders preserve input and output order by default. The module can also sort keys when configured with sort_keys=True. Sorting can change their sequence in serialized output, but order is not a safe way to express that one field matters more than another. A receiver may select named fields, validate against a schema, or otherwise process the object without treating earlier keys as higher priority.
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Python issue 30550 is historical discussion about documenting order-preserving output. It provides context for Python’s encoder behavior, not evidence that key order caused this particular field loss.
What does “400 characters” count?
The number alone does not identify a technical limit. It could refer to the value of one field, the serialized JSON text, a prompt fragment, a display cutoff, or another boundary. The available incident description does not establish which meaning applies, nor does it verify that 400 is the threshold at which the field disappears.
Do not treat a character count as interchangeable with bytes, tokens, or conversation items. If an API or runtime limit is suspected, identify the exact documented limit and what it counts before attributing the behavior to truncation.
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Trace the field at every boundary
Capture the same minimal input at each stage so you can identify the first point where the field changes or vanishes. Redact secrets before recording payloads.
- Original mapping: Record the Python version, the mapping before serialization, the field’s exact key and value, and the insertion sequence.
- Serialized output: Record the exact JSON string or bytes and the serializer options, including whether
sort_keysor a custom encoder is in use. - Received payload: Check what actually crossed the boundary, rather than assuming it matches the local serialized value.
- Parsed structure: Inspect the decoder’s result, including key names and types. Check for custom decoding or transformations after parsing.
- Schema or projection: Verify that the receiving schema, validation step, or field-selection logic includes the field under the same name and type.
- Agent input and output: Inspect the final input presented to the agent and the output or downstream result. This distinguishes a field missing before the agent from one present but not used.
Compare the reproduction with ordinary insertion order, sort_keys, string and non-string keys, custom encoders or decoders, and downstream field selection. Change one variable at a time; a missing field at the final stage does not identify which earlier boundary failed.
Make important fields explicit
If the agent depends on a value, express that dependency through a named field or schema and validate that it is present before the agent runs. Do not rely on the field appearing earlier in a JSON object to communicate priority.
- Check that the key is present and has the expected type.
- Validate required fields at the receiving boundary and report a clear error when one is absent.
- Keep a minimal reproducible input and compare the serialized, received, and parsed forms.
- If truncation is suspected, determine whether the responsible layer counts characters, bytes, tokens, or conversation items.
Keep context-window truncation separate from JSON ordering
The OpenAI Agents SDK models documentation describes a Responses API option for automatically truncating conversation context when it exceeds a model’s context window; that behavior can drop older conversation items. It does not document a generic 400-character field limit, and it does not connect context truncation to the incident described here. Treat it as a separate mechanism to check only if the affected application uses that option and the missing data is part of conversation history.
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