RFD 043: Incremental Tool Call Argument Streaming

Status: Discussion
Category: Design
Authors: Jean Mertz git@jeanmertz.com
Date: 2026-02-24
Requires: RFD 012

Summary

This RFD proposes extending the EventBuilder to incrementally parse tool call argument JSON as it streams in, emitting a recursive stream of typed fragments so that downstream consumers (e.g. the terminal renderer) can act on argument data as it arrives — including partial string values, individual array items, and nested object entries — before the full tool call is complete.

Motivation

When the LLM calls a tool like fs_create_file, the terminal currently shows nothing until all arguments have been fully received and parsed. For tools with large arguments — file content, code, diffs — this means several seconds of silence between the "Calling tool X" header and the styled argument display.

Today's flow:

txt

content_block_start(tool_use{id, name})
  → Event::Part with ToolCallRequest{id, name, arguments: {}}     ← UI shows "Calling tool X"
content_block_delta(input_json_delta: '{"path":')
  → swallowed by ToolCallRequestAggregator                        ← silence
content_block_delta(input_json_delta: '"src/main.rs","content":')
  → swallowed                                                     ← silence
  ... 8+ seconds of JSON chunks ...
content_block_stop
  → Event::Part with ToolCallRequest{id, name, arguments: {path, content}}
  → Event::Flush                                                  ← UI shows styled args

If we could emit the path argument as soon as its value is complete, the UI could show "creating src/main.rs" within the first second. And if the content string were streamed as chunks, the file content could appear in the terminal in real-time rather than all at once.

For tools like fs_modify_file, whose patterns argument is an array of objects with potentially large old and new string fields, the same principle applies recursively: each array item's fields can stream as they arrive, giving the user immediate feedback on what's being changed.

Design

User-facing behavior

No changes to the CLI interface or configuration. The observable difference is that tool call arguments appear in the terminal incrementally:

Tool name appears immediately (already implemented).
Short arguments (paths, flags) appear as soon as their value is parsed.
Long string arguments (file content, diffs) stream to the terminal in real-time as chunks arrive.
Compound arguments (arrays, nested objects) stream recursively — individual items and entries appear as they arrive, with their own values streaming in turn.

Callers that don't care about incremental updates continue to work unchanged — they ignore the intermediate events and only act on the final flushed ToolCallRequest.

Event model

The EventBuilder currently emits ToolCallRequest events only on flush, with all arguments populated at once. This RFD introduces a streaming fragment protocol that the EventBuilder emits during accumulation, before the flush.

The protocol mirrors the existing Event::Part / Event::Flush pattern: fragments stream in, a Done signal marks completion. Every value — whether a scalar, a long string, or a deeply nested object — follows the same pipeline. There is no separate "complete" vs "streaming" code path.

Fragment types

rust

/// A non-string, non-compound JSON value.
///
/// Separated from `serde_json::Value` so that the type system enforces
/// that strings, arrays, and objects are always streamed through their
/// respective `StreamFragment` variants — never smuggled inside a
/// catch-all `Value`.
pub enum Scalar {
    Null,
    Bool(bool),
    Number(serde_json::Number),
}

/// A single fragment of an incrementally parsed JSON value.
///
/// The parser emits a sequence of fragments as JSON chunks arrive.
/// Every value path ends with `Done`. Recursive nesting encodes the
/// path from root to leaf — each fragment is self-describing.
pub enum StreamFragment {
    /// A scalar value (null, bool, or number).
    Scalar(Scalar),

    /// A chunk of string data.
    String(String),

    /// An item in a streaming array.
    ArrayItem {
        index: usize,
        value: Box<StreamFragment>,
    },

    /// A key-value pair in a streaming object.
    ObjectEntry {
        key: String,
        value: Box<StreamFragment>,
    },

    /// No more fragments for this value.
    Done,
}

The EventBuilder wraps each fragment with tool call identity:

rust

/// Ephemeral progress event emitted by EventBuilder during tool call
/// argument streaming. Not persisted to the conversation stream.
pub struct ToolCallArgumentProgress {
    pub tool_call_id: String,
    pub tool_name: String,
    pub fragment: StreamFragment,
}

Protocol examples

For fs_create_file with {"path": "/tmp/foo.rs", "content": "fn main() {...}"}:

txt

ObjectEntry { key: "path", value: String("/tmp/foo.rs") }
ObjectEntry { key: "path", value: Done }
ObjectEntry { key: "content", value: String("fn main(") }
ObjectEntry { key: "content", value: String(") {...}") }
ObjectEntry { key: "content", value: Done }
Done

The renderer sees path complete in the first events (after getting Done in the second event) and can display "creating /tmp/foo.rs" immediately. The content string streams to the terminal in real-time.

For fs_modify_file with {"path": "lib.rs", "patterns": [{"old": "long...", "new": "also long..."}]}:

txt

ObjectEntry { key: "path", value: String("lib.rs") }
ObjectEntry { key: "path", value: Done }
ObjectEntry { key: "patterns", value: ArrayItem { index: 0, value:
    ObjectEntry { key: "old", value: String("lo") } } }
ObjectEntry { key: "patterns", value: ArrayItem { index: 0, value:
    ObjectEntry { key: "old", value: String("ng...") } } }
ObjectEntry { key: "patterns", value: ArrayItem { index: 0, value:
    ObjectEntry { key: "old", value: Done } } }
ObjectEntry { key: "patterns", value: ArrayItem { index: 0, value:
    ObjectEntry { key: "new", value: String("also ") } } }
ObjectEntry { key: "patterns", value: ArrayItem { index: 0, value:
    ObjectEntry { key: "new", value: String("long...") } } }
ObjectEntry { key: "patterns", value: ArrayItem { index: 0, value:
    ObjectEntry { key: "new", value: Done } } }
ObjectEntry { key: "patterns", value: ArrayItem { index: 0, value: Done } }
ObjectEntry { key: "patterns", value: Done }
Done

Each nesting level encodes the path from root to leaf. The renderer can stream each pattern's old and new fields as they arrive.

For a scalar argument like {"dry_run": true}:

txt

ObjectEntry { key: "dry_run", value: Scalar(Bool(true)) }
ObjectEntry { key: "dry_run", value: Done }
Done

Scalars are a single fragment followed by Done, same pipeline as everything else.

If the root value is not an object (e.g. a bare string), the parser streams it directly — String("chunk") fragments followed by Done. No special error case needed; the protocol handles any JSON shape.

Aggregator layer

Consumers that don't care about streaming can use a FragmentAggregator that collects fragments and emits complete serde_json::Values:

rust

struct FragmentAggregator { /* ... */ }

impl FragmentAggregator {
    /// Feed a fragment. Returns `Some(Value)` when a value is complete
    /// (i.e. `Done` was received).
    fn push(&mut self, fragment: StreamFragment) -> Option<serde_json::Value>;
}

The EventBuilder uses this internally to build the final ToolCallRequest.arguments map, adding each argument as its Done arrives. This replaces the ToolCallRequestAggregator that currently lives in the provider layer.

Where the parsing lives

The incremental JSON parsing happens inside EventBuilder, not in the provider layer. This is a change from today's architecture, where the provider layer's ToolCallRequestAggregator buffers raw JSON strings and parses them on finalize.

With this RFD, argument parsing moves entirely to EventBuilder via the IncrementalArgParser and FragmentAggregator. The ToolCallRequestAggregator is removed. Providers already emit ToolCall(ArgumentChunk(chunk)) events via the EventPart redesign from RFD 012. The EventBuilder feeds these chunks to the IncrementalArgParser, which emits StreamFragments. The FragmentAggregator collects these and populates ToolCallRequest.arguments progressively. By flush time, the arguments map is complete.

Incremental JSON parsing

The parser is a recursive descent state machine that emits StreamFragment events as JSON chunks arrive. It maintains a stack tracking the current nesting context:

Object context: expecting a key or a value; tracks the current key.
Array context: expecting an item; tracks the current item index.
String context: accumulating string data; tracks escape sequence state.
Scalar context: accumulating a number, boolean, or null literal.

On each push(chunk) call, the parser appends to its internal buffer and advances the state machine, emitting fragments as structural boundaries are detected.

For example, given {"path":"/tmp/foo.rs","content":"fn main() {}\n","dry_run":false}, the parser emits:

txt

ObjectEntry { key: "path", value: String("/tmp/foo.rs") }
ObjectEntry { key: "path", value: Done }
ObjectEntry { key: "content", value: String("fn main()") }   ┐
ObjectEntry { key: "content", value: String(" {}\n") }       ├ streamed as chunks arrive
ObjectEntry { key: "content", value: Done }                  ┘
ObjectEntry { key: "dry_run", value: Scalar(Bool(false)) }
ObjectEntry { key: "dry_run", value: Done }
Done

The parser handles:

Strings: Emitted as String chunks as data arrives. Escape sequences (\", \\, \uXXXX) are decoded correctly. If a chunk boundary splits an escape sequence, the partial escape is buffered until the next chunk resolves it.
Objects: Each key-value pair is wrapped in ObjectEntry. The key is parsed first (always a complete string), then the value is parsed recursively.
Arrays: Each item is wrapped in ArrayItem with its index. Items are parsed recursively.
Scalars: Numbers, booleans, and null are emitted as Scalar once the literal is complete (detected by the next structural character or whitespace).
Done signals: Emitted at each level when the closing delimiter (}, ], or end of string/scalar) is reached.

EventBuilder changes

The IndexBuffer::ToolCall variant gains an incremental parser and an optional fragment aggregator:

rust

enum IndexBuffer {
    // ...existing variants...
    ToolCall {
        request: ToolCallRequest,
        /// Incremental argument parser. None if the tool call arrived
        /// as a single Part (no streaming).
        arg_parser: Option<IncrementalArgParser>,
        /// Aggregator that collects fragments into complete values,
        /// populating `request.arguments` progressively.
        aggregator: FragmentAggregator,
    },
}

When the EventBuilder receives a ToolCall(ArgumentChunk(chunk)), it:

Feeds the chunk to the IncrementalArgParser.
The parser returns Vec<StreamFragment> — zero or more fragments.
Each fragment is fed to the FragmentAggregator, which adds completed arguments to request.arguments as their Done arrives.
Each fragment is wrapped in ToolCallArgumentProgress (with tool call id and name) and returned to the caller.

The existing handle_flush behavior is unchanged — it returns the final ToolCallRequest with all arguments. The aggregator ensures arguments parsed incrementally are already present in the request by flush time.

Return type for handle_part

EventBuilder::handle_part currently returns nothing — it just accumulates. With this RFD, it returns Vec<ToolCallArgumentProgress> (empty for non-tool-call parts). The TurnCoordinator forwards these to the ToolRenderer.

TurnCoordinator changes

The TurnCoordinator already matches on EventPart::ToolCall variants (per RFD 012). The change is that handle_part now returns ToolCallArgumentProgress events for ArgumentChunk parts:

rust

EventPart::ToolCall(ToolCallPart::ArgumentChunk(_)) => {
    let progress = self.event_builder.handle_part(index, part, metadata);
    for event in progress {
        // Forward to ToolRenderer for incremental display
    }
}

Provider changes

Providers already emit ToolCall(ArgumentChunk(chunk)) per RFD 012. The only change is that the ToolCallRequestAggregator is removed from the EventBuilder and replaced by the IncrementalArgParser + FragmentAggregator pipeline.

Backwards compatibility

The final ToolCallRequest event on flush is identical to today's.
ToolCallArgumentProgress events are ephemeral and not persisted.
The ConversationStream is not affected.
No new Event variants are added — this RFD builds on the EventPart types introduced by RFD 012.

Drawbacks

Recursive parser complexity. The incremental JSON parser is a recursive descent state machine that must handle arbitrary nesting depths correctly. Edge cases include escaped characters in strings at any depth, Unicode escapes (\uXXXX), escape sequences split across chunk boundaries, and deeply nested structures. This is substantially more complex than a top-level-only parser.
Box allocations per fragment. Each nesting level in a StreamFragment requires a Box allocation. For patterns[0].old string chunks, that's three Boxes per chunk. In a CLI streaming terminal output where chunks are tens to hundreds of bytes, this is negligible — but it is a per-chunk cost proportional to nesting depth.
Argument order assumption. The incremental parsing is most useful when short arguments (like path) come before long ones (like content). Most providers emit arguments in schema-definition order, but this is not guaranteed by any spec. If content comes first, the user still sees it streamed in real-time, but the path won't appear until after the full content has been received.

Alternatives

Keep ToolCallRequestAggregator alongside the incremental parser

Keep the existing ToolCallRequestAggregator in the provider layer as the authoritative source for the final ToolCallRequest, and treat the incremental parser as a best-effort side channel for UI progress. This provides defense in depth — if the incremental parser has a bug, the aggregator still produces correct arguments on flush.

Rejected because:

It means buffering every JSON chunk twice (once in the aggregator, once in the parser) for no functional benefit.
The incremental parser + FragmentAggregator already produce the complete arguments by flush time. A second independent parse path adds complexity without improving correctness — if the parser is buggy, the aggregator would silently mask the bug rather than surfacing it.
Removing the aggregator simplifies the provider layer: providers just forward chunks and let EventBuilder handle parsing.

Use a streaming JSON parser crate

Use something like serde_json::StreamDeserializer or a SAX-style JSON parser instead of a hand-written state machine. Worth investigating during implementation. A SAX-style parser would provide the event stream we need (start-object, key, start-string, string-data, end-string, etc.) and the IncrementalArgParser would translate SAX events into StreamFragments. If a well-tested crate fits with minimal API surface, it should be preferred over a hand-rolled parser — especially given the recursive parsing requirement.

Emit intermediate ToolCallRequest events with partial arguments

Instead of a separate ToolCallArgumentProgress type, emit ToolCallRequest events with partial arguments maps. Rejected because:

Consumers that match on ToolCallRequest would need to distinguish partial from complete.
Partial events would need careful handling in persistence to avoid writing incomplete tool calls.
A distinct type makes the contract explicit: these are progress signals, not complete events.

Flat (non-recursive) fragment model

Stream only top-level argument key-value pairs, emitting nested structures (arrays, objects) as complete serde_json::Values. Simpler parser, but loses the ability to stream inside fs_modify_file's patterns array or any other nested structure with large string values. The recursive model adds Box allocations per nesting level per fragment, but this cost is negligible for a CLI tool and the streaming benefit for nested arguments is real.

Carry complete value in terminal Done fragment

Instead of a data-free Done, have Done(serde_json::Value) carrying the final assembled value. Rejected because:

The value is redundant — the consumer either aggregated from chunks already, or uses the final ToolCallRequest from the flush path.
For large string values, this means allocating the full value a second time just to attach it to a signal nobody reads.
The FragmentAggregator provides this convenience for consumers that need complete values without duplicating data in the streaming protocol.

Non-Goals

Terminal renderer changes. How the renderer uses ToolCallArgumentProgress events to update the display is out of scope. The renderer already has the infrastructure for incremental tool call display (ToolRenderer::register, complete). Wiring up the new events is straightforward follow-up work.
Reordering arguments. We do not attempt to reorder arguments to ensure short ones arrive first. The LLM controls the order.

Risks and Open Questions

JSON edge cases. The incremental parser must handle: escaped quotes (\"), Unicode escapes (\uXXXX), nested objects and arrays, null / true / false / numbers as values, empty objects and arrays. The recursive parser must handle these at every nesting depth. A thorough test suite with property-based testing is warranted.
Escape sequences at chunk boundaries. A chunk can split mid-escape: \ at the end of one chunk, " at the start of the next. Or \u00 in one chunk, 41 in the next. The parser needs a small state machine (4-5 states) to handle partial escapes at every string nesting level. This is the trickiest part of the parser implementation.
Provider argument ordering. We assume providers tend to emit arguments in schema-definition order. If a provider reorders arguments (e.g. longest first), the incremental parsing adds overhead with no user-visible benefit. This should be validated empirically with Anthropic, OpenRouter, and Llamacpp.
Chunk boundaries. JSON chunks from providers can split at arbitrary byte positions — including mid-string, mid-escape-sequence, or mid-number. The parser must handle partial data gracefully by buffering until a parse boundary is reached.

Implementation Plan

Phase 1: StreamFragment types and FragmentAggregator

Define the Scalar, StreamFragment, and ToolCallArgumentProgress types in jp_conversation. Implement FragmentAggregator with thorough unit tests. These are pure data types with no I/O dependencies.

Test aggregation: scalars, strings, arrays, nested objects.
Test that Done at each level produces the correct serde_json::Value.
Can be merged independently.

Phase 2: Incremental JSON parser

Implement IncrementalArgParser as a standalone module in jp_conversation with thorough unit tests. This is pure logic with no I/O dependencies.

Input: push(&mut self, chunk: &str)
Output: Vec<StreamFragment>
Recursive parsing of objects, arrays, strings, and scalars.
Edge case tests: escaped strings at every depth, split escape sequences, nested structures, empty containers.
Property-based tests: generate random JSON, chunk it at random boundaries, verify the fragment stream reassembles to the original value via FragmentAggregator.
Can be merged independently.

Phase 3: Event plumbing

Replace the ToolCallRequestAggregator in EventBuilder with IncrementalArgParser + FragmentAggregator for ToolCall(ArgumentChunk(...)) handling.
Update EventBuilder::handle_part to return Vec<ToolCallArgumentProgress> for tool call argument chunks.
Update TurnCoordinator to forward progress events to the ToolRenderer.
Can be merged independently (UI changes are a separate phase).

Phase 4: Terminal renderer integration

Wire ToolCallArgumentProgress events into ToolRenderer to display arguments incrementally. This is follow-up work and can be scoped in a separate PR or RFD.

References

RFD 012 (Event Part Redesign) — prerequisite; introduces EventPart and ToolCallPart
Query Stream Pipeline Architecture
crates/jp_llm/src/stream/aggregator/tool_call_request.rs — ToolCallRequestAggregator (removed by this RFD)
crates/jp_conversation/src/event_builder.rs — current EventBuilder
crates/jp_cli/src/cmd/query/turn/coordinator.rs — TurnCoordinator
crates/jp_cli/src/cmd/query/tool/renderer.rs — ToolRenderer

RFD 043: Incremental Tool Call Argument Streaming ​

Summary ​

Motivation ​

Design ​

User-facing behavior ​

Event model ​

Fragment types ​

Protocol examples ​

Aggregator layer ​

Where the parsing lives ​

Incremental JSON parsing ​

EventBuilder changes ​

Return type for handle_part ​

TurnCoordinator changes ​

Provider changes ​

Backwards compatibility ​

Drawbacks ​

Alternatives ​

Keep ToolCallRequestAggregator alongside the incremental parser ​

Use a streaming JSON parser crate ​

Emit intermediate ToolCallRequest events with partial arguments ​

Flat (non-recursive) fragment model ​

Carry complete value in terminal Done fragment ​

Non-Goals ​

Risks and Open Questions ​

Implementation Plan ​

Phase 1: StreamFragment types and FragmentAggregator ​

Phase 2: Incremental JSON parser ​

Phase 3: Event plumbing ​

Phase 4: Terminal renderer integration ​

References ​

RFD 043: Incremental Tool Call Argument Streaming

Summary

Motivation

Design

User-facing behavior

Event model

Fragment types

Protocol examples

Aggregator layer

Where the parsing lives

Incremental JSON parsing

EventBuilder changes

Return type for handle_part

TurnCoordinator changes

Provider changes

Backwards compatibility

Drawbacks

Alternatives

Keep ToolCallRequestAggregator alongside the incremental parser

Use a streaming JSON parser crate

Emit intermediate ToolCallRequest events with partial arguments

Flat (non-recursive) fragment model

Carry complete value in terminal Done fragment

Non-Goals

Risks and Open Questions

Implementation Plan

Phase 1: StreamFragment types and FragmentAggregator

Phase 2: Incremental JSON parser

Phase 3: Event plumbing

Phase 4: Terminal renderer integration

References