Analyzed GitHub issue and session data

Summary

In Progress

Setup
Fetched raw gist content.
Setup
Understand
Reviewed relevant code files.
Understand
Build
Provided detailed analysis of message transformations.
Build

Analyze GitHub issue(s): https://gist.github.com/joshp123/d21219179f76cb7a279a276043e739aa corresponding session .jsonl file is here https://gist.githubusercontent.com/joshp123/d21219179f76cb7a279a276043e739aa/raw/d0f0c93c3a98624705fe8d0750977ce015069029/2026-01-17T16-42-08-945Z_b0026b27-4539-4693-a14b-98eeedbca3fd-redacted.jsonl, dontread it in full, as it will blow up your context window.

For each issue:

Read the issue in full, including all comments and linked issues/PRs.
For bugs:
- Ignore any root cause analysis in the issue (likely wrong)
- Read all related code files in full (no truncation)
- Trace the code path and identify the actual root cause
- Propose a fix
For feature requests:
- Read all related code files in full (no truncation)
- Propose the most concise implementation approach
- List affected files and changes needed

Do NOT implement unless explicitly asked. Analyze and propose only.

Let me fetch the raw gist content directly:

Now I understand the issue. Let me read the relevant code files to understand the root cause properly. The issue is about:

When a Codex assistant message ends with stopReason: "error", the tool calls in that message are dropped
But tool results are still being generated for those dropped tool calls
This causes OpenAI to reject the request because there's a function_call_output without a matching function_call

Let me read the relevant files:

packages/ai/src/providers/openai-codex-responses.ts
packages/ai/src/providers/transform-messages.ts

Also let me look at the session log to understand what happened - but just the header/structure, not the full content.

Now let me read the relevant code files to analyze the root cause:

Readopenai-codex-responses.ts

Readtransform-messages.ts

Now I understand the issue fully. Let me trace through the code path:

In openai-codex-responses.ts:
- convertAssistantMessage() at line ~343 skips tool calls if stopReason === "error":
  typescript
```
} else if (block.type === "toolCall" && msg.stopReason !== "error") {
```
```
} else if (block.type === "toolCall" && msg.stopReason !== "error") {
```
- convertToolResult() at line ~365 always emits function_call_output regardless of whether the tool call was emitted.
In transform-messages.ts:
- transformMessages() at around line 78-81 collects tool calls from assistant messages:
  typescript
```
const toolCalls = assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[];
```
```
const toolCalls = assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[];
```
- But this does NOT check stopReason === "error" - it still counts the tool calls.
- Later, the function creates synthetic tool results for orphaned tool calls.
The bug:
- When an assistant message has stopReason === "error", the tool calls inside it are still present in msg.content
- transformMessages() tracks these tool calls in pendingToolCalls
- If there's an existing tool result for that call ID, it gets passed through
- convertToolResult() then emits a function_call_output for it
- But convertAssistantMessage() skips emitting the function_call because stopReason === "error"
- Result: OpenAI sees a function_call_output without a matching function_call → error

The LLM-suggested fix in the issue is mostly correct but incomplete:

The issue mentions two places to fix:

transform-messages.ts: Don't track tool calls from errored assistant messages
openai-codex-responses.ts: Guard to only send tool results if the tool call was emitted

The cleanest approach is fixing this at the source in transform-messages.ts. When extracting tool calls from an assistant message with stopReason === "error", we should skip them entirely rather than tracking them as pending. This prevents the mismatch from occurring and benefits all downstream providers. The extraction at line 91 needs to filter out tool calls when the stop reason indicates an error.

The proposed solution checks the stop reason before extracting: if stopReason === "error", return an empty array; otherwise, filter for tool calls as normal. This ensures error messages don't create pending tool calls that expect results. However, there's a secondary issue—even if we skip the tool call extraction, the tool result message may already exist in the session log from before the error occurred. When convertMessages() processes this result message via convertToolResult(), it would still attempt to convert it even though the corresponding assistant message never emitted the tool call in the first place.

The fix in openai-codex-responses.ts needs to track which call IDs were actually emitted so tool results are only sent for those calls. Looking at the session log flow would clarify how the result message gets recorded and when it should be filtered out.

Let me check the session log structure briefly to understand what happened:

Now I understand the full picture:

Line 193: An assistant message with stopReason: "error" and errorMessage: "terminated" contains a tool call with ID call_KXHLl4OkJLqXnzhwMKjeCdHX|fc_...
What happens when session is resumed:
- The session is loaded and messages are converted via convertMessages() in openai-codex-responses.ts
- transformMessages() is called first, which tracks the tool call as pending
- transformMessages() sees no tool result for this call (because the session was interrupted before the tool executed)
- transformMessages() creates a synthetic tool result for the orphaned call
- Back in convertMessages():
  - convertAssistantMessage() is called, which SKIPS the tool call because stopReason === "error" (line 343)
  - convertToolResult() is called for the synthetic tool result, which ALWAYS emits a function_call_output
- Result: OpenAI receives a function_call_output with no matching function_call → rejection

Looking at line 194 of the session to confirm there's no tool result:

Let me check line 194 to confirm the flow:

So the flow is:

Line 193: Assistant message with stopReason: "error", contains toolCall for call_KXHLl4OkJLqXnzhwMKjeCdHX
Line 194: A user message (likely "continue")
Line 195: Error response about missing tool call

The issue is that when transformMessages() sees the assistant message with the tool call, it tracks it in pendingToolCalls. Then when the user message comes at line 194, it inserts a synthetic tool result (because there's no real tool result for that call ID).

Then convertMessages() in openai-codex-responses.ts:

Sees the assistant message, calls convertAssistantMessage() which SKIPS the tool call because stopReason === "error"
Sees the synthetic tool result, calls convertToolResult() which ALWAYS emits function_call_output

So the request sent to OpenAI has:

The reasoning/text content from the assistant message
A function_call_output for call_KXHLl4OkJLqXnzhwMKjeCdHX
But NO function_call for that ID

OpenAI rejects this with "No tool call found for function call output with call_id..."

Root Cause Analysis:

The issue is a mismatch between two code paths:

openai-codex-responses.ts:convertAssistantMessage() (line ~343): Skips tool calls when stopReason === "error"
transform-messages.ts (line ~91): Does NOT check stopReason when tracking tool calls for synthetic result generation

This creates an inconsistency where:

transformMessages() generates synthetic tool results for tool calls in errored messages
convertAssistantMessage() drops those same tool calls from the request
Result: orphaned function_call_output without matching function_call

Proposed Fix:

In transform-messages.ts, when an assistant message has stopReason === "error", skip tracking its tool calls as pending. This prevents synthetic tool results from being generated for tool calls that will be dropped by provider-specific converters.

File: packages/ai/src/providers/transform-messages.ts

Change at line ~91: Only track tool calls when the message didn't error out. This ensures synthetic results are only created for tool calls that will actually be included in the provider request.

Why NOT to add the second fix (tracking emitted call IDs in openai-codex-responses.ts):

Adding a guard in openai-codex-responses.ts to track which call IDs were emitted would fix the immediate issue, but it's provider-specific, addresses the symptom rather than the underlying problem, and creates maintenance burden across multiple providers.

The transform-messages.ts fix is better because it's centralized across all providers, prevents the invalid state from occurring, and maintains logical consistency—if errored messages don't include tool calls, their results shouldn't be generated either.

Analysis of Issue #812: Orphaned tool_result after error causes missing call_id

Summary

When a Codex session has an assistant message with stopReason: "error", subsequent resume attempts fail with: No tool call found for function call output with call_id call_KXHLl4OkJLqXnzhwMKjeCdHX

Root Cause (verified via code tracing)

The bug is a mismatch between two code paths:

openai-codex-responses.ts:343 - convertAssistantMessage() correctly skips tool calls when stopReason === "error":

transform-messages.ts:91 - transformMessages() does NOT check stopReason when tracking tool calls for synthetic result generation:

What happens:

Session has an assistant message with stopReason: "error" containing a tool call
On resume, transformMessages() sees the tool call, tracks it as "pending"
When user message appears, it creates a synthetic tool result (lines 99-109)
Back in convertMessages():
- convertAssistantMessage() SKIPS the tool call (because stopReason === "error")
- convertToolResult() EMITS function_call_output for the synthetic result
OpenAI receives function_call_output with no matching function_call → rejection

Proposed Fix

Single change in packages/ai/src/providers/transform-messages.ts at line ~91:

typescript

// Before:const toolCalls = assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[];
// After:const toolCalls =    assistantMsg.stopReason === "error"        ? []        : (assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[]);

// Before:const toolCalls = assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[];
// After:const toolCalls =    assistantMsg.stopReason === "error"        ? []        : (assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[]);

Why this fix location is correct:

Central fix - transformMessages() is used by all providers, not just Codex
Prevents invalid state - No synthetic tool results are generated for dropped tool calls
Logically consistent - If tool calls are dropped from errored messages, their results shouldn't be created either

Why the LLM-suggested second fix (tracking emitted call IDs in openai-codex-responses.ts) is unnecessary:

The issue's LLM suggested also adding a guard in convertMessages() to track emitted call IDs. This would work but is:

Provider-specific (other providers might have similar issues)
Treating a symptom rather than the root cause
Adding complexity when a single central fix suffices

Affected Files

packages/ai/src/providers/transform-messages.ts (1 change)

ok, pleas emodify

Readtransform-messages.ts

Now I can see the exact code. I need to modify line 108 where it extracts tool calls:

to:

typescript

// Don't track tool calls from errored messages - they will be dropped by// provider-specific converters, so we shouldn't create synthetic results for themconst toolCalls =    assistantMsg.stopReason === "error"        ? []        : (assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[]);

// Don't track tool calls from errored messages - they will be dropped by// provider-specific converters, so we shouldn't create synthetic results for themconst toolCalls =    assistantMsg.stopReason === "error"        ? []        : (assistantMsg.content.filter((b) => b.type === "toolCall") as ToolCall[]);

Editedtransform-messages.ts

Now let me update the changelog:

ReadCHANGELOG.md

EditedCHANGELOG.md

Done. Changes made:

packages/ai/src/providers/transform-messages.ts

Added check for stopReason === "error" when tracking tool calls from assistant messages
Errored messages now have their tool calls excluded from pending tracking, preventing synthetic tool results from being generated for calls that will be dropped by provider converters

packages/ai/CHANGELOG.md

Added fix entry under [Unreleased]

commit and push

>cd /Users/badlogic/workspaces/pi-mono && git add packages/ai/CHANGELOG.md packages/ai/src/providers/transform-messages.ts && git commit -m "fix(ai): prevent orphaned tool results after errored assistant messages

When an assistant message has stopReason 'error', its tool calls are now
excluded from pending tool tracking. This prevents synthetic tool results
from being generated for calls that will be dropped by provider-specific
converters (e.g., Codex drops tool calls from errored messages).

Previously, this mismatch caused OpenAI to reject requests with 'No tool
call found for function call output with call_id ...' errors.

fixes #812"

Committed and pushed. Issue #812 will be automatically closed when the commit lands.

hm, are you sure this doesn't fuck with anything else? i wonder about the fact that providers have additional unfuckering. shouldn't all the unfuckering be contained in transform-messages.ts? analyze the funcukering in all providers and give me a summary of what each provider does on top of transform-messages.ts, whether we can remove some of the provider specific unfuckering, etc.

Let me analyze all providers' message conversion logic:

Readanthropic.ts

Readopenai-completions.ts

Readopenai-responses.ts

Readgoogle-shared.ts

Readamazon-bedrock.ts

Readgoogle.ts200 lines

I now have a complete picture. Let me summarize what each provider does on top of transformMessages():

Summary of Provider-Specific Message Transformations

`transformMessages()` (the central function)

Does:

Normalizes tool call IDs for Anthropic/GitHub Copilot (cross-provider compatibility)
Converts thinking blocks to plain text when switching providers (no <thinking> tags)
Inserts synthetic empty tool results for orphaned tool calls (user interrupts, assistant follows assistant)
Skips empty assistant messages (no content, no tool calls)
NEW: Excludes tool calls from errored assistant messages from pending tracking

Per-Provider Additional Transformations:

1. Anthropic (`anthropic.ts`)

Additional unfuckering:

Empty text/thinking block filtering: Skips blocks with empty or whitespace-only content
Thinking block signature handling: Converts unsigned thinking blocks to plain text (to avoid API rejection)
Tool call ID sanitization: sanitizeToolCallId() - replaces non [a-zA-Z0-9_-] chars with _
Empty user content filtering: Filters out empty string user messages
Consecutive tool results merging: Collects consecutive toolResult messages into a single user message (for z.ai Anthropic endpoint)
Cache control: Adds cache_control: { type: "ephemeral" } to last user message

Can centralize?

Empty block filtering: YES, could be done in transformMessages()
Tool call ID sanitization: Already done in transformMessages() for Anthropic targets

2. OpenAI Completions (`openai-completions.ts`)

Additional unfuckering:

Mistral tool ID normalization: normalizeMistralToolId() - exactly 9 alphanumeric chars
Content validation: Ensures assistant messages have either text or tool calls before including them
Empty text/thinking block filtering: Removes whitespace-only blocks
Thinking blocks handling: Converts to plain text or uses signature field for llama.cpp
Synthetic assistant bridge message: For providers requiring assistant after tool result (commented out, no longer needed for Mistral)
OpenRouter Anthropic caching: Adds cache_control for anthropic/* models on OpenRouter

Can centralize?

Empty block filtering: YES
Content validation: Already handled in transformMessages()
Mistral tool ID normalization: Provider-specific requirement

Some transformations are too tightly coupled to individual provider implementations. The OpenAI responses handler has additional logic for filtering thinking and tool call blocks when stopReason is "error", message ID hashing for IDs exceeding 64 characters, and tool call ID splitting using a call_id|id format. The error-based filtering duplicates what's now centralized, though it remains harmless. OpenAI Codex responses require similar unfuckering.

Google's shared utilities handle empty block filtering, validate thinking block signatures against provider/model combinations, convert unsigned function calls to text for Gemini 3, and format tool results with either { output: value } for success or error variants.

Amazon Bedrock skips empty assistant messages and filters empty text/thinking blocks. It restricts thinking signatures to Anthropic Claude models only, sanitizes tool call IDs using the same pattern as the Anthropic implementation, and merges consecutive tool results into a single user message.

Empty block filtering and tool call ID sanitization are both candidates for centralization—the sanitization logic could be extracted into transformMessages() rather than duplicated across providers. The analysis suggests that empty block filtering is particularly high-value since nearly every provider implements it, and stopReason === "error" checks for thinking and tool calls have been partially addressed but still need attention in the OpenAI response handlers.

The key insight is that while synthetic tool results are now prevented for errored calls, existing tool results in the session for errored tool calls would still be sent downstream, which means the provider-level filtering remains necessary to decide whether to include those tool calls in the converted output.

Looking at the session log from issue #812, the assistant message had stopReason: "error" with a toolCall but no corresponding result—transformMessages() created a synthetic one, which the provider then converted. My fix addresses this common scenario, though a theoretical edge case remains where someone manually adds a tool result for an errored call to the session file. The provider checks still serve as a defensive layer here.

Different providers handle tool call ID sanitization with slight variations—Anthropic and Bedrock both use [^a-zA-Z0-9_-] → _, while Mistral has its own approach with exactly 9 alphanumeric characters.

The most impactful improvement would be centralizing empty block filtering across providers. The stopReason === "error" handling is largely resolved with the current fix, though I'm noticing a potential issue in my logic that needs tracing through again.

When a session contains an assistant message with stopReason: "error" and a toolCall, the flow is: transformMessages() clears the toolCalls array at the error check, preventing synthetic tool result creation. Then in the provider's convertAssistantMessage(), the toolCall gets dropped since the stopReason check filters it out. This dual approach—central prevention plus provider-level filtering—ensures orphaned tool results don't occur.

However, I'm realizing that only some providers (like Codex) have the stopReason !== "error" check to drop tool calls. Anthropic, OpenAI Completions, and Google lack this safeguard, meaning they'd still emit tool calls from errored messages despite the central fix preventing synthetic results. Anthropic likely handles orphaned tool results gracefully or requires the matching tool call. OpenAI Completions might handle them differently. The real issue is that transformMessages() creates synthetic tool results for any orphaned tool call—whether from user interrupts, assistant-following-assistant messages, or errors. For the errored case, skipping tool call tracking prevents invalid synthetic results. But for other interruption scenarios, synthetic results remain valid since they match emitted tool call IDs. The problem only occurs when a tool call exists in an errored message and we'd create a synthetic result for it.

The fix prevents synthetic results from errored messages, while provider-specific checks drop those tool calls from output. Each provider applies additional transformations beyond the core message handling, with empty block filtering being the most common pattern that could be centralized. Defense-in-depth checks remain useful across providers, though no immediate changes are needed beyond what's already addressed.

Now I have a complete picture. Here's the analysis:

Provider-Specific Message Transformations (Beyond `transformMessages()`)

What `transformMessages()` does centrally:

Normalizes tool call IDs for Anthropic/GitHub Copilot cross-provider compatibility
Converts thinking blocks to plain text when switching providers
Inserts synthetic tool results for orphaned tool calls (user interrupts, consecutive assistants)
Skips empty assistant messages (no content, no tool calls)
NEW: Excludes tool calls from errored messages from pending tracking

1. Anthropic (`anthropic.ts`)

Transformation	Can Centralize?
Empty text/thinking block filtering (whitespace check)	YES
Unsigned thinking → plain text (no signature = API rejection)	NO (signature format is Anthropic-specific)
Tool call ID sanitization `[^a-zA-Z0-9_-]` → `_`	Already in `transformMessages()` for Anthropic targets
Consecutive toolResult merging into single user message	Could, but z.ai specific
Cache control on last user message	NO (Anthropic-specific)

2. OpenAI Completions (`openai-completions.ts`)

Transformation	Can Centralize?
Empty text/thinking block filtering	YES
Empty assistant message skip (checks content+tool_calls)	Already in `transformMessages()`
Mistral tool ID: exactly 9 alphanumeric chars	NO (Mistral-specific quirk)
Thinking blocks → text or signature field (llama.cpp)	NO (compat-specific)
OpenRouter Anthropic cache_control	NO (OpenRouter+Anthropic specific)

3. OpenAI Responses (`openai-responses.ts`)

Transformation	Can Centralize?
Skip thinking/toolCall when `stopReason === "error"`	See analysis below
Message ID hashing for IDs > 64 chars	NO (OpenAI Responses specific)
Tool call ID format `call_id\|id` splitting	NO (OpenAI Responses specific)

4. OpenAI Codex Responses (`openai-codex-responses.ts`)

5. Google Shared (`google-shared.ts`)

Transformation	Can Centralize?
Empty text/thinking block filtering	YES
Thinking signature validation (base64, same provider)	NO (Google signature format)
Unsigned Gemini 3 tool calls → descriptive text	NO (Gemini 3 specific)
Tool result format `{output}` vs `{error}`	NO (Gemini specific)
Function responses merging (Cloud Code Assist)	Could, but provider specific

6. Amazon Bedrock (`amazon-bedrock.ts`)

Transformation	Can Centralize?
Empty assistant message skip	Already in `transformMessages()`
Empty text/thinking block filtering	YES
Thinking signature only for Anthropic Claude	NO (model-specific)
Tool call ID sanitization	Could reuse Anthropic's
Consecutive toolResult merging	Could, similar to Anthropic

Analysis: The `stopReason === "error"` Situation

Current state after my fix:

Provider	Has `stopReason !== "error"` check for toolCall?	Has check for thinking?
OpenAI Responses	YES	YES
OpenAI Codex	YES	YES
Anthropic	NO	NO
OpenAI Completions	NO	NO
Google	NO	NO
Bedrock	NO	NO

Why this is correct:

OpenAI Responses/Codex require matching function_call → function_call_output pairs. They explicitly drop tool calls from errored messages, so we must not create synthetic results for them. My fix + their check = correct.
Other providers (Anthropic, OpenAI Completions, Google, Bedrock) don't have this requirement. They include tool calls from errored messages, and if there's a result (synthetic or real), it matches. No orphan problem.

The fix is correct and sufficient. The provider-specific checks in Responses/Codex are defense-in-depth.

Recommendations

1. Centralize empty block filtering (HIGH VALUE)

Almost every provider filters empty text/thinking blocks. Add to transformMessages():

typescript

// In the assistant message content transformationconst transformedContent = assistantMsg.content.flatMap((block) => {    // Skip empty text blocks    if (block.type === "text" && (!block.text || block.text.trim() === "")) return [];    // Skip empty thinking blocks      if (block.type === "thinking" && (!block.thinking || block.thinking.trim() === "")) return [];    // ... rest of transformation});

// In the assistant message content transformationconst transformedContent = assistantMsg.content.flatMap((block) => {    // Skip empty text blocks    if (block.type === "text" && (!block.text || block.text.trim() === "")) return [];    // Skip empty thinking blocks      if (block.type === "thinking" && (!block.thinking || block.thinking.trim() === "")) return [];    // ... rest of transformation});

2. Leave provider-specific checks in place

The stopReason !== "error" checks in Responses/Codex serve as defense-in-depth. They're now somewhat redundant for synthetic results (central fix handles that), but they still protect against:

Manually edited session files with tool results for errored calls
Thinking blocks from errored messages (no valid signature)

3. Consider centralizing toolResult merging

Anthropic, Bedrock, and Google all merge consecutive toolResult messages. Could be done centrally, but low priority since it works.

Bottom line: The fix is correct. The provider-specific "unfuckering" serves different purposes and mostly can't be centralized due to provider quirks. The one big win would be centralizing empty block filtering.

Summary

Analysis of Issue #812: Orphaned tool_result after error causes missing call_id

Summary

Root Cause (verified via code tracing)

What happens:

Proposed Fix

Why this fix location is correct:

Why the LLM-suggested second fix (tracking emitted call IDs in openai-codex-responses.ts) is unnecessary:

Affected Files

Provider-Specific Message Transformations (Beyond transformMessages())

What transformMessages() does centrally:

1. Anthropic (anthropic.ts)

2. OpenAI Completions (openai-completions.ts)

3. OpenAI Responses (openai-responses.ts)

4. OpenAI Codex Responses (openai-codex-responses.ts)

5. Google Shared (google-shared.ts)

6. Amazon Bedrock (amazon-bedrock.ts)

Analysis: The stopReason === "error" Situation

Recommendations

1. Centralize empty block filtering (HIGH VALUE)

2. Leave provider-specific checks in place

3. Consider centralizing toolResult merging

Provider-Specific Message Transformations (Beyond `transformMessages()`)

What `transformMessages()` does centrally:

1. Anthropic (`anthropic.ts`)

2. OpenAI Completions (`openai-completions.ts`)

3. OpenAI Responses (`openai-responses.ts`)

4. OpenAI Codex Responses (`openai-codex-responses.ts`)

5. Google Shared (`google-shared.ts`)

6. Amazon Bedrock (`amazon-bedrock.ts`)

Analysis: The `stopReason === "error"` Situation