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Chore: Format and cleanup code
- Apply code formatting standards. - Add documentation files (ANTHROPIC_IMPLEMENTATION.md, IMPLEMENTATION_SUMMARY.md). - Include test-anthropic-format.js for verification.
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‎ANTHROPIC_IMPLEMENTATION.md‎

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# Anthropic API Format Support Implementation
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## Summary
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Successfully implemented proper Anthropic Messages API format support to fix the broken system message injection. The implementation now correctly handles Anthropic's unique top-level `system` array format.
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## Changes Made
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### 1. Created `lib/fetch-wrapper/formats/anthropic.ts`
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Implements the `FormatDescriptor` interface with Anthropic-specific handling:
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#### Detection Logic
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```typescript
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detect(body: any): boolean {
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return (
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body.system !== undefined &&
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Array.isArray(body.messages)
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)
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}
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```
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- Checks for `body.system` (can be string or array) at the top level
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- Requires `body.messages` array
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- Distinguishes from OpenAI (no top-level system) and Bedrock (has inferenceConfig)
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#### System Message Injection
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```typescript
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injectSystemMessage(body: any, injection: string): boolean {
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// Converts string system to array if needed
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if (typeof body.system === 'string') {
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body.system = [{ type: 'text', text: body.system }]
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} else if (!Array.isArray(body.system)) {
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body.system = []
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}
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// Appends injection as text block
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body.system.push({ type: 'text', text: injection })
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return true
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}
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```
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- Handles both string and array system formats
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- Converts string to array of text blocks automatically
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- Appends to top-level `body.system` array (NOT in messages)
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#### Tool Output Extraction
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```typescript
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extractToolOutputs(data: any[], state: PluginState): ToolOutput[] {
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// Looks for role='user' messages with type='tool_result' blocks
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// Uses tool_use_id field (Anthropic-specific)
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}
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```
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- Searches user messages for `type: 'tool_result'` content blocks
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- Uses `tool_use_id` field (not `tool_call_id`)
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- Normalizes IDs to lowercase for consistency
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#### Tool Output Replacement
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```typescript
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replaceToolOutput(data: any[], toolId: string, prunedMessage: string): boolean {
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// Replaces content field in tool_result blocks
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return {
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...block,
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content: prunedMessage // Direct string replacement
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}
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}
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```
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- Finds matching `tool_result` blocks by `tool_use_id`
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- Replaces the `content` field with pruned message
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- Preserves other block properties (is_error, cache_control, etc.)
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### 2. Updated `lib/fetch-wrapper/formats/index.ts`
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```typescript
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export { anthropicFormat } from './anthropic'
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```
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Added export for the new Anthropic format descriptor.
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### 3. Updated `lib/fetch-wrapper/index.ts`
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#### Import Statement
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```typescript
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import { openaiChatFormat, openaiResponsesFormat, geminiFormat, bedrockFormat, anthropicFormat } from "./formats"
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```
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#### Detection Chain Order (CRITICAL)
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```typescript
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// 1. OpenAI Responses API: has body.input (not body.messages)
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if (openaiResponsesFormat.detect(body)) { ... }
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// 2. Bedrock: has body.system + body.inferenceConfig + body.messages
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else if (bedrockFormat.detect(body)) { ... }
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// 3. Anthropic: has body.system + body.messages (no inferenceConfig)
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else if (anthropicFormat.detect(body)) { ... }
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// 4. OpenAI Chat: has body.messages (no top-level system)
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else if (openaiChatFormat.detect(body)) { ... }
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// 5. Gemini: has body.contents
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else if (geminiFormat.detect(body)) { ... }
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```
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**Why Order Matters:**
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- `anthropicFormat` MUST come before `openaiChatFormat`
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- Both have `body.messages`, but Anthropic has `body.system` at top level
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- Without proper ordering, Anthropic requests would be incorrectly handled by OpenAI format
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- Bedrock comes before Anthropic because it has more specific fields (inferenceConfig)
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### 4. OpenAI Format Compatibility
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The existing `openaiChatFormat` has fallback handling for `tool_result` blocks (lines 42-52 in `openai-chat.ts`). This is preserved for:
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- Backward compatibility with hybrid providers
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- Edge cases where providers use mixed formats
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- The detection order ensures true Anthropic requests are caught first
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## Key Differences: Anthropic vs OpenAI
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| Feature | OpenAI | Anthropic |
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|---------|--------|-----------|
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| System location | In messages array | Top-level `system` field |
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| System format | `{role: "system", content: "..."}` | String or array of blocks |
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| Tool results | `role: "tool"` message | In `user` message with `type: "tool_result"` |
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| Tool ID field | `tool_call_id` | `tool_use_id` |
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| Message roles | system/user/assistant/tool | user/assistant only |
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## Testing
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Successfully compiled with TypeScript:
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```bash
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npm run build # ✓ No errors
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```
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Generated outputs:
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- `dist/lib/fetch-wrapper/formats/anthropic.js`
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- `dist/lib/fetch-wrapper/formats/anthropic.d.ts`
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- Properly exported in `dist/lib/fetch-wrapper/formats/index.js`
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- Integrated into main wrapper in `dist/lib/fetch-wrapper/index.js`
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## Verification Points
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1. ✅ Format detection distinguishes Anthropic from OpenAI (checks `body.system`)
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2. ✅ System injection appends to top-level array (not messages)
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3. ✅ Handles both string and array system formats
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4. ✅ Tool extraction uses `tool_use_id` (Anthropic convention)
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5. ✅ Tool replacement targets `tool_result` blocks in user messages
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6. ✅ Detection order prevents OpenAI format from capturing Anthropic requests
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7. ✅ Log metadata tags with `format: 'anthropic'`
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8. ✅ TypeScript compilation successful
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## References
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- Documentation: `docs/providers/anthropic.md`
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- Similar pattern: `lib/fetch-wrapper/formats/bedrock.ts` (also uses top-level system array)
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- Official API: https://docs.anthropic.com/en/api/messages
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## Impact
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This fix resolves the issue where Anthropic requests were being incorrectly processed by the OpenAI format handler, which tried to inject system messages into the messages array instead of the top-level system field. The new implementation:
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- Properly injects pruning context into Anthropic's system array
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- Correctly identifies and replaces pruned tool outputs
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- Maintains separation between format handlers
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- Preserves backward compatibility with existing OpenAI handling

‎IMPLEMENTATION_SUMMARY.md‎

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# Anthropic API Support - Implementation Complete ✅
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## What Was Fixed
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The Anthropic Messages API format was incorrectly handled by the OpenAI Chat format adapter, causing system message injections to fail. Anthropic uses a **top-level `system` field** (string or array), while OpenAI uses `role: 'system'` messages within the messages array.
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## Files Changed
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### 1. **Created:** `lib/fetch-wrapper/formats/anthropic.ts`
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- Full implementation of `FormatDescriptor` interface
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- Detects `body.system` + `body.messages` (distinguishes from OpenAI)
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- Injects into top-level `body.system` array (handles string-to-array conversion)
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- Extracts tool outputs from `role: 'user'` messages with `type: 'tool_result'` blocks
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- Uses `tool_use_id` field (Anthropic convention, not `tool_call_id`)
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- Replaces pruned tool results with shortened message
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### 2. **Updated:** `lib/fetch-wrapper/formats/index.ts`
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```typescript
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export { anthropicFormat } from './anthropic' // Added
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```
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### 3. **Updated:** `lib/fetch-wrapper/index.ts`
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- Imported `anthropicFormat`
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- Added detection check **before** `openaiChatFormat` (critical ordering)
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- Detection chain order:
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1. OpenAI Responses (body.input)
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2. Bedrock (body.system + inferenceConfig)
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3. **Anthropic (body.system + messages)** ← New
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4. OpenAI Chat (messages only)
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5. Gemini (body.contents)
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## Technical Details
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### Anthropic Format Characteristics
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```typescript
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// Request structure
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{
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"system": "string" | [{"type": "text", "text": "...", "cache_control": {...}}],
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "tool_result", "tool_use_id": "toolu_123", "content": "..."}
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]
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}
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]
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}
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```
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### Key Implementation Points
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1. **Detection**: Checks `body.system !== undefined` to distinguish from OpenAI
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2. **System Injection**: Converts string system to array, then appends text block
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3. **Tool IDs**: Uses `tool_use_id` (not `tool_call_id`)
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4. **Tool Results**: Found in `user` messages with `type: 'tool_result'` (not separate `tool` role)
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5. **Order Matters**: Must detect before OpenAI format (both have `messages`)
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## Build & Verification
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```bash
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npm run build # ✅ Success
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```
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Generated files:
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- `dist/lib/fetch-wrapper/formats/anthropic.js`
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- `dist/lib/fetch-wrapper/formats/anthropic.d.ts`
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- `dist/lib/fetch-wrapper/formats/anthropic.js.map`
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- `dist/lib/fetch-wrapper/formats/anthropic.d.ts.map`
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Verification:
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- ✅ TypeScript compilation successful
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- ✅ Format exported in index
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- ✅ Imported and used in main wrapper
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- ✅ Correct detection order (before OpenAI)
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- ✅ All methods implemented correctly
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## Testing Recommendations
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To verify in production:
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1. Use an Anthropic model (Claude)
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2. Execute multiple tool calls
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3. Verify system message shows prunable tools list
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4. Confirm pruned tool outputs are replaced in API requests
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5. Check logs for `format: 'anthropic'` metadata
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## References
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- Anthropic API docs: `docs/providers/anthropic.md`
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- Similar implementation: `lib/fetch-wrapper/formats/bedrock.ts`
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- Official API: https://docs.anthropic.com/en/api/messages
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## Impact
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- ✅ Fixes broken system message injection for Anthropic API
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- ✅ Properly handles tool result pruning
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- ✅ Maintains backward compatibility with other formats
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- ✅ No changes needed to existing OpenAI/Gemini/Bedrock handlers

‎lib/fetch-wrapper/formats/anthropic.ts‎

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name: 'anthropic',
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detect(body: any): boolean {
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// Anthropic has top-level `system` field (can be string or array) AND messages array
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// This distinguishes it from OpenAI (no top-level system) and Bedrock (has inferenceConfig)
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return (
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body.system !== undefined &&
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Array.isArray(body.messages)
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injectSystemMessage(body: any, injection: string): boolean {
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if (!injection) return false
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// Anthropic system can be:
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// 1. A string: "You are a helpful assistant"
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// 2. An array of blocks: [{"type": "text", "text": "...", "cache_control": {...}}]
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// Convert to array if needed
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if (typeof body.system === 'string') {
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body.system = [{ type: 'text', text: body.system }]
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} else if (!Array.isArray(body.system)) {
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body.system = []
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}
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// Append the injection as a text block
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body.system.push({ type: 'text', text: injection })
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return true
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},
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const outputs: ToolOutput[] = []
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for (const m of data) {
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// Tool results are in user messages with type='tool_result'
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if (m.role === 'user' && Array.isArray(m.content)) {
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for (const block of m.content) {
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if (block.type === 'tool_result' && block.tool_use_id) {
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const newContent = m.content.map((block: any) => {
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if (block.type === 'tool_result' && block.tool_use_id?.toLowerCase() === toolIdLower) {
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messageModified = true
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// Anthropic tool_result content can be string or array of content blocks
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// Replace with simple string
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return {
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...block,
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content: prunedMessage

‎lib/fetch-wrapper/formats/bedrock.ts‎

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injectSystemMessage(body: any, injection: string): boolean {
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if (!injection) return false
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// Bedrock uses top-level system array with text blocks
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if (!Array.isArray(body.system)) {
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body.system = []
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}
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body.system.push({ text: injection })
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return true
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},

‎lib/fetch-wrapper/formats/gemini.ts‎

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injectSystemMessage(body: any, injection: string): boolean {
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if (!injection) return false
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// Gemini uses systemInstruction.parts array for system content
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if (!body.systemInstruction) {
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body.systemInstruction = { parts: [] }
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}
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if (!Array.isArray(body.systemInstruction.parts)) {
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body.systemInstruction.parts = []
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}
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body.systemInstruction.parts.push({ text: injection })
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return true
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},

‎lib/fetch-wrapper/formats/openai-chat.ts‎

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injectSystemMessage(body: any, injection: string): boolean {
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if (!injection || !body.messages) return false
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// Find the last system message index to insert after it
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let lastSystemIndex = -1
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for (let i = 0; i < body.messages.length; i++) {
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if (body.messages[i].role === 'system') {
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lastSystemIndex = i
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}
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}
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// Insert after the last system message, or at the beginning if none exist
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const insertIndex = lastSystemIndex + 1
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body.messages.splice(insertIndex, 0, { role: 'system', content: injection })
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return true

‎lib/fetch-wrapper/formats/openai-responses.ts‎

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injectSystemMessage(body: any, injection: string): boolean {
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if (!injection) return false
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// OpenAI Responses API uses top-level `instructions` for system content
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// Append to existing instructions if present
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if (body.instructions && typeof body.instructions === 'string') {
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body.instructions = body.instructions + '\n\n' + injection
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} else {

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