Patterns

SuspendedAction -> ExecutionPermission

Halt thread execution of an active agent action until an external operator approves or rejects the action via API.

AgentYAML -> AgentNetwork

Construct an operational multi-agent collaboration network by parsing a declarative YAML configuration specifying roles, models, and tool bindings.

EnvironmentState -> SystemContext

Inspect the local system's environment variables, OS type, default shell, and active working directory to construct an LLM system prompt.

MediaBuffer -> MediaBufferWithMetadata

Execute deep-learning inference models on a specified hardware accelerator (CPU, GPU, or NPU) directly inside a real-time streaming pipeline.

ToolCall -> ExecutionResult

Intercept agentic tool execution requests parsed from LLM completions, executing them on the system only after explicit user confirmation.

PromptQuery -> CachedResponse

Retrieve cached answers for incoming queries by comparing prompt embedding similarity against a vector database threshold.

HarnessComponents + StructuredAnalysisReport -> MutatedHarnessComponents

Propose and apply git-tracked file-level mutations to modular harness components (prompts, tools, and middleware) based on structured failure evidence.

MelSpectrogram -> AudioWaveform

Reconstruct time-domain audio waveforms from mel-spectrograms using a generative adversarial network.

PhonemeSequence -> MelSpectrogram

Predict mel-spectrogram frames from phoneme sequences using a transformer-based acoustic model.

UnlabeledVideo -> List<HighUncertaintyFrame>

Select video frames with the highest model tracking uncertainty to prioritize for manual human annotation.

Image -> List<PoseKeypoints>

Detect all candidate keypoints globally across an image and group them into distinct instances using spatial affinity scores.

Image -> List<PoseKeypoints>

Detect individual object bounding boxes first, then estimate keypoints inside each isolated bounding box.

BrowserRuntimeState -> PromptContext

Inject live browser console logs and debugger stack traces into an LLM context window to guide troubleshooting.

TaskPrompt -> List<SubAgentResult>

Decompose a complex parent prompt into parallel child-agent subtasks and aggregate their outputs back into the primary thread.

RawTranscription -> RichTranscription

Parse and structure metadata tags (e.g., laughter, coughing, bgm) from the raw model-generated token sequence into user-friendly text.

(AudioSignal, Text) -> TranscriptWithTimestamps

Align generated textual tokens to precise audio time intervals using connectionist temporal classification boundary mappings.

List<SpendRequest> -> Stream<SpendResult>

Queue concurrent asset-spending operations sequentially to prevent local transaction race conditions and double-spend conflicts.

UserQuery -> MCPToolPayload

Expose catalog schema registry queries as callable tools via the Model Context Protocol.

ShortPrompt -> DenseStructuredPrompt

Expand short scene descriptions into dense, structured, spatial-temporally rich prompts using an LLM prior to video/image generation.

Tensor[Tokens] -> Tensor[PositionEncodedTokens]

Encode spatial, temporal, and modal structures by applying a unified 3D rotary position embedding to mixed-modality tokens.

MultimodalTokens -> MultimodalTokens

Route reasoning tasks through causal self-attention and multimodal generation tasks through full-attention denoising within a shared transformer backbone.

Audio -> TranscriptWithSpeakerLabels

Segment audio using voice activity detection (FSMN-VAD), extract speaker embeddings via verification models (CAM++), transcribe audio with ASR, and align outputs to produce punctuated, speaker-attributed transcripts.