Claude Certified Developer - Foundations flashcards

32 cards. Read the term and the definition here. The deck at the top of this page is optional.

max_tokens parameter

Required field in every Messages API request that caps how many output tokens Claude may generate; reaching the cap yields stop_reason "max_tokens" and a truncated response.

System parameter

Top-level request field carrying persona, role, and standing rules. It is separate from the messages array and has no role attribute of its own.

stop_reason field

Response field naming why generation ended: end_turn for natural completion, max_tokens for truncation, stop_sequence for a matched sequence, and tool_use when Claude requests a tool.

count_tokens endpoint

POST /v1/messages/count_tokens returns the input token count a prospective request would use, without generating output, for budgeting and context-window checks.

Streaming event sequence

With stream enabled, the API emits server-sent events in order: message_start, content_block_start, content_block_delta, content_block_stop, message_delta, and message_stop.

Messages array roles

The messages array accepts only the roles "user" and "assistant"; turns conventionally alternate, and adjacent entries with the same role are combined into one turn.

Prefilled assistant turn

Placing an opening fragment in a final assistant message forces Claude to continue from that text, locking output format and suppressing conversational preamble.

XML tag structuring

Wrapping instructions, documents, and examples in consistently named, fully closed tags such as <document> or <example> lets Claude separate prompt sections reliably.

Few-shot examples

Several diverse input-output pairs embedded in the prompt that demonstrate the exact target format and edge-case handling; three to five well-chosen examples usually suffice.

Long-context document ordering

Placing large documents near the top of the prompt and the question at the end improves answer quality, reportedly by up to roughly thirty percent.

Prompt chaining

Splitting a complex task into sequential model calls where each prompt consumes the previous output, trading extra latency for accuracy when one prompt covers too many steps.

tool_choice auto versus any

auto lets Claude decide whether to call a tool; any forces at least one call; tool with a name forces that specific tool; none forbids tool use entirely.

tool_use content block

Block in an assistant response containing id, name, and input for a requested tool call; it appears when the response stop_reason equals tool_use.

tool_result block

User-message block returning a tool's output, matched to the request by tool_use_id, with an is_error flag for failures; all results ship in one message.

Tool input_schema

JSON Schema object describing a tool's parameters, using type "object" with a properties map and required list; it constrains the input Claude generates for the call.

Tool name constraints

Tool names must be unique within a request, at most sixty-four characters long, and composed only of letters, digits, underscores, and hyphens.

Agent loop

Repeated cycle of observing results, deciding the next action, executing a tool call, and observing again, terminated by a stop condition or an iteration cap.

Orchestrator-worker pattern

A lead model call decomposes the task, dispatches independent subtasks to worker calls, then merges their outputs into a single synthesized answer.

Evaluator-optimizer pattern

One model call produces a draft while a second critiques it against explicit criteria; the loop repeats until the critique passes or the budget is exhausted.

Routing pattern

A cheap classification call labels the incoming input, and that label selects which specialized prompt, toolset, or model tier handles the request.

cache_control ephemeral

Per-block marker that designates a prompt prefix as cacheable; up to four breakpoints are allowed, and the prefix must match exactly to produce a cache hit.

Cache pricing multipliers

Writing a cached prefix costs about 1.25 times base input token price, while reading it costs about 0.1 times, so reuse roughly twice to break even.

Minimum cacheable length

Prompts shorter than 1024 tokens on Opus and Sonnet class models, or 2048 tokens on Haiku class models, are not cached even when marked.

Cache prefix ordering

The cacheable prefix is evaluated in the order tools, then system, then messages; editing anything earlier in that order invalidates all later cached content.

Retrieval augmented prompting

Chunk and embed a corpus, retrieve the top matching passages, optionally rerank them for relevance, and place them before the question as quoted context.

LLM as judge

Using a model to grade outputs. Pairwise comparisons are more reliable than absolute numeric scores, and the judge must be validated against human labels before trusting it.

Grading ladder

Order of preference for automated checks: deterministic code assertions first, model-based judges for open-ended output, and human review for calibrating both.

Prompt versioning

Storing prompts and eval sets under version control so any quality change can be attributed to a specific edit and cleanly rolled back.

Truncation rate metric

Share of production responses ending with stop_reason max_tokens; a rising rate signals max_tokens set too low or prompts demanding overly long output.

Constitutional AI

Training approach in which the model critiques and revises its own outputs against a written set of principles, generating preference data used for alignment.

AI Safety Levels

Tiered framework in Anthropic's Responsible Scaling Policy that pairs capability thresholds with required security and deployment safeguards before a model is released.

Prompt injection defense

Treating retrieved documents and tool outputs as untrusted data, delimiting them clearly, and never letting their text override system instructions or grant new capabilities.