Break an Agent task down with structured prompting

One-sentence takeaway

Google's prompting guide provides Gemini 3 Flash with a reusable structured-prompting and Agent workflow: separate roles, constraints, context, tasks, and output formats; plan before executing; and validate the results. It can serve as an official starting template for Gemini 3.8 Flash, but the page provides no 3.8-specific success-rate or parameter guarantees.

Use cases

• Suitable tasks: Extraction, summarization, code analysis, and knowledge Q&A that require stable output formats, as well as Agents that need planning, tool execution, and result validation.

• Unsuitable tasks: Treating the template as an automatic authorization mechanism or a guarantee of factual accuracy, or using it to directly replace tool permissions, human confirmation, and business acceptance.

• Applicable model version: The target model in this article is Google's API gemini-3.8-flash. The original page has a dedicated section titled Gemini 3 Flash strategies, while its navigation also shows “Gemini 3.8 Flash is now available,” so it is selected as the official prompting starting point for 3.8 Flash; this is not an independent evaluation of a 3.8 model snapshot.

• Applicable client, Agent, or API: The prompting-design context of the Gemini API on Google AI for Developers. Third-party clients, IDE Agents, or orchestration frameworks need to map system instructions, tool permissions, and stop conditions themselves.

• Parameter notes: This page does not specify a model ID, sampling parameters, or tool schema; do not infer these configurations from the template.

Ready-to-use content

1. Official Gemini 3 Flash strategy snippets

The following three snippets are the original templates provided by the page's Gemini 3 Flash strategies section, ready to be combined into a system instruction. The date year should be replaced by the application at runtime:

# Current-day accuracy
For time-sensitive user queries that require up-to-date information, you
MUST follow the provided current time (date and year) when formulating
search queries in tool calls. Remember it is 2026 this year.

# Knowledge-cutoff accuracy
Your knowledge cutoff date is January 2025.

# Strict grounding (use only for closed-book tasks)
You are a strictly grounded assistant limited to the information provided in
the User Context. In your answers, rely only on the facts that are directly
mentioned in that context. You must not access or utilize your own knowledge
or common sense to answer. Do not assume or infer from the provided facts;
simply report them exactly as they appear. Your answer must be factual and
fully truthful to the provided text, leaving absolutely no room for
speculation or interpretation. Treat the provided context as the absolute
limit of truth; any facts or details that are not directly mentioned in the
context must be considered completely untruthful and completely unsupported.
If the exact answer is not explicitly written in the context, you must state
that the information is not available.

2. Structured prompting template (official example adapted for 3.8 Flash)

The official page uses XML or Markdown tags to distinguish instructions, context, and tasks, and provides a combined template of “role → instructions → constraints → output format → user context/task.” The only change below is the model tag from the official example to the target version; the remaining fields are retained as replaceable placeholders:

System Instruction:

<role>
You are Gemini 3.8 Flash, a specialized assistant for [domain].
You are precise, analytical, and persistent.
</role>

<instructions>
1. Plan: analyze the task and create a step-by-step plan.
2. Execute: carry out the plan.
3. Validate: review your output against the user's task.
4. Format: present the final answer in the requested structure.
</instructions>

<constraints>
- Verbosity: [low / medium / high]
- Tone: [formal / casual / technical]
- Permissions: [what the agent may read, write, call, or ask permission for]
- Evidence: [required sources or context; say “not available” when absent]
</constraints>

<output_format>
1. Executive Summary: [short overview]
2. Detailed Response: [main content]
3. Validation: [checks performed and unresolved issues]
</output_format>

User Prompt:

<context>
[Insert relevant documents, code, tool results, or background information]
</context>

<task>
[Insert the specific user request here]
</task>

<final_instruction>
Use the context and constraints above. Think through the task before
answering, but return only the requested result and validation fields.
</final_instruction>

3. Agent workflow

Put the three dimensions of the page's Agentic workflows into a minimal closed loop:

1. Reason and plan
   - Decompose dependencies, prerequisites, constraints, and operation order.
   - Diagnose failures beyond the first obvious cause.
   - Decide how exhaustive the information search must be.

2. Execute reliably
   - Adapt the plan when observations contradict assumptions.
   - Retry transient errors within an explicit limit; change strategy for other errors.
   - Distinguish low-risk reads from high-risk writes and request permission when needed.

3. Interact and return
   - Ask for clarification when ambiguity changes the action or its risk.
   - Set verbosity explicitly and meet the required precision/completeness.
   - Validate against the task, then return the requested format plus unresolved issues.

Google also notes that the Gemini 2.5 and Gemini 3 series automatically produce internal thinking text; for complex tasks, a brief “Think very hard before answering” prompt can strengthen reasoning, but it increases thinking tokens, and normally there is no need to require the model to output its thought process verbatim.

Testing/workflow steps

1. Fill the template with the domain, permissions, evidence requirements, and output fields; do not mix the user's original text directly into the rules section of the system instruction.

2. For long documents, codebases, or long videos, put the context first and the specific question after the context, beginning with “Based on the information above.”

3. Add the runtime current date to date-sensitive tasks; when knowledge is not current enough, use a configured grounding tool rather than hard-coding the current date as a long-lived fact.

4. Enable strict grounding only for closed-book extraction/compliance summaries; open-ended Q&A should not mistakenly use the restriction “use only the User Context.”

5. Run a representative set of tasks and check at least: rule following, tool/permission boundaries, format compliance, evidence coverage, failure recovery, and token/latency cost.

6. Compare results from the “basic prompt” and “structured template” groups, retaining the complete inputs, tool calls, validation outputs, and human handoff points; do not use the model's self-reported “completed” as acceptance.

Original evidence and data

Applicability boundaries

• The original page's main text targets Gemini 3 / Gemini 3 Flash and does not publish dedicated prompt comparison experiments, datasets, success rates, model snapshots, or confidence intervals for gemini-3.8-flash; this article's 3.8 adaptation is a usage mapping based on the official page context, not an independent evaluation conclusion.

• “Gemini 3 reasons automatically” does not imply a fixed number of reasoning tokens, latency, or quality; whether it improves a task must be verified with your own harness regression tests.

• The strict-grounding template prohibits common-sense completion and inference; when the context is incomplete, explicitly return that the information is unavailable rather than using it for tasks requiring open-world knowledge.

• “Remember it is 2026 this year.” is the example's collection-time year; production implementations should inject the real date to prevent the year from becoming outdated.

• Planning, retry, and risk rules cannot replace application-layer tool allowlists, permission controls, audit logs, write confirmations, and human handoffs.

• The page examples are in English; Chinese output, tag naming, tool schemas, and client fields need separate testing in the target API/Agent.

Source excerpt or observation (short excerpt for compliance only)

Google's central reminder is: “Gemini 3 is a reasoning model. This changes how you should prompt.” Its practical advice is not to increase prompt length without limit, but to iterate with clear tasks, structured context, explicit constraints, and a verifiable Agent loop.