Processing boundary
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Prompt tools
Prompt Boundary & Delimiter Builder
Wraps user or RAG text in generated delimiters and produces a template that tells a model to treat enclosed content as data, with allowed and forbidden behavior. It does not stop prompt injection by itself.
✓ Free✓ No account✓ In-browser
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What does this tool do?
Build explicit data boundaries that separate untrusted content from instructions. Prompt Boundary & Delimiter Builder limitation: Rule-based review does not prove real model behavior; retest with representative cases.
- Input
- For Prompt Boundary & Delimiter Builder, provide iNI or properties text with valid sections, keys, and values. The requested outcome is to build explicit data boundaries that separate untrusted content from instructions.
- Output
- When Prompt Boundary & Delimiter Builder finishes, it returns a parsed structure, field metrics, and explicit syntax findings, organised around the goal to build explicit data boundaries that separate untrusted content from instructions.
- Method
- Prompt Boundary & Delimiter Builder uses this disclosed method to build explicit data boundaries that separate untrusted content from instructions: parsing uses deterministic rules that preserve field and type boundaries.
- Verification
- Before accepting a Prompt Boundary & Delimiter Builder result, complete field names, value types, escaping, and empty or null values compared with the source; the evidence should support the goal to build explicit data boundaries that separate untrusted content from instructions.
TOOL-SPECIFIC RUN PLANPrompt Boundary & Delimiter Builder: Input and result guideOpen the format, method, and acceptance check when needed+
See exactly what Prompt Boundary & Delimiter Builder expects and returns
Prompt Boundary & Delimiter Builder uses the contract below to complete “Separating RAG content from instructions: local analysis with Prompt Boundary & Delimiter Builder” in particular. Confirm the shape with the example first; use real data only when the fields and expected result are clear.
- Use this shape
1 · Prepare the input
Prompt Boundary & Delimiter Builder — For Prompt Boundary & Delimiter Builder, provide iNI or properties text with valid sections, keys, and values. The requested outcome is to build explicit data boundaries that separate untrusted content from instructions.. Paste the content to process. Expected format for Prompt Boundary & Delimiter Builder: For Prompt Boundary & Delimiter Builder, provide iNI or properties text with valid sections, keys, and values. The requested outcome is to build explicit data boundaries that separate untrusted content from instructions..
- Method applied
2 · Run the operation
Prompt Boundary & Delimiter Builder — Prompt Boundary & Delimiter Builder uses this disclosed method to build explicit data boundaries that separate untrusted content from instructions: parsing uses deterministic rules that preserve field and type boundaries. Generate the local template and review its boundaries. Prompt Boundary & Delimiter Builder applies this method: Prompt Boundary & Delimiter Builder uses this disclosed method to build explicit data boundaries that separate untrusted content from instructions: parsing uses deterministic rules that preserve field and type boundaries.
- Expected output
3 · Read the result
Prompt Boundary & Delimiter Builder — When Prompt Boundary & Delimiter Builder finishes, it returns a parsed structure, field metrics, and explicit syntax findings, organised around the goal to build explicit data boundaries that separate untrusted content from instructions.. Isolating user text as data: validating the Prompt Boundary & Delimiter Builder output
- Acceptance check
4 · Accept or correct
Prompt Boundary & Delimiter Builder — Before accepting a Prompt Boundary & Delimiter Builder result, complete field names, value types, escaping, and empty or null values compared with the source; the evidence should support the goal to build explicit data boundaries that separate untrusted content from instructions.. Test separately with role separation and allowlists on the real model. Acceptance check for Prompt Boundary & Delimiter Builder: Before accepting a Prompt Boundary & Delimiter Builder result, complete field names, value types, escaping, and empty or null values compared with the source; the evidence should support the goal to build explicit data boundaries that separate untrusted content from instructions..
A tool-specific example path
1. Separating RAG content from instructions: local analysis with Prompt Boundary & Delimiter Builder → 2. Isolating user text as data: validating the Prompt Boundary & Delimiter Builder output → 3. Standardizing prompt reviews: checking the limits of Prompt Boundary & Delimiter Builder
Tip: when an example-data button is available, run it first. Do not use the result in a live process unless it passes the acceptance check.
Persistent storage
Input and output are not stored. The optional usage counter keeps only tool identity and count, never content.
Verification
Output comes from disclosed rules or browser APIs and needs independent review before high-impact use.
APPLICATION AND DECISION GUIDE
✓ REVIEWEDUse Prompt Boundary & Delimiter Builder with the right input, acceptance check, and next step
Wraps user or RAG text in generated delimiters and produces a template that tells a model to treat enclosed content as data, with allowed and forbidden behavior. It does not stop prompt injection by itself. The notes below help you do more than produce a result: they show how to test whether Prompt Boundary & Delimiter Builder fits the task and when to stop before a weak output travels further.
Prompt Boundary & Delimiter Builder uses this disclosed method to build explicit data boundaries that separate untrusted content from instructions: parsing uses deterministic rules that preserve field and type boundaries. Goal, context, output contract, and conflicting constraints are inspected separately. The tool runs no language model and applies only visible rules.
For Prompt Boundary & Delimiter Builder, provide iNI or properties text with valid sections, keys, and values. The requested outcome is to build explicit data boundaries that separate untrusted content from instructions. Confirm the shape first with a small example containing no personal data.
When Prompt Boundary & Delimiter Builder finishes, it returns a parsed structure, field metrics, and explicit syntax findings, organised around the goal to build explicit data boundaries that separate untrusted content from instructions. — Before accepting a Prompt Boundary & Delimiter Builder result, complete field names, value types, escaping, and empty or null values compared with the source; the evidence should support the goal to build explicit data boundaries that separate untrusted content from instructions.
Three practical use cases
Separating RAG content from instructions: local analysis with Prompt Boundary & Delimiter Builder
Action: Start with a small synthetic fixture that represents this need. Expected input: For Prompt Boundary & Delimiter Builder, provide iNI or properties text with valid sections, keys, and values. The requested outcome is to build explicit data boundaries that separate untrusted content from instructions..
Acceptance signal: The fixture should reproduce “Separating RAG content from instructions: local analysis with Prompt Boundary & Delimiter Builder” without real personal data.
Isolating user text as data: validating the Prompt Boundary & Delimiter Builder output
Action: Keep that fixture unchanged and run the on-device method: Prompt Boundary & Delimiter Builder uses this disclosed method to build explicit data boundaries that separate untrusted content from instructions: parsing uses deterministic rules that preserve field and type boundaries.
Acceptance signal: Identical input should return the same result, with no network or file action assumed beyond the disclosed method.
Standardizing prompt reviews: checking the limits of Prompt Boundary & Delimiter Builder
Action: Retain the output record before moving it into the target workflow: When Prompt Boundary & Delimiter Builder finishes, it returns a parsed structure, field metrics, and explicit syntax findings, organised around the goal to build explicit data boundaries that separate untrusted content from instructions..
Acceptance signal: Acceptance requires Before accepting a Prompt Boundary & Delimiter Builder result, complete field names, value types, escaping, and empty or null values compared with the source; the evidence should support the goal to build explicit data boundaries that separate untrusted content from instructions.; otherwise do not move the result forward.
Do not use the result for a decision beyond this boundary: Prompt Boundary & Delimiter Builder limitation: Rule-based review does not prove real model behavior; retest with representative cases.
Move the result to another tool or live process only after Before accepting a Prompt Boundary & Delimiter Builder result, complete field names, value types, escaping, and empty or null values compared with the source; the evidence should support the goal to build explicit data boundaries that separate untrusted content from instructions.. Keep this limit visible in the decision record: Prompt Boundary & Delimiter Builder limitation: Rule-based review does not prove real model behavior; retest with representative cases.
A result in three steps
- 01
Paste the content to process. Expected format for Prompt Boundary & Delimiter Builder: For Prompt Boundary & Delimiter Builder, provide iNI or properties text with valid sections, keys, and values. The requested outcome is to build explicit data boundaries that separate untrusted content from instructions..
- 02
Generate the local template and review its boundaries. Prompt Boundary & Delimiter Builder applies this method: Prompt Boundary & Delimiter Builder uses this disclosed method to build explicit data boundaries that separate untrusted content from instructions: parsing uses deterministic rules that preserve field and type boundaries.
- 03
Test separately with role separation and allowlists on the real model. Acceptance check for Prompt Boundary & Delimiter Builder: Before accepting a Prompt Boundary & Delimiter Builder result, complete field names, value types, escaping, and empty or null values compared with the source; the evidence should support the goal to build explicit data boundaries that separate untrusted content from instructions..
When is this tool useful?
- ✓ Separating RAG content from instructions: local analysis with Prompt Boundary & Delimiter Builder
- ✓ Isolating user text as data: validating the Prompt Boundary & Delimiter Builder output
- ✓ Standardizing prompt reviews: checking the limits of Prompt Boundary & Delimiter Builder
Tool-specific limitation
Prompt Boundary & Delimiter Builder limitation: Rule-based review does not prove real model behavior; retest with representative cases.
LEARN THE WORKFLOW
Guides for this tool
A Reliable AI Workflow with Prompt Boundaries, Structured Output, and Red-Teaming
Separate untrusted data from instructions, define a JSON output contract, and test the model with evidence-driven cases before release.
Read guide →Prompt and Few-shot Example Quality Across Four Languages
Preserve placeholders, balance example classes, and prevent the behaviour contract changing silently during translation.
Read guide →ABOUT THIS TOOL
Frequently asked questions
What input does Prompt Boundary & Delimiter Builder accept?+
For Prompt Boundary & Delimiter Builder, provide iNI or properties text with valid sections, keys, and values. The requested outcome is to build explicit data boundaries that separate untrusted content from instructions. Paste the content to process. Expected format for Prompt Boundary & Delimiter Builder: For Prompt Boundary & Delimiter Builder, provide iNI or properties text with valid sections, keys, and values. The requested outcome is to build explicit data boundaries that separate untrusted content from instructions..
What does Prompt Boundary & Delimiter Builder return?+
When Prompt Boundary & Delimiter Builder finishes, it returns a parsed structure, field metrics, and explicit syntax findings, organised around the goal to build explicit data boundaries that separate untrusted content from instructions. Prompt Boundary & Delimiter Builder uses this disclosed method to build explicit data boundaries that separate untrusted content from instructions: parsing uses deterministic rules that preserve field and type boundaries.
How should I validate Prompt Boundary & Delimiter Builder output?+
For “Separating RAG content from instructions: local analysis with Prompt Boundary & Delimiter Builder”, first complete “Generate the local template and review its boundaries. Prompt Boundary & Delimiter Builder applies this method: Prompt Boundary & Delimiter Builder uses this disclosed method to build explicit data boundaries that separate untrusted content from instructions: parsing uses deterministic rules that preserve field and type boundaries.”, then apply this check: “Test separately with role separation and allowlists on the real model. Acceptance check for Prompt Boundary & Delimiter Builder: Before accepting a Prompt Boundary & Delimiter Builder result, complete field names, value types, escaping, and empty or null values compared with the source; the evidence should support the goal to build explicit data boundaries that separate untrusted content from instructions..”. Do not use a consequential result before a second test with boundary or malformed input.
Does this tool send or store input on a server?+
No. Processing runs in this browser tab and tool input is not persisted. Copying, downloading, or transferring happens only when you choose it.