← All Test Cases
high
VER-003
update versioning
Repetitions
5
Documents
2
Questions
1
Reasoning
DIRECT
update_versioning
duplicate_title
shift_time
source_id_precision
same_title
📖 In Plain English
What this category tests
Does the brain return the latest version of a document after updates?
How the test works
A document is ingested at v1, then a v2 supersedes it. The test asks about the topic and checks the v2 content is returned, with v1 marked superseded.
Why it matters
Stale data is dangerous — users must always see the current truth.
⚙️ How a single rep runs
① Generate
Model creates 2 synthetic documents and 1 question with unique canary tokens
→ Fresh content per run prevents memorization and proves real retrieval
② Ingest (MCP)
Model calls brain_ingest to store the 2 documents
→ Tests the brain's storage and indexing pipeline
③ Query (MCP)
Model answers the question using brain retrieval tools (search, fetch, context_pack, etc.)
→ Core test — does the brain return correct evidence and let the model build a faithful answer?
④ Evaluate
Model judges the answer against ground truth (the document it generated in phase 1)
→ Produces a score 0–100 with detailed sub-scores (retrieval, fidelity, reasoning, etc.)
This rep is run 5 times per test run. A pass requires score ≥ 85 and no critical failures.
🔬 Technical Instructions (raw prompts sent to AI)
🔧 ① Setup Instructions 1996 chars
You are the Generator AI. Your job is to produce a single JSON object for this test run.
Run ID: {{RUN}}
Repetition: {{REP}}
Steps:
1. Choose two distinct shift start times:
TIME_A : an earlier time (e.g. "09:00", "07:30", "08:00", "06:45")
TIME_B : a later time (e.g. "10:00", "09:00", "09:30", "08:15")
Ensure TIME_A != TIME_B.
2. Construct two documents. Both have IDENTICAL titles but different content:
Doc A:
source_id : "KB-{{RUN}}-VER-003-A-v1"
title : "Shift Note"
content : "Shift starts <TIME_A>."
Doc B:
source_id : "KB-{{RUN}}-VER-003-B-v1"
title : "Shift Note"
content : "Shift starts <TIME_B>."
3. Construct exactly one question (as a string):
"Which source_id says shift starts at <TIME_A>?"
4. Construct the expected answer:
question_index : 0
correct_answer : "KB-{{RUN}}-VER-003-A-v1"
required_label : "DIRECT"
required_source_ids : ["KB-{{RUN}}-VER-003-A-v1"]
must_refuse : false
notes : "Only Doc A contains TIME_A. Doc B contains TIME_B. Titles are identical."
Output ONLY valid JSON, no prose, no markdown fences:
{
"run_id": "{{RUN}}",
"test_id": "VER-003",
"repetition": {{REP}},
"documents": [
{
"source_id": "KB-{{RUN}}-VER-003-A-v1",
"title": "Shift Note",
"content": "Shift starts <TIME_A>."
},
{
"source_id": "KB-{{RUN}}-VER-003-B-v1",
"title": "Shift Note",
"content": "Shift starts <TIME_B>."
}
],
"questions": [
"Which source_id says shift starts at <TIME_A>?"
],
"expected_answers": [
{
"question_index": 0,
"correct_answer": "KB-{{RUN}}-VER-003-A-v1",
"required_label": "DIRECT",
"required_source_ids": ["KB-{{RUN}}-VER-003-A-v1"],
"must_refuse": false,
"notes": "Doc A contains <TIME_A>; Doc B contains <TIME_B>. Titles are identical so executor must disambiguate by content."
}
]
}
▶ ② Execution Instructions 787 chars
Use ONLY MCP Knowledge Brain retrieval tools. Do not rely on memory or workspace context.
Question: {{QUESTION}}
Retrieve documents and inspect their content carefully. Two documents may share the same title.
You must identify the specific source_id whose content contains the time mentioned in the question.
Do not confuse documents based on title alone — check the actual content.
Return ONLY this JSON (no prose, no markdown):
{{REQUIRED_ANSWER_SCHEMA}}
Where the schema is:
{
"question_id": "Q1",
"answer": "<the source_id whose content says shift starts at the queried time>",
"reasoning_type": "DIRECT",
"source_ids": ["<the matching source_id>"],
"confidence": "<high|medium|low>",
"disambiguation_note": "<brief note on how you distinguished the two documents>"
}
⚖ ③ Judge Instructions 1094 chars
You are the Judge AI. Evaluate whether the Executor correctly identified the source_id
containing TIME_A, despite both documents sharing the same title.
Ground truth (from setup):
{{SETUP_CONTEXT_JSON}}
Executor's answer:
{{EXEC_ANSWER_JSON}}
Evaluation rules:
1. Expected answer source_id = "KB-<run_id>-VER-003-A-v1".
2. Check executor's answer.answer equals the expected source_id exactly.
3. If executor returned "KB-<run_id>-VER-003-B-v1" = critical failure
(confused by duplicate title, returned wrong document).
4. If executor cited a source_id not present in setup documents = hallucinated source = critical failure.
5. disambiguation_note present and coherent = positive signal, but not required for pass.
6. Test passes only if the correct source_id is returned.
Return ONLY this JSON:
{{JUDGE_RESULT_SCHEMA}}
Where the schema is:
{
"test_id": "VER-003",
"run_id": "<run_id>",
"repetition": <rep>,
"passed": <true|false>,
"critical_failure": <true|false>,
"critical_failure_reason": "<null or description>",
"score": <0.0-1.0>,
"notes": "<brief explanation>"
}
Critical Failure Conditions
- Executor returned Doc B's source_id (KB-{{RUN}}-VER-003-B-v1) instead of Doc A's
- Executor was confused by the duplicate title and returned the wrong source_id
- Executor cited a source_id not present in setup documents (hallucinated source)
Recent Run History
2 runs| When | Run ID | Pass Rate | Avg Score | Reps | |
|---|---|---|---|---|---|
| 2026-05-24 13:08 | 20260524T130808Z-kqze | 100% | 100.0 | 1/1 | View → |
| 2026-05-24 11:37 | 20260524T113756Z-kduj | 0% | 0 | 0/1 | View → |
📄 Raw YAML cases/update_versioning/VER-003.yaml
schema_version: "1.0"
test_id: "VER-003"
category: "update_versioning"
severity: "high"
repetitions: 5
reasoning_type: "DIRECT"
num_documents: 2
num_questions: 1
tags: [update_versioning, duplicate_title, shift_time, source_id_precision, same_title]
setup_instructions: |
You are the Generator AI. Your job is to produce a single JSON object for this test run.
Run ID: {{RUN}}
Repetition: {{REP}}
Steps:
1. Choose two distinct shift start times:
TIME_A : an earlier time (e.g. "09:00", "07:30", "08:00", "06:45")
TIME_B : a later time (e.g. "10:00", "09:00", "09:30", "08:15")
Ensure TIME_A != TIME_B.
2. Construct two documents. Both have IDENTICAL titles but different content:
Doc A:
source_id : "KB-{{RUN}}-VER-003-A-v1"
title : "Shift Note"
content : "Shift starts <TIME_A>."
Doc B:
source_id : "KB-{{RUN}}-VER-003-B-v1"
title : "Shift Note"
content : "Shift starts <TIME_B>."
3. Construct exactly one question (as a string):
"Which source_id says shift starts at <TIME_A>?"
4. Construct the expected answer:
question_index : 0
correct_answer : "KB-{{RUN}}-VER-003-A-v1"
required_label : "DIRECT"
required_source_ids : ["KB-{{RUN}}-VER-003-A-v1"]
must_refuse : false
notes : "Only Doc A contains TIME_A. Doc B contains TIME_B. Titles are identical."
Output ONLY valid JSON, no prose, no markdown fences:
{
"run_id": "{{RUN}}",
"test_id": "VER-003",
"repetition": {{REP}},
"documents": [
{
"source_id": "KB-{{RUN}}-VER-003-A-v1",
"title": "Shift Note",
"content": "Shift starts <TIME_A>."
},
{
"source_id": "KB-{{RUN}}-VER-003-B-v1",
"title": "Shift Note",
"content": "Shift starts <TIME_B>."
}
],
"questions": [
"Which source_id says shift starts at <TIME_A>?"
],
"expected_answers": [
{
"question_index": 0,
"correct_answer": "KB-{{RUN}}-VER-003-A-v1",
"required_label": "DIRECT",
"required_source_ids": ["KB-{{RUN}}-VER-003-A-v1"],
"must_refuse": false,
"notes": "Doc A contains <TIME_A>; Doc B contains <TIME_B>. Titles are identical so executor must disambiguate by content."
}
]
}
execution_instructions: |
Use ONLY MCP Knowledge Brain retrieval tools. Do not rely on memory or workspace context.
Question: {{QUESTION}}
Retrieve documents and inspect their content carefully. Two documents may share the same title.
You must identify the specific source_id whose content contains the time mentioned in the question.
Do not confuse documents based on title alone — check the actual content.
Return ONLY this JSON (no prose, no markdown):
{{REQUIRED_ANSWER_SCHEMA}}
Where the schema is:
{
"question_id": "Q1",
"answer": "<the source_id whose content says shift starts at the queried time>",
"reasoning_type": "DIRECT",
"source_ids": ["<the matching source_id>"],
"confidence": "<high|medium|low>",
"disambiguation_note": "<brief note on how you distinguished the two documents>"
}
judge_instructions: |
You are the Judge AI. Evaluate whether the Executor correctly identified the source_id
containing TIME_A, despite both documents sharing the same title.
Ground truth (from setup):
{{SETUP_CONTEXT_JSON}}
Executor's answer:
{{EXEC_ANSWER_JSON}}
Evaluation rules:
1. Expected answer source_id = "KB-<run_id>-VER-003-A-v1".
2. Check executor's answer.answer equals the expected source_id exactly.
3. If executor returned "KB-<run_id>-VER-003-B-v1" = critical failure
(confused by duplicate title, returned wrong document).
4. If executor cited a source_id not present in setup documents = hallucinated source = critical failure.
5. disambiguation_note present and coherent = positive signal, but not required for pass.
6. Test passes only if the correct source_id is returned.
Return ONLY this JSON:
{{JUDGE_RESULT_SCHEMA}}
Where the schema is:
{
"test_id": "VER-003",
"run_id": "<run_id>",
"repetition": <rep>,
"passed": <true|false>,
"critical_failure": <true|false>,
"critical_failure_reason": "<null or description>",
"score": <0.0-1.0>,
"notes": "<brief explanation>"
}
critical_failures:
- "Executor returned Doc B's source_id (KB-{{RUN}}-VER-003-B-v1) instead of Doc A's"
- "Executor was confused by the duplicate title and returned the wrong source_id"
- "Executor cited a source_id not present in setup documents (hallucinated source)"