CLI and workspace hygiene · Lesson 10 of 12 · 9 min

Verify a manifest checksum

A checksum tests byte identity against a trusted expected value. Matching hashes do not by themselves establish the safety or provenance of the expected artifact.

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learner@clairos:~ $

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Your objectives

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1
Read the case evidence
Read /opt/ai-lab/cases/aiops-cli-workspace-010.json. Separate the recorded facts from your assumptions.
Hint & worked example
A checksum tests byte identity against a trusted expected value. Matching hashes do not by themselves establish the safety or provenance of the expected artifact.
The complete case JSON is read successfully.
```
cat /opt/ai-lab/cases/aiops-cli-workspace-010.json
```
Common mistake to avoid: Activate the artifact because its filename looks correct.
2
Isolate the deciding signal
Select the match field from the case JSON. What does it establish—and what does it not establish?
Hint & worked example
Hold the artifact because its observed checksum differs from the expected value.
A successful JSON query isolates match.
```
jq .match /opt/ai-lab/cases/aiops-cli-workspace-010.json
```
Common mistake to avoid: Using a different case or an unrelated signal as the justification.
3
Record your operational decision
Choose the justified code: hold-artifact, change-without-evidence, or ignore-the-signal. Save that one code followed by a newline in /home/learner/lab/aiops-cli-workspace-010-decision.txt.
Hint & worked example
Hold the artifact because its observed checksum differs from the expected value.
The decision artifact contains the correct code, not just a matching command in history.
```
printf '%s\n' 'hold-artifact' > /home/learner/lab/aiops-cli-workspace-010-decision.txt
```
Common mistake to avoid: Activate the artifact because its filename looks correct.

Understand the pattern

A checksum tests byte identity against a trusted expected value. Matching hashes do not by themselves establish the safety or provenance of the expected artifact.

Interpret the evidence

Hold the artifact because its observed checksum differs from the expected value.

A tempting mistake

Activate the artifact because its filename looks correct.

All names, measurements, prices, versions, and thresholds in this exercise are fictional training data. The evidence supports this bounded scenario, not a claim about a live provider.

Worked example and expected result

$ cat /opt/ai-lab/cases/aiops-cli-workspace-010.json

{
  "fixture": "Fictional training data; not a live measurement.",
  "expected_sha256": "training-a1",
  "observed_sha256": "training-b2",
  "match": false
}

Exit status: 0. The command completed successfully in the training fixture.

$ jq .match /opt/ai-lab/cases/aiops-cli-workspace-010.json

false

Exit status: 0. The command completed successfully in the training fixture.

$ printf '%s\n' 'hold-artifact' > /home/learner/lab/aiops-cli-workspace-010-decision.txt

(no output; exit 0)

Exit status: 0. The command completed successfully in the training fixture.

Try a variation

Name the assumption that would have to change for “hold-artifact” to stop being the justified action. Do not silently replace missing evidence with a guess.

Explain it

What does the evidence in “Verify a manifest checksum” justify?Activate the artifact because its filename looks correct.Make the change now and gather the missing evidence afterward.Hold the artifact because its observed checksum differs from the expected value.

Apply it elsewhere

A colleague concludes: “Activate the artifact because its filename looks correct.” What should you do?Treat this fixture as a live measurement.Reject that conclusion; return to the case evidence and its stated limits.Accept it because the training command completed.

Keep the momentum.

Complete the lab, then explain and apply the pattern.

Next: Write an operator note Try an incident drill

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Keep learning

Case methodology: evidence, limits, decision