How to Use: Langfuse Trace Span Checklist from Observability Notes (No Invented Token Totals)
How to use the Langfuse Trace Span Checklist from Observability Notes (No Invented Token Totals) PromptDig prompt without inventing metrics.
You pasted messy Langfuse observability notes and need a clean deliverable without invented numbers. This PromptDig prompt turns only what you already listed into a structured trace-span checklist for trace span handoffs.
What this prompt does
It locks your observability notes, version, labels, and domain fields, then builds a ledger plus a table that refuses fake metrics. Missing cells stay NOT IN INPUTS instead of guessing.
Use it when you already have real stubs from Langfuse and want a teachable trace-span checklist for this job, not a generic template swap from another vendor. The Generate steps name Langfuse nouns on purpose so a title swap into another category would fail the swap-title test.
The deliverable is aimed at Langfuse trace-span checklists. Reviewers should see your locked nouns echoed in the table rows, not marketing fluff. Cap style limits stay soft unless you add them later in Extra.
How to fill the brackets
- Paste your observability notes with concrete nouns only. Prefer two labeled rows so the example shape stays visible after you swap names.
- Lock Version to what you actually run. If you do not know the version, write unknown rather than guessing a marketing release name.
- Fill labels you may quote only when you already have names you are allowed to use.
- Complete the domain fields that match this job. Leave blanks as UNKNOWN instead of inventing token totals, latency ranks, cost scoreboards.
- Set Banned and Never to the phrases you refuse. Keep Format and Lang explicit.
Keep Harbor Quay sample nouns out of your production paste. Those labels exist only so the example_input shows two concrete rows. Replace them with your real labels before you run the prompt.
Who it is for
ML engineers who inherit messy Langfuse observability notes. It is also useful when a teammate hands you a partial export and you need a trace-span checklist that stays honest about gaps.
How to run it
- Open Langfuse Trace Span Checklist from Observability Notes (No Invented Token Totals) on PromptDig.
- Copy the prompt into ChatGPT, Claude, or Gemini.
- Replace every bracket with your locked observability notes. Do not leave sample Harbor nouns in place if they are not yours.
- Run once, then fix only the gaps list. Do not ask the model to invent missing metrics.
- Paste the trace-span checklist into your handoff doc and keep NOT IN INPUTS visible for reviewers.
What good output looks like
A strong run starts with an honesty ledger that quotes your locked nouns and Version. The tables attach only names that appeared beside each other in Inputs. Refuse lines explicitly reject fake token totals, latency ranks, cost scoreboards.
Weak output invents metrics, adds vendor features not in Version, or swaps in another tool's nouns. If you see that, tighten Banned and Never, then rerun.
Common mistakes
- Inventing token totals, latency ranks, or cost scoreboards the notes never stated.
- Treating UNKNOWN as a cue to guess defaults.
- Dropping the gaps list so reviewers cannot see what is still owed.
- Softening Never so the model pads with industry averages.
- Copying a Phoenix or Helicone template and hoping the nouns still fit.
When not to use it
Skip this prompt if you have no Langfuse observability notes at all. It will not invent a starter inventory for you. Skip it if you need live dashboard sync or API pulls; this is a checklist compiler from pasted text only.
Soft next steps
After you lock a clean trace-span checklist, browse related PromptDig prompts for nearby jobs, or share your own improved version with the community.
Langfuse Trace Span Checklist from Observability Notes (No Invented Token Totals)