Trace to Interview Agent Skill

Turns a set of production traces into discovery interviews — recovering, for each behaviour pattern, the discovery question the user…

Context cost
11.3k tokensestimated from the bundle, loaded when it triggers
Bundle
13 files · 45.2 kBtext throughout, nothing executable
Licence
Apache-2.0the author’s own terms
Last change
—no release on file
Servers it uses
Noneruns standalone

What it does

Turns a set of production traces into discovery interviews — recovering, for each behaviour pattern, the discovery question the user answered by acting instead of talking. Fires on "learn from usage", "mine the logs", "what are our production traces telling us", "turn usage data into discovery", "what are users saying in the logs". Outputs a trace-interview log: one card per behaviour pattern with the observed behaviour [Fact, 0.7], the discovery question it answers, the inferred JTBD/satisfaction signal [Hypothesis], distinct-user weight, the confirm-the-why probe, and the cost of the…

What this skill changes about the agent has not been set out here as a list. Its SKILL.md, shown below, says it in the author’s own words.

analytics

The skill itself

A skill is instructions the model reads, so you can see what you are getting: below is the start of its SKILL.md. The front matter loads with every session, the body loads when the skill triggers, and the whole file comes with the install.

SKILL.md13.8 kB · preview
--- name: trace-to-interview type: generator supersedes: none ---
7# Trace to Interview
8
9## What it does
10Reads production traces as interviews that already happened. For each pattern of what users actually did — retried, edited before accepting, exported and left, abandoned at step three — it recovers the discovery question the behaviour answers and the job behind it, then writes it up as an interview card ([template.md](template.md)). The output is a trace-interview log: one card per pattern carrying the observed behaviour [Fact] at behaviour-rung 0.7, the discovery question it answers, the inferred JTBD and satisfaction signal [Hypothesis], how many distinct users produced it, the probe that confirms the why, and what the equivalent scheduled interview would have cost. Each card routes to continuous-discovery-engine as a feed-2 signal. It is not a funnel, not a metrics dashboard, and not a transcript summary.
11
12## The Icarus reframe
13Generic log-mining counts events and draws a funnel: how many, how often, where they drop. That returns metrics, and a metric tells you *what* happened while hiding *why*. The Icarus move is that every production trace is a customer interview that already happened — the user answered a discovery question through behaviour instead of words, for free, with no calendar invite. A retry is the user saying "that wasn't what I meant." An edit-before-accept is "close, but wrong here." An export-then-leave is "I'll finish this elsewhere." The trace is both cheaper *and* more truthful than the interview it replaces: it sits at behaviour 0.7, a rung above what a person *says* they do (verbal 0.3), and its marginal cost is the triage minutes rather than a recruit, an incentive, and two weeks of lead time. That is the exact reason launch is when discovery gets cheap, not when it ends.
14
15## When to use / When NOT
16Use it post-launch (or mid-pilot) when you have real production traces and you want to turn usage into discovery findings, not into a chart.
17
18| Situation | Use this? | Go to |
19|---|---|---|
20| "Mine our logs — what are users telling us?" | Yes | trace-to-interview |
21| "Turn our production traces into discovery questions." | Yes | trace-to-interview |
22| "What job aren't we finishing? Read it off the usage." | Yes | trace-to-interview |
23| "Build the retention curve / North Star / AARRR dashboard." | No | metrics-that-matter (keeps the number; this recovers the question) |
24| "Summarise this recorded customer interview / transcript." | No | summarize-interview (words at 0.3; this is behaviour at 0.7) |
25| "Stand up the whole discovery loop — interviews + traces + evals, on a cadence." | No | continuous-discovery-engine (this decodes one feed and feeds it up) |
26| "Prep and run a live tacit-knowledge interview with an operator." | No | tacit-knowledge-interview |
This is a preview of SKILL.md. Download or install the skill to get the whole thing.
In the file
SKILL.md2,255 words
Files13
LicenceApache-2.0
Why you can read it

Nothing in a skill executes. The client loads the text and the model follows it, so a skill can be audited the way a runbook is — by reading it.

What it costs in context

Skills are not billed by the call. They are paid for in context: every token the instructions occupy is a token your code, your diff and your conversation cannot use. Here is what this one takes and when it takes it.

≈290
always loaded
The name and description, so the model knows the skill exists and when to reach for it.
11,010
on trigger
The instruction body and 12 supporting files, read only when the skill fires.
5.7%
of a 200k window
Ten skills this size would take about 57% of the window before you open a file.
050k100k150k200k context window

11.3k tokens, estimated from the bundle at four bytes to the token, held for the rest of the session once it triggers. Heavy. Teams tend to install this one per project rather than globally, and load it only when the job comes up.

Servers bill, skills cost

A server charges by the month. A skill charges once per session, in context, and then keeps charging it for as long as the session lives.

Before and after

The same question, put to the same model twice: once as it comes, and once with these instructions loaded.

No worked example has been published for this skill yet.

The procedure it runs

The procedure has not been set out here step by step. It is in the body of its SKILL.md: the start of it is shown above, and the whole file comes with the install.

Prose, not code

These steps are written for a model to follow, not executed by a runtime. It can still be told to skip one, and it will say so when it does.

Servers it uses

None. This skill calls no MCP servers at all.

Everything it needs is in the instructions, so it works in a project with nothing connected — the model reads the file and changes how it works with what it can already reach.

Its SKILL.md does not declare which tools it asks the agent for, so what it touches is whatever the instructions themselves ask for — read them before you install it.

What it asks for
Writes filesnot declared
Network accessnot declared

This SKILL.md carries no allowed-tools line, so neither is declared. A skill grants no permissions of its own — it can only ask for tools your client already has.

What it will not do

Every skill is narrow, and the useful ones say where they stop. These are the jobs this one is the wrong tool for.

What this skill is not for has not been published here. Nothing is implied by that: it is a section the author has not filled in.

What is in the bundle

13 files, 45.2 kB on disk. A bundle is text throughout: the instructions the model reads, plus the templates it fills in.

  • SKILL.md13.8 kB
  • template.md4.6 kB
  • examples/sample.md7.0 kB
  • tests/RESULTS.md5.7 kB
  • tests/rubric.json1.1 kB
  • tests/adversarial/01.md0.9 kB
  • tests/adversarial/02.md1.5 kB
  • tests/adversarial/03.md1.4 kB
  • tests/golden/01.md1.9 kB
  • tests/golden/02.md1.9 kB
  • tests/golden/03.md2.0 kB
  • tests/golden/04.md1.6 kB
  • tests/golden/05.md1.8 kB
What is not in it

No dependencies and nothing executable: a skill is text the agent reads, so the bundle is 13 files you can review in full before installing. The Apache-2.0 licence covers the templates and examples as well as the instructions.

Install

Installing copies the bundle into your project. Nothing runs at install time — the files sit on disk until the model reads them.

# Trace to Interview · 11.3k tokens when loaded · macOS, Linux mkdir -p .claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/trace-to-interview/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/trace-to-interview" ] && { [ ! -e .claude/skills/trace-to-interview ] || { mv .claude/skills/trace-to-interview "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/trace-to-interview" .claude/skills/ && echo "Installed .claude/skills/trace-to-interview"
On Windows, or any OS with Node 20+
npx mcprush@latest skill add the-utopia-studio/trace-to-interview

Windows PowerShell says 'running scripts is disabled on this system'? Run Set-ExecutionPolicy -Scope CurrentUser RemoteSigned once, or type npx.cmd instead of npx (codex.cmd, gemini.cmd, grok.cmd likewise). PowerShell 7 needs neither. Writes to .claude/skills/trace-to-interview/ in the current project. For every project instead, run mkdir -p ~/.claude/skills && t=$(mktemp -d) && curl -fsSL -o "$t/bundle.tar.gz" https://mcprush.com/api/skills/trace-to-interview/bundle.tar.gz && tar -xzf "$t/bundle.tar.gz" -C "$t" && [ -d "$t/trace-to-interview" ] && { [ ! -e ~/.claude/skills/trace-to-interview ] || { mv ~/.claude/skills/trace-to-interview "$t/.previous" && echo "Previous copy moved to $t/.previous"; }; } && mv "$t/trace-to-interview" ~/.claude/skills/ && echo "Installed ~/.claude/skills/trace-to-interview" (macOS, Linux) — or add --global to the npx line. The curl line replaces .claude/skills/trace-to-interview/ only after the download succeeds, so files left there by another skill of the same name, or by an older release, do not mix in. A copy already there is moved aside, not deleted, and the line prints where.

Which clients pick it up on their own

A skill is a folder of text. Most of these read a skills folder and pick it up without being told; the rest take the same folder another way — an upload in the app, a parameter on an API call — and then choose it by its description just the same.

Claude Code.claude/skills/
Claude DesktopCustomize › Skills
ChatGPTSkills › Create › Upload
Cursor.cursor/skills/
VS Code.github/skills/
Codex CLI.agents/skills/
Gemini CLI.gemini/skills/
Grok Build.grok/skills/
Microsoft CopilotSkills › Upload a skill
PerplexityComputer › Skills › Upload a skill
DeepSeek Harness.dsh/skills/
Zed.agents/skills/
Devin Desktop.devin/skills/
Windsurf (legacy).windsurf/skills/
OpenAI Agents SDKInstructions or sandbox Skills
HTTP / APIa request parameter
This release
Versionnot versioned
Publishedno release date on file
PriceFree
Referencethe-utopia-studio/trace-to-interview

Versions

Its author publishes no version number, so there is nothing here to pin to: what you install is the folder as it stands today. Instructions change more often than APIs do — a skill can be rewritten entirely without anything it depends on moving.

Pinning

Nothing to pin to: this skill carries no version number of its own. What you install is what the folder holds on the day you install it.

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