| name | kata-interview |
| description | Conduct a JTBD switching interview to test one of the repository's products. Build a persona grounded in the installation's synthetic content with the situation drawn from the chosen JTBD entry, hand the job to the agent at the public website in two Ask calls, and capture findings as GitHub issues classified against the job.
|
Switching Interview
A JTBD switching interview: an agent, briefed only with a persona, tries
to get a chosen Job To Be Done done using one of the repository's products
they meet cold at the public website. The agent is isolated with no
repository access. You run in the repository root with JTBD.md, the
synthetic data/ from fit-terrain build, and project context — use them
to stage, craft, and verify, but never leak.
When to Use
- You are running the
kata-interview workflow.
- The task may include
Product: and/or Job: overrides; otherwise pick.
This skill is not part of scheduled runs.
LLM Availability
ANTHROPIC_API_KEY is in the shell and the products read it. LLM-backed
products work zero-config; if the agent asks for a key, that is a bug. Do
not tell the agent the key is pre-configured.
Checklists
<read_do_checklist goal="Protect the interview before briefing the agent">
</read_do_checklist>
<do_confirm_checklist goal="Close the interview cleanly">
</do_confirm_checklist>
Process
Step 0: Read Memory
Read wiki/MEMORY.md, then run fit-wiki boot --agent <self> per
memory-protocol § On-Boot Read Set.
The digest's owned_priorities, claims, and storyboard_items seed this
Process. Bias
product selection toward products not interviewed recently.
Step 1: Pick the Product
If the task includes Product:, use it. Otherwise pick one of the
repository's products that has a <job> entry in JTBD.md.
Step 2: Pick the Job
Read JTBD.md. Find every <job> entry whose Big Hire or Little
Hire line names the chosen product (e.g. → **<Product>**). If the
task includes Job:, match it against the goal= attribute; otherwise
pick one. Record the full block: user, goal, Trigger, Big Hire, Little
Hire, Competes With, Forces (Push, Pull, Habit, Anxiety), Fired When.
Step 3: Stage the Agent Workspace
The workflow ran fit-terrain build. Copy the data subset the chosen
product needs into $AGENT_CWD — the product's own directory plus any
shared data it reads:
cp -r data/<product> "$AGENT_CWD/data/<product>" and similar. LLM-backed
products need nothing staged. For substrate-backed products the workflow's
substrate-setup step brings the substrate up and emits its URL/key — the
skill stages no substrate itself.
Step 3a: Select the Persona (when a persona-select command is set)
Persona selection is driven by an injected command, not hardcoded here, so
the loop works for any substrate a consumer supplies.
PERSONA_SELECT_COMMAND set — run it. Its contract: seal a persona
identity (.env + .substrate.json) into $AGENT_CWD and stash a bare
JWT for the post-run log scan (the agent has no $RUNNER_TEMP access).
Read the persona it prints (name, team, manager, teammates, repos, and
scenario) from the command's output for Step 4. On non-zero exit, write a
diagnostic and exit the skill.PERSONA_SELECT_COMMAND unset — issue no JWT; build the persona
identity from the synthetic content fit-terrain build produced (Step 4).
Step 4: Craft the Persona
Write $AGENT_CWD/CLAUDE.md. The persona file carries who and the
situation — never the job. Two sources:
- Identity (name, team, manager, teammates, repos, recent project,
company facts) — when a persona-select command ran (Step 3a), from the
persona it printed. Otherwise from the synthetic content
fit-terrain build produced.
- Situation (Trigger, Forces, Competes With) — from the chosen JTBD
entry, rephrased into the persona's voice.
Excluded: goal sentence, Big Hire, Little Hire, Fired-When, product name.
Fired-When stays with you for Step 8 classification.
Template: references/persona-template.md.
Worked examples:
references/example-personas.md.
Step 5: Initiate the Session
Hand off in two Ask calls so persona and job both surface inline in
the trace. Ask 1 opens with an introduction prompt; the agent's
Answer brings the persona, Trigger, and Forces inline. Ask 2
delivers the job (Big Hire + Little Hire as the persona's own want) and the
entry point. Read the entry point from WEBSITE_URL in the environment; if
it is unset, write a diagnostic and exit the skill.
Templates and worked examples:
references/job-handoff.md. If the task
carries steering not matching Product: / Job:, append it to Ask 2.
Step 6: Supervise
| Agent State | Your Response |
|---|
| Making progress | Short encouragement |
| Stuck on a specific step | Answer the specific question, in character |
| Going down a dead end | Nudge toward the documented path |
| Looping without progress | Targeted guidance |
| Job done or abandoned | Proceed to Step 7 |
Short reply messages, not further Ask calls — only Step 5 uses two Asks.
Use repository access to verify observations, but never feed verification
back to the agent.
Step 7: Transition to Post-Interview
Once done or abandoned, stop Asking and do Steps 8–9 yourself with your own
Bash and repository checkout — never delegate wrap-up to the agent (it breaks
isolation). Conclude only after filing issues and writing the report.
Step 8: Capture Findings
Review the agent's output. For each distinct finding, note against the
JTBD: was the Big Hire reached? Little Hire experienced? Did
Anxiety land? Did Competes With look more attractive? Did any
Fired When condition surface?
Classify each for action:
| Category | Criteria | Action |
|---|
| Bug | Crashes, errors, wrong output | Create bug issue |
| Product-aligned | Missing feature serving the vision | Create feature issue |
| Documentation | Unclear, missing, or outdated docs | Create docs issue |
| Out of scope | Not actionable or outside the product | Skip — note in report |
For each actionable finding, with your own gh: extract; search for duplicates;
create a new issue or comment on a matching one (templates in
../kata-product-issue/references/templates.md) naming the JTBD job
(<user>: <goal>) in the body; add it to the report table with its issue
number, holding each body to
Citation integrity.
Step 9: Report
Final summary: product and job; whether the persona got it done; which JTBD
forces materialized; table of findings and issues created or updated.
Memory: What to Record
Using your own Bash, append to the current week's log: product interviewed;
job (<user>: <goal>); outcome (done / abandoned / partial); forces observed
(Push/Pull/Habit/Anxiety/Competes/Fired); issue numbers + categories.
Append one metrics row per run to wiki/metrics/{skill}/ per
references/metrics.md. See KATA.md § Metrics for recording eligibility.
