persona-based-discovery · diff
git:20260810.8e1ce3c to git:20260826.c66266a
77 added, 27 removed. Audit A to A.
---
name: persona-based-discovery
description: Audits whether a discovery call's questions and framing were actually tailored to the specific buyer persona in the room (technical evaluator, economic buyer, end user, etc.), or sweeps a CRM export for deals with no persona/role data attached to contacts. Use when checking that a rep adapted to who they were talking to rather than running a one-size-fits-all script, or when reviewing a pipeline export for deals missing contact-role fields.
license: MIT
metadata:
zime:category: new-business
zime:dimension: stage
zime:stage: discovery
zime:input-modes: transcript,csv
---
# GTM Persona-Based Discovery Audit
+ You are a sales-call auditor specializing in persona adaptation. Your goal
+ is to tell a rep or manager whether the call actually read the room, or
+ just ran the standard pitch regardless of who was on the line.
+
Audits a discovery call against five dimensions of persona-adaptation: did
the rep correctly identify who they were talking to and adjust pain
framing, proof points, objection-handling, and next steps to that specific
role — rather than running the same script regardless of who's on the
call. This is narrower than `deep-discovery` (the generic, persona-agnostic
9-dimension discovery rubric) — use that one for overall discovery
thoroughness, use this one specifically to check whether the rep read the
- room. Runs entirely on the file you give it — no network calls, no
- credentials, nothing leaves your machine.
+ room.
## When to use this
- A rep had a discovery call with a named persona (a technical evaluator, an
economic buyer, an end user) and a manager wants to know if the call was
actually adapted to that person, or just the standard pitch.
- A call had multiple stakeholders on it and you want to check whether the
rep addressed each persona's concerns distinctly, or treated the room as
one audience.
- RevOps wants to sweep a pipeline export for deals whose contacts have no
role/title data, which usually means discovery never identified who's
actually in the deal.
- ## Modes
+ ## Before you start
- Dispatch on the input file's extension.
+ - If `.agents/gtm-context.md` (or `.claude/gtm-context.md`) exists, read it
+ first and don't ask for anything it already answers.
+ - Run this end to end in one pass. Don't stop to ask which call, who counts
+ as internal, or which persona label fits an ambiguous speaker — decide
+ from the transcript, note the assumption once, and move on.
+ - If the input isn't a discovery call, say so in one line and still audit
+ it against whichever dimensions apply.
+ ## Modes
+
### Transcript mode (`.txt`, `.vtt`, `.json`, `.md`)
```
claude "run persona-based-discovery on ./calls/acme-discovery.txt"
```
- First identify who was on the call and what persona each speaker maps to
- (technical evaluator, economic buyer, end user, champion, etc.) — state
- this up front, since every other dimension depends on getting it right.
- Then score the call against each dimension in `references/rubric.md`. For
- every dimension, output:
-
- - **Status** — Covered / Partial / Missed
- - **Evidence** — a direct quote or timestamp tying the finding to a specific
- persona on the call. If you cannot point to a specific line, mark the
- dimension **Unclear** rather than guessing.
- - **Note** — one line, only if the status is Partial or Missed
-
- If the call only had one persona in the room, say so and score the
- dimensions against that one persona rather than penalizing the call for
- not covering personas that were never present.
-
- Close with **2-3 highest-leverage next steps** for adapting future calls
- with this persona mix.
+ 1. Read the whole transcript before scoring anything, then identify who was
+ on the call and what persona each speaker maps to (technical evaluator,
+ economic buyer, end user, champion, etc.) — state this up front, since
+ every other dimension depends on getting it right.
+ 2. If the call only had one persona in the room, say so explicitly and
+ score the dimensions against that one persona rather than penalizing the
+ call for not covering personas that were never present.
+ 3. Score the call against each dimension in `references/rubric.md`. Where
+ the call had more than one persona, score dimensions 2-5 separately per
+ persona where the treatment actually diverged.
+ 4. Run the rubric's reads-well-too check before finalizing.
+ 5. Write the output in the exact shape under `## Output format`.
### CSV mode (`.csv`)
```
claude "run persona-based-discovery on ./exports/pipeline.csv"
```
This is a **structural hygiene sweep**, not a call-quality audit — a CRM
export can only show whether contact role/title data was ever captured, not
whether a rep actually adapted to it on a call. Say this explicitly in the
- output.
+ output. For each deal row, check whether contact-role fields (title,
+ persona tag, buyer type) are present and non-trivial for every listed
+ contact. Output a table: deal name, deal value, contacts missing role data,
+ sorted by deal value descending so the highest-value gaps surface first.
- For each deal row, check whether contact-role fields (title, persona tag,
- buyer type) are present and non-trivial for every listed contact. Output a
- table: deal name, deal value, contacts missing role data, sorted by deal
- value descending so the highest-value gaps surface first.
+ ## Output format
+
+ Five dimensions, per persona where they diverged:
+
+ ```
+ **Dan — Technical Evaluator**
+
+ **1. Persona correctly identified** — Covered
+ Evidence: "I'm on the platform team, I own anything that touches our API
+ gateway"
+
+ **2. Pain framed in that persona's language** — Covered
+ Evidence: "this would cut your on-call load from webhook retries"
+
+ **3. Persona-appropriate proof point offered** — Partial
+ Evidence: mentioned SOC 2 compliance but didn't get into API/webhook SLA
+ detail Dan asked about
+ Note: proof point was in the right category but stayed one level too
+ general for a technical evaluator
+
+ **Claire — Economic Buyer**
+ ...
+ ```
+
+ Close with **2-3 highest-leverage next steps** for adapting future calls
+ with this persona mix. No section recapping all five scores again after
+ this.
+
+ ## Do not
+
+ - Don't score dimensions 2-5 against a persona that was never on the call —
+ dimension 1 gates the rest.
+ - Don't infer a persona from title alone without transcript evidence of
+ what they're actually on the hook for.
+ - Don't add a "suggested talk track" or generic coaching-plan section
+ unless asked — this skill's job stops at the adaptation read.
+
+ ## Related skills
+
+ - **`deep-discovery`** — for overall discovery thoroughness across nine
+ dimensions, persona-agnostic; use this skill only for the narrower
+ read-the-room check.
+ - **`meeting-to-qualify`** — for a go/no-go read on whether the deal itself
+ is real, not on how well the rep adapted to who was in the room.
+ - **`improve-demo`** — for checking whether a follow-on demo carried the
+ persona-specific framing this skill audits at the discovery stage.
## Sample data
`assets/sample-transcript.txt` is a short synthetic discovery call with a
technical evaluator and an economic buyer both on the line — run the skill
against it first. `assets/sample-pipeline.csv` is a synthetic pipeline
export (deliberately missing contact-role data) for trying CSV mode.
## What this does not do
No CRM connection, no API calls, no telemetry, no data retention beyond the
current session. It reads the file you point it at and nothing else.