# Presales With Docs

> Run live presales discovery one question at a time, preserve a decision ledger, and produce an auditable ballpark/ROM for services, infrastructure, timeline, and BAU. Use when a presales operator is scoping a client project, qualifying requirements, estimating man-days, loading an approved rate card from Notion, or preparing an indicative cost for client discussion.

- Skill: `thattimc/presales-with-docs` (Agent Skill, multi-file: 13 files)
- Install (CLI): `npx skillmds@latest add thattimc/presales-with-docs`
- Raw SKILL.md: https://api.skillmd.com/api/skills/thattimc/presales-with-docs/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Product & Planning
- Author: thattimc (https://skillmd.com/u/thattimc)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/thattimc/presales-with-docs

---


# Presales with Docs

Guide a client conversation from desired outcome to a reviewable, non-binding ballpark.
The presales operator owns the meeting and every commercial approval.

## Start

1. Read [references/live-discovery.md](references/live-discovery.md). Ingest supplied
   requirements before asking anything. Ask the operator whether the conversation is
   client-visible or private, then create `<client-slug>-presales/discovery-record.md`
   from the reference template. State that this is discovery for an indicative ROM.
   **Complete when:** visibility is known and the record contains every fact already
   available from supplied material.

2. Ask: **“What outcome would make this project successful for you?”** Ask exactly one
   client-facing question, then wait. Honor operator controls: `park`, `skip`, `revisit`,
   `summarize`, `private checkpoint`, and `end discovery`.
   **Complete when:** the client has answered or the item is explicitly parked.

## Discovery loop

3. Update `discovery-record.md` after every answer: confirmed facts, client decisions,
   assumptions, exclusions, unresolved items, and conflicts remain distinct. Choose the
   next question by this order: conflict, readiness blocker, largest estimate swing,
   then output detail. Ask one question and wait. Offer a recommended answer only when
   the operator or client needs options; label it as a recommendation.
   **Complete when:** every readiness-gate field is confirmed, assumed with a stated
   basis, or recorded as non-blocking, and no blocking conflict remains.

4. Present one scope checkpoint: outcomes, scope in/out, work breakdown, assumptions,
   unresolved items, and proposed effort ranges. Ask the operator for one confirmation.
   Revise through the discovery loop when they reject it.
   **Complete when:** the operator explicitly approves the estimate basis.

## Ballpark

5. Read [references/estimate-input.md](references/estimate-input.md). Build the JSON input
   from the approved basis and controlled sources. For a Notion-backed rate card, also read
   [references/notion-rate-card.md](references/notion-rate-card.md), load an approved/effective card
   into a private snapshot, and map every estimate role to one composite rate key. Use the
   inline rate card only as the documented fallback. Keep tokens, private rates, snapshots,
   and role math out of client-visible conversation.
   **Complete when:** every service line has role, day range, rate-card match, and basis;
   snapshot provenance verifies when used; every external cost has source and as-of date;
   timeline has a stated basis.

6. Run the deterministic calculator in draft mode:

   ```bash
   python3 "<this skill dir>/scripts/calculate_ballpark.py" estimate.json \
     --output-dir ./ballpark-output
   ```

   When step 5 produced a Notion snapshot, add
   `--rate-card-snapshot ./private/rate-card-snapshot.json`. Never run the loader in a
   client-visible terminal.

   Validation errors return to the discovery loop. Review `internal-estimate.md` privately;
   the client artifact contains totals but no day rates.
   **Complete when:** every total traces to an input line and the operator accepts the
   range, confidence, assumptions, exclusions, contingency, and validity period.

7. Ask one approval question: **“Do you approve this ROM for client discussion?”** After
   explicit approval, record the human reviewer:

   ```bash
   python3 "<this skill dir>/scripts/calculate_ballpark.py" estimate.json \
     --output-dir ./ballpark-output --approved-by "Reviewer name"
   ```

   Present `client-ballpark.md`. If approval is withheld, present the discovery summary
   and missing decisions instead.
   **Complete when:** approved output names its reviewer, or the session ends without a
   commercially usable estimate.

## Hard gates

- A ballpark is a range. The client artifact states ROM status, confidence, basis,
  assumptions, exclusions, contingency, validity, unresolved items, and non-binding use.
- Critical unknowns stay in `blocking_unknowns`; the calculator refuses an estimate.
- Services, one-time infrastructure, and recurring cloud/BAU remain separate totals.
- Keep private rates, margins, discounts, and role-level math in internal artifacts.
- Fetch Notion rates through the read-only deterministic loader, not through model context.
- Reject changed snapshots, ambiguous active versions, mixed currency, and missing mappings.
- The calculator performs arithmetic; the model performs discovery and decomposition.

For a complete synthetic run, read [examples/sample-session.md](examples/sample-session.md)
and use [examples/sample-estimate.json](examples/sample-estimate.json).