Client Discovery
Take a client's raw list of requests and produce a structured scoping breakdown with categories, hours, pricing, dependencies, and recommended phases.
When to use
- Client sends a list of automation/AI tasks they want built
- "analyze requests from [client]"
- "scope this project"
- "estimate hours for [client]"
- "create proposal breakdown"
- Before a discovery/scoping call — to come prepared with estimates
Dependencies
- Other skills:
query-leads (CRM data), client-workspace (for shared docs)
- External: none (this is an analysis skill, no scripts)
How to execute
Step 1: Gather inputs
- Client's raw request list — from TG, email, call notes, or shared doc
- Client's tech stack — CRM, ATS, tools they use (from CRM notes or questionnaire)
- Company context — from CRM: size, industry, budget signals
Step 2: For each request item, analyze
For every item in the client's list, produce:
| Field |
Description |
| Name |
Short name (2-5 words) |
| Category |
agent / automation / integration / knowledge-base / product |
| What client wants |
Plain language — what outcome they expect |
| What needs to be built |
Technical: APIs, triggers, LLM prompts, data flows |
| Key questions |
What we need to clarify before building |
| Integrations |
Which tools/APIs: CRM, ATS, LinkedIn, Bluedot, etc. |
| Complexity |
low (prompt eng, 4-6h) / medium (integration, 6-10h) / high (multi-system, 10-15h) |
| Hours estimate |
Range: low-high |
| Dependencies |
Other items that should be built first |
Step 3: Prioritize
Group items into:
- Quick wins (low complexity, high impact) — do first, show value fast
- High ROI (medium complexity, core business impact) — second phase
- Strategic (high complexity, long-term value) — third phase
- Can skip / already exists — tools like NotebookLM that solve it out of the box
Step 4: Check for off-the-shelf solutions
Before estimating custom build hours, check if an existing tool already does it:
- NotebookLM for knowledge bases
- Zapier/Make for simple automations
- Existing SaaS (Fireflies for transcription, Clay for signal tracking, etc.)
Flag these as "buy vs build" decisions with the client.
Step 5: Produce summary table
| # | Request | Hours | $ | Phase | Notes |
|---|---------|-------|---|-------|-------|
| 1 | Job posting AI | 4-6 | 400-600 | Quick win | Few-shot prompting |
| 2 | CRM automation | 8-12 | 800-1200 | Phase 2 | Needs API access |
...
| TOTAL | | 60-90 | $6K-9K | | |
Step 6: Generate discovery questions
Based on gaps in the analysis, generate a pre-call questionnaire:
- Questions about tech stack and data
- Questions about priorities and budget
- Questions about team and users
Use client-workspace skill to create a shared Google Doc with these questions.
Rate Card
| Service |
Rate |
| Consulting / implementation |
$100/hr, 15-min increments ($25 min) |
| Quick win (4-6h) |
$400-600 |
| Medium project (6-12h) |
$600-1200 |
| Complex project (10-15h) |
$1000-1500 |
Output Format
The analysis should be saved as:
- CRM activity — summary in activities.csv
- Shared doc — if questionnaire created, in client's Discovery folder
- Text summary — shown to Ivan for review before the call
Checklist
Examples
Client J (2026-03-04)
Client: Diana Prince, Client J (IT recruiting, 22 years experience)
Stack: Recruitee (ATS), Streak (CRM), Bluedot (call recording)
11 automation requests → analyzed into 4 blocks:
- Block 1: CRM & Sales (18-27h, $1.8-2.7K)
- Block 2: Recruiting process (16-22h, $1.6-2.2K)
- Block 3: Knowledge base (13-20h, $1.3-2K) — partly solved by NotebookLM
- Block 4: Client-facing products (14-22h, $1.4-2.2K)
Total: 61-91h, $X-YK
Related skills
client-workspace — create shared docs for discovery
call-prep — prepare for the discovery/scoping call
query-leads — CRM data lookup
1---2name: client-discovery3description: Analyze client automation/AI requests into structured scoping with hours, pricing, and priorities4---5# Client Discovery
6
7> Take a client's raw list of requests and produce a structured scoping breakdown with categories, hours, pricing, dependencies, and recommended phases.
8
9## When to use
10
11- Client sends a list of automation/AI tasks they want built
12- "analyze requests from [client]"
13- "scope this project"
14- "estimate hours for [client]"
15- "create proposal breakdown"
16- Before a discovery/scoping call — to come prepared with estimates
17
18## Dependencies
19
20- Other skills: `query-leads` (CRM data), `client-workspace` (for shared docs)
21- External: none (this is an analysis skill, no scripts)
22
23## How to execute
24
25### Step 1: Gather inputs
26
271. **Client's raw request list** — from TG, email, call notes, or shared doc
282. **Client's tech stack** — CRM, ATS, tools they use (from CRM notes or questionnaire)
293. **Company context** — from CRM: size, industry, budget signals
30
31### Step 2: For each request item, analyze
32
33For every item in the client's list, produce:
34
35| Field | Description |
36|-------|-------------|
37| **Name** | Short name (2-5 words) |
38| **Category** | `agent` / `automation` / `integration` / `knowledge-base` / `product` |
39| **What client wants** | Plain language — what outcome they expect |
40| **What needs to be built** | Technical: APIs, triggers, LLM prompts, data flows |
41| **Key questions** | What we need to clarify before building |
42| **Integrations** | Which tools/APIs: CRM, ATS, LinkedIn, Bluedot, etc. |
43| **Complexity** | `low` (prompt eng, 4-6h) / `medium` (integration, 6-10h) / `high` (multi-system, 10-15h) |
44| **Hours estimate** | Range: low-high |
45| **Dependencies** | Other items that should be built first |
46
47### Step 3: Prioritize
48
49Group items into:
50
511. **Quick wins** (low complexity, high impact) — do first, show value fast
522. **High ROI** (medium complexity, core business impact) — second phase
533. **Strategic** (high complexity, long-term value) — third phase
544. **Can skip / already exists** — tools like NotebookLM that solve it out of the box
55
56### Step 4: Check for off-the-shelf solutions
57
58Before estimating custom build hours, check if an existing tool already does it:
59- NotebookLM for knowledge bases
60- Zapier/Make for simple automations
61- Existing SaaS (Fireflies for transcription, Clay for signal tracking, etc.)
62
63Flag these as "buy vs build" decisions with the client.
64
65### Step 5: Produce summary table
66
67```
68| # | Request | Hours | $ | Phase | Notes |
69|---|---------|-------|---|-------|-------|
70| 1 | Job posting AI | 4-6 | 400-600 | Quick win | Few-shot prompting |
71| 2 | CRM automation | 8-12 | 800-1200 | Phase 2 | Needs API access |
72...
73| TOTAL | | 60-90 | $6K-9K | | |
74```
75
76### Step 6: Generate discovery questions
77
78Based on gaps in the analysis, generate a pre-call questionnaire:
79- Questions about tech stack and data
80- Questions about priorities and budget
81- Questions about team and users
82
83Use `client-workspace` skill to create a shared Google Doc with these questions.
84
85## Rate Card
86
87| Service | Rate |
88|---------|------|
89| Consulting / implementation | $100/hr, 15-min increments ($25 min) |
90| Quick win (4-6h) | $400-600 |
91| Medium project (6-12h) | $600-1200 |
92| Complex project (10-15h) | $1000-1500 |
93
94## Output Format
95
96The analysis should be saved as:
971. **CRM activity** — summary in activities.csv
982. **Shared doc** — if questionnaire created, in client's Discovery folder
993. **Text summary** — shown to Ivan for review before the call
100
101## Checklist
102
103- [ ] All client request items analyzed and categorized
104- [ ] Hours and pricing estimated for each item
105- [ ] Off-the-shelf alternatives checked
106- [ ] Items prioritized into phases
107- [ ] Discovery questions generated for unknowns
108- [ ] Summary table produced
109- [ ] CRM activity logged
110
111## Examples
112
113### Client J (2026-03-04)
114
115Client: Diana Prince, Client J (IT recruiting, 22 years experience)
116Stack: Recruitee (ATS), Streak (CRM), Bluedot (call recording)
11711 automation requests → analyzed into 4 blocks:
118- Block 1: CRM & Sales (18-27h, $1.8-2.7K)
119- Block 2: Recruiting process (16-22h, $1.6-2.2K)
120- Block 3: Knowledge base (13-20h, $1.3-2K) — partly solved by NotebookLM
121- Block 4: Client-facing products (14-22h, $1.4-2.2K)
122Total: 61-91h, $X-YK
123
124## Related skills
125
126- `client-workspace` — create shared docs for discovery
127- `call-prep` — prepare for the discovery/scoping call
128- `query-leads` — CRM data lookup