Agent-Skills.md

Agent Skills: Client Discovery

Analyze client automation/AI requests into structured scoping with hours, pricing, and priorities

UncategorizedID: aaaaqwq/claude-code-skills/client-discovery

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aaaaqwq/claude-code-skills
aAAaqwqLicense: MIT
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pnpm dlx add-skill https://github.com/aAAaqwq/AGI-Super-Team/tree/HEAD/skills/client-discovery

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skills/client-discovery/SKILL.md

Skill Metadata

Name
client-discovery
Description
Analyze client automation/AI requests into structured scoping with hours, pricing, and priorities

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

  1. Client's raw request list — from TG, email, call notes, or shared doc
  2. Client's tech stack — CRM, ATS, tools they use (from CRM notes or questionnaire)
  3. 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:

  1. Quick wins (low complexity, high impact) — do first, show value fast
  2. High ROI (medium complexity, core business impact) — second phase
  3. Strategic (high complexity, long-term value) — third phase
  4. 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:

  1. CRM activity — summary in activities.csv
  2. Shared doc — if questionnaire created, in client's Discovery folder
  3. Text summary — shown to Ivan for review before the call

Checklist

  • [ ] All client request items analyzed and categorized
  • [ ] Hours and pricing estimated for each item
  • [ ] Off-the-shelf alternatives checked
  • [ ] Items prioritized into phases
  • [ ] Discovery questions generated for unknowns
  • [ ] Summary table produced
  • [ ] CRM activity logged

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