weekly-gtm-report

# Weekly GTM Report

Generate a structured weekly GTM performance report by reading data from the local `docs/` directory and optional CRM exports. Produces an executive-ready summary with metrics, highlights, week-over-week trends, and recommended actions.

## Tools Used

- **Read** — load pipeline data, signal reports, account briefs, sequence configs, battlecards, meeting prep notes, CRM CSV exports, and previous reports
- **Write** — save the weekly report and update the reports index
- **Glob** — discover available data files across `docs/` subdirectories
- **Bash** — date calculations (week number, date ranges)

## Methodology

Follow these steps in order. Do not skip steps. Do not fabricate metrics. If data is missing for a section, include the section with a "No data available" note and a suggestion for how to populate it.

### Step 1: Data Collection

Ask the user:

> What week is this report for? (default: current week)

Use Bash to compute the ISO week number and Monday-to-Friday date range for the target week.

Then scan the `docs/` directory for available data sources. Run these searches:

```
Glob: docs/pipeline/scored-leads.md
Glob: docs/signals/*.md
Glob: docs/accounts/*.md
Glob: docs/sequences/*.md
Glob: docs/battlecards/*.md
Glob: docs/meeting-prep/*.md
Glob: docs/reports/week-*.md
```

Also ask the user:

> Do you have a CRM export CSV for this week? If so, provide the file path.

Read every file that exists. For each data source found, summarize what was loaded (file count and date range of contents). For each data source NOT found, note it as unavailable. Present the summary to the user before proceeding:

> **Data loaded:**
> - Pipeline: scored-leads.md (12 leads, last updated 2026-03-07)
> - Signals: 4 signal reports found
> - Sequences: not found
> - Battlecards: 3 battlecards found
> - Meeting prep: not found
> - Previous reports: 2 found (latest: week-2026-W10)
>
> I'll build the report from what's available. Missing sections will note what data is needed.

### Step 2: Pipeline Summary

**Requires:** `docs/pipeline/scored-leads.md`

If the pipeline file exists, extract and present:

1. **Total leads by tier** — count of HOT, WARM, COLD, and PARK leads
2. **Movement since last report** — compare against the previous week's report (if one exists in `docs/reports/`). Identify leads that were upgraded, downgraded, newly added, or closed/removed
3. **Pipeline velocity** — if date-added or last-scored timestamps exist, calculate average days a lead has spent in its current tier
4. **Top 5 hottest leads** — the five highest-scoring leads with their composite scores, strongest signal, and recommended next action

Format as a table:

| Tier | Count | Change vs Last Week |
|------|-------|---------------------|
| HOT  | {n}   | {+/- or "new"}      |
| WARM | {n}   | {+/- or "new"}      |
| COLD | {n}   | {+/- or "new"}      |
| PARK | {n}   | {+/- or "new"}      |

**If not found:** Note "No pipeline data available. Run the Qualification Scorer skill to generate `docs/pipeline/scored-leads.md`."

### Step 3: Outreach Activity

**Requires:** `docs/sequences/*.md` or CRM export CSV

If sequence files or CRM data exist, extract:

1. **Active sequences** — list each sequence by name, status (active/paused/completed), and contacts enrolled
2. **Messages sent by channel** — email, LinkedIn, phone. Aggregate totals for the week
3. **Response rates** — replies received divided by messages sent, broken down by channel if data permits
4. **Highlights** — best performing sequence (highest response rate) and best individual response (most promising reply or conversion)

Format as a table:

| Channel  | Sent | Replies | Response Rate |
|----------|------|---------|---------------|
| Email    | {n}  | {n}     | {n}%          |
| LinkedIn | {n}  | {n}     | {n}%          |
| Phone    | {n}  | {n}     | {n}%          |

**If not found:** Note "No outreach data available. Run the Outreach Sequence Builder skill to create sequences at `docs/sequences/`, or provide a CRM export CSV."

### Step 4: Signals Detected

**Requires:** `docs/signals/*.md`

If signal files exist, extract:

1. **New signals this week** — filter signal reports to those with detection dates within the target week. Present as a table:

| Company | Signal Type | Date | Score | Source |
|---------|-------------|------|-------|--------|
| {name}  | {type}      | {date}| {n}/20 | [{source}]({url}) |

2. **Signal trends** — compare against previous weeks if older signal files exist. Are funding signals increasing? Hiring signals? Competitor churn? Note any shifts
3. **Recommended actions** — for the top 3 highest-scoring new signals, provide a specific next step (e.g., "Acme Corp raised Series B last Tuesday. Reach out to their new VP Sales this week with a congrats + value angle.")

**If not found:** Note "No signal data available. Run the Signal Scanner skill to populate `docs/signals/`."

### Step 5: Meetings and Research

**Requires:** `docs/meeting-prep/*.md` and/or `docs/accounts/*.md`

If meeting prep or account files exist, extract:

1. **Meetings held this week** — list each meeting with company name, attendees (if noted), and date
2. **New accounts researched** — list account briefs created or updated this week (based on file modification dates)
3. **Key takeaways** — pull any outcomes, decisions, or insights noted in meeting prep files
4. **Follow-up actions outstanding** — extract any action items, next steps, or commitments mentioned in meeting notes that have not been marked complete

Format as a table:

| Date | Company | Type | Key Takeaway | Follow-Up |
|------|---------|------|--------------|-----------|
| {date} | {name} | {meeting/research} | {one line} | {action item} |

**If not found:** Note "No meeting or account research data available. Use the Meeting Prep Brief skill to generate `docs/meeting-prep/` files, or the Account Research Brief skill for `docs/accounts/`."

### Step 6: Competitive Updates