account-research
**Duration:** 20–40 minutes per account **Output:** `outputs/[date]-[account]-research.md`
**Duration:** 15–30 minutes per account (or run in batch) **Output:** ICP score + tier assignment saved to CRM or `outputs/scoring/`
$ npx -y skills add karlraf/gtm-starter-kit --skill icp-scoring --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/icp-scoringContext preview
The summary Claude sees to decide when to auto-load this skill.
**Duration:** 15–30 minutes per account (or run in batch) **Output:** ICP score + tier assignment saved to CRM or `outputs/scoring/`
**Duration:** 15–30 minutes per account (or run in batch) **Output:** ICP score + tier assignment saved to CRM or `outputs/scoring/`
---
Single account:
Read skills/icp-scoring/SKILL.md and score [company.com] against our ICP
Batch:
Read skills/icp-scoring/SKILL.md and context/icp-definition.md. Score these companies and output a table sorted by score, Tier 1 flagged: [paste list of company names or domains]
---
Score any account against your ICP and assign it to the right tier. Replaces gut feel with a repeatable model. When run at scale, it tells you which accounts to prioritize this week, which to monitor, and which to skip entirely.
---
Scores go stale. Set a recurring schedule:
| Segment | Frequency | Why | |---------|-----------|-----| | Full account list | Quarterly | ICP drift, new signal data | | Tier 1 accounts | Monthly | High-value; worth tracking closely | | Active pipeline | After each campaign | Campaign results reveal scoring gaps | | After ICP change | Immediately | Find newly qualified or disqualified accounts |
After a quarterly re-score, pull the delta: which accounts moved tiers? Accounts that dropped from Tier 1 to Tier 2 need to be removed from AE pipelines. Accounts that moved up need to be activated.
---
---
Measure how well the account matches your ideal customer profile.
| Criterion | Points | How to assess | |-----------|--------|---------------| | Employee count in range | 0–10 | [Your range from ICP definition] | | Industry match | 0–10 | Primary = 10, Secondary = 5, Other = 0 | | Funding stage match | 0–10 | Ideal stage = 10, Adjacent = 5, Outside = 0 |
| Criterion | Points | How to assess | |-----------|--------|---------------| | Uses [key integration tool] | 0–10 | Confirms workflow match | | Uses [secondary tool] | 0–5 | Confirms sophistication level | | No [disqualifying tool] | 0–5 | Absence of competitive blocker |
| Criterion | Points | How to assess | |-----------|--------|---------------| | Has [key role/function] | 0–10 | Confirms decision-maker exists | | [Role] hired in last 12 months | 0–5 | New leader = change appetite | | Hiring for [relevant role] | 0–5 | Active investment in function |
---
Add points for active signals from `context/signal-library.md`. Reference the point values defined there.
**Note:** Signal scores decay over time. Apply the decay multipliers from `context/signal-library.md` — a signal at 91–180 days is worth 25% of its original value; at 180+ days it expires entirely.
---
| Total | Tier | Action | |-------|------|--------| | 80–100 | Tier 1 | Immediate outreach, full research (run Account Research skill), assign to AE | | 60–79 | Tier 2 | Signal-triggered sequence within 48 hours | | 40–59 | Tier 3 | Add to automated sequence | | 20–39 | Tier 4 | Monitor, re-score in 90 days | | 0–19 | Exclude | Remove from active list |
---
When scoring a large list (50+ accounts), structure the output as a table:
| Account | Domain | Firmographic | Technographic | Org | Signal | Total | Tier | Action |
Instruct Claude:
Read skills/icp-scoring/SKILL.md and context/icp-definition.md. Score the accounts in [file or pasted list]. Output a scored table sorted by total score descending. Flag any accounts scoring 80+ for immediate follow-up.
---
# ICP Score: [Company Name] Date scored: [YYYY-MM-DD] Scored by: [Claude / Name] ## Score Breakdown | Category | Score | Max | Notes | |----------|-------|-----|-------| | Firmographic fit | X | 30 | [Key observations] | | Technographic fit | X | 20 | [Key observations] | | Organizational fit | X | 20 | [Key observations] | | Active signals | X | 30 | [Signals present] | | **Total** | **X** | **100** | | ## Tier Assignment: [Tier 1 / 2 / 3 / 4 / Exclude] ## What Qualifies Them - [Specific reason 1] - [Specific reason 2] ## What Disqualifies or Reduces Score - [Gap 1 — what would need to change for this to be a higher tier] ## Recommended Next Action [Specific: which skill to run next, which sequence to assign, or what to monitor] ## Re-score Trigger [Condition that should trigger re-scoring — e.g., "If they raise a new round" or "If they hire a VP of Ops"]
---
Scoring models drift. Thresholds that made sense when you had 20 deals may not hold after 100. Run a calibration review quarterly, or immediately if scored tiers consistently don't match outcomes.
Export all accounts scored in the last 90 days with:
If you use CRM tracking, pull from there. If scores live in `outputs/scoring/`, compile manually.
Built by The Revenue Architects — a GTM engineering firm based in San Francisco.
**Duration:** 20–40 minutes per account **Output:** `outputs/[date]-[account]-research.md`
**Duration:** 15–30 minutes (including your review) **Run once:** When you first clone this repo **Output:** All context files…
**Duration:** 2–4 hours per campaign **Output:** `outputs/campaigns/[date]-[campaign-name]/`
**Duration:** 10–15 minutes **Cadence:** Weekly (Monday morning recommended) **Output:** Updated context files + a brief change…