prospect-scoring

Name: prospect-scoring
Author: Xuxchloris

17stars2forks

How to install prospect-scoring?

xuxchloris/export_skills/prospect-scoring

$npx -y skills add Xuxchloris/export_skills --skill prospect-scoring

Installs into the current project.

Summary

Use when a trade agent needs to rank, qualify, prioritize, segment, score, or reject overseas prospects based on product fit, channel value, decision-maker access, market relevance, and risk

Files · 1

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SKILL.md

1	# Prospect Scoring
2
3	## Overview
4
5	Score prospects with transparent evidence so the user knows who to contact first. The score is a decision aid, not a claim that the prospect is ready to buy.
6
7	## When to Use
8
9	Use this skill after `company-research` has produced facts and evidence for a prospect, or when the user uploads a prospect list and asks which companies deserve outreach.
10
11	Do not use it when there is no product context.
12
13	## Inputs
14
15	- Product context from `product-loader`
16	- Company research output
17	- Target market rules from `MARKET.yaml`
18	- Optional contact availability data
19
20	## Outputs
21
22	```json
23	{
24	"score": 0,
25	"priority": "A\|B\|C\|D",
26	"score_breakdown": {},
27	"recommended_action": "",
28	"evidence_status": "verified\|no_evidence\|fetch_failed",
29	"reason": "",
30	"evidence": [],
31	"risk_notes": []
32	}
33	```
34
35	## Procedure
36
37	1. Score product and category fit from 0 to 40.
38	2. Score channel value from 0 to 20.
39	3. Score decision-maker access from 0 to 15.
40	4. Score target-market value from 0 to 10.
41	5. Score website quality and business activity from 0 to 10.
42	6. Apply risk adjustment from 0 to -10 for weak evidence, unrelated business, suspicious contact data, or compliance concerns.
43	7. If evidence status is `fetch_failed` or `no_evidence`, cap priority at D and set `recommended_action` to `manual_review`.
44	8. If no product or channel evidence was fetched, do not assign A or B even when the market is relevant.
45	9. Assign priority:
46	- A: 80-100, contact first
47	- B: 60-79, contact after manual review
48	- C: 40-59, keep for monitoring or enrichment
49	- D: 0-39, do not contact
50	10. Provide a recommended next action.
51
52	## Verification
53
54	- Score breakdown totals equal final score.
55	- Priority matches the score range.
56	- A or B priority requires fetched evidence for product or channel fit.
57	- A-level prospects include at least two evidence points.
58	- D-level prospects are not recommended for outreach.
59	- Risk notes explain every deduction.
60
61	## Common Mistakes
62
63	\| Mistake \| Fix \|
64	\| --- \| --- \|
65	\| Giving high score because the company is large \| Product fit must carry the most weight \|
66	\| Ignoring missing decision-maker data \| Reflect it in the access score \|
67	\| Hiding risk deductions \| List each risk note \|
68	\| Treating score as purchase intent \| Explain that score means development priority \|

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prospect-scoring

17stars2forks

View on GitHub

How to install prospect-scoring?

xuxchloris/export_skills/prospect-scoring

$npx -y skills add Xuxchloris/export_skills --skill prospect-scoring

Installs into the current project.

Summary

Use when a trade agent needs to rank, qualify, prioritize, segment, score, or reject overseas prospects based on product fit, channel value, decision-maker access, market relevance, and risk

Files · 1

View on GitHub

SKILL.md

1	# Prospect Scoring
2
3	## Overview
4
5	Score prospects with transparent evidence so the user knows who to contact first. The score is a decision aid, not a claim that the prospect is ready to buy.
6
7	## When to Use
8
9	Use this skill after `company-research` has produced facts and evidence for a prospect, or when the user uploads a prospect list and asks which companies deserve outreach.
10
11	Do not use it when there is no product context.
12
13	## Inputs
14
15	- Product context from `product-loader`
16	- Company research output
17	- Target market rules from `MARKET.yaml`
18	- Optional contact availability data
19
20	## Outputs
21
22	```json
23	{
24	"score": 0,
25	"priority": "A\|B\|C\|D",
26	"score_breakdown": {},
27	"recommended_action": "",
28	"evidence_status": "verified\|no_evidence\|fetch_failed",
29	"reason": "",
30	"evidence": [],
31	"risk_notes": []
32	}
33	```
34
35	## Procedure
36
37	1. Score product and category fit from 0 to 40.
38	2. Score channel value from 0 to 20.
39	3. Score decision-maker access from 0 to 15.
40	4. Score target-market value from 0 to 10.
41	5. Score website quality and business activity from 0 to 10.
42	6. Apply risk adjustment from 0 to -10 for weak evidence, unrelated business, suspicious contact data, or compliance concerns.
43	7. If evidence status is `fetch_failed` or `no_evidence`, cap priority at D and set `recommended_action` to `manual_review`.
44	8. If no product or channel evidence was fetched, do not assign A or B even when the market is relevant.
45	9. Assign priority:
46	- A: 80-100, contact first
47	- B: 60-79, contact after manual review
48	- C: 40-59, keep for monitoring or enrichment
49	- D: 0-39, do not contact
50	10. Provide a recommended next action.
51
52	## Verification
53
54	- Score breakdown totals equal final score.
55	- Priority matches the score range.
56	- A or B priority requires fetched evidence for product or channel fit.
57	- A-level prospects include at least two evidence points.
58	- D-level prospects are not recommended for outreach.
59	- Risk notes explain every deduction.
60
61	## Common Mistakes
62
63	\| Mistake \| Fix \|
64	\| --- \| --- \|
65	\| Giving high score because the company is large \| Product fit must carry the most weight \|
66	\| Ignoring missing decision-maker data \| Reflect it in the access score \|
67	\| Hiding risk deductions \| List each risk note \|
68	\| Treating score as purchase intent \| Explain that score means development priority \|

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6 picks

Type