Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add WellApp-ai/Well --skill gtm-alignmentgit clone --depth 1 https://github.com/WellApp-ai/WellWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/wellapp-ai/well/gtm-alignment)<a href="https://agentmods.dev/skills/wellapp-ai/well/gtm-alignment"><img src="https://agentmods.dev/badge/skills/wellapp-ai/well/gtm-alignment.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.01798 |
| Opus 5 | $0.00009 | $0.00899 |
| Sonnet 5 | $0.00004 | $0.00360 |
| Haiku 4.5 | $0.00002 | $0.00180 |
Grade A, and why
gtm-alignment scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GTM Alignment Skill
Ensure implementation phasing aligns with go-to-market strategy by validating against persona tiers and estimating business value from KPI database.
CRITICAL: This skill MUST fetch real data from Notion. Do NOT make up personas or GTM tiers.
When to Use
- During Ask mode Phase 2 (CONVERGE), after dependency-mapping
- When prioritizing between equally-risky slices
- Before finalizing phase order
Notion Database IDs
| Database | ID | Purpose |
|---|---|---|
| Persona DB | 2b1c4d5e-7bea-80ee-85c2-fb96dfdcf98b |
Persona tiers, RICE scores, characteristics |
| GTM Strategy | 2b2c4d5e-7bea-809d-8c49-cc6b443738df |
Positioning, messaging, segments |
Note: If API-query-data-source fails, use API-post-search with query "Persona" as fallback.
Instructions
Phase 1: Fetch Persona Tiers (REQUIRED)
Primary method - Query database:
CallMcpTool:
server: user-notion
toolName: API-query-data-source
arguments: {"data_source_id": "2b1c4d5e-7bea-80ee-85c2-fb96dfdcf98b"}
Fallback method - Search (if query fails):
CallMcpTool:
server: user-notion
toolName: API-post-search
arguments: {"query": "Persona"}
STOP if BOTH methods fail. Report error and do not proceed with made-up data.
Extract from Persona DB:
- Persona name (title)
- RICE score (for prioritization)
- Goals, Pain points, Background
- Market segments
Build Tier Priority Table (sorted by RICE score):
| Tier | Persona | RICE Score | Key Traits |
|---|---|---|---|
| T1 | [Highest RICE from Notion] | [Score] | [Goals/Pain points] |
| T2 | [Second RICE from Notion] | [Score] | [Goals/Pain points] |
| T3 | [Third RICE from Notion] | [Score] | [Goals/Pain points] |
Evidence required: Show persona names and RICE scores from Notion
Phase 2: Fetch GTM Strategy (REQUIRED)
Primary method - Query database:
CallMcpTool:
server: user-notion
toolName: API-query-data-source
arguments: {"data_source_id": "2b2c4d5e-7bea-809d-8c49-cc6b443738df"}
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 8d ago First seen · 215 lines · 18 tokens per session scan A b4e90b3397f6
gtm-alignment is a skill published in the GitHub repository WellApp-ai/Well (340 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 1,798 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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