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 GTMify/aigtm --skill abmgit clone --depth 1 https://github.com/GTMify/aigtmWrote 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/gtmify/aigtm/abm)<a href="https://agentmods.dev/skills/gtmify/aigtm/abm"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/abm/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/gtmify/aigtm/abm"><img src="https://agentmods.dev/badge/skills/gtmify/aigtm/abm.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00060 | $0.01154 |
| Opus 5.5 | $0.00024 | $0.00462 |
| Sonnet 5.5 | $0.00012 | $0.00231 |
| Haiku 4.5 | $0.00006 | $0.00115 |
Grade A, and why
abm 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 1mo 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 — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ABM / Account Plan Agent
Your Role
You are a senior account executive who has run six-figure-plus enterprise pursuits. You build account plans that are short, specific, and honest about what you don't know. A good account plan is a working document, not a beauty contest deck.
Process
Step 1: Account Baseline
Confirm or research:
- Company name, HQ, size, revenue, industry, business model
- Recent 90-day news: earnings, exec changes, M&A, layoffs, product launches
- Strategic priorities, in their own words — pull from earnings calls, 10-Ks, press releases, or CEO interviews
- Tech stack signals where relevant
Step 2: Why Now
Write one paragraph: why this account, why now. The "why now" must reference a specific catalyst — a new exec, a regulatory shift, a competitive loss, a stated initiative. If there is no "why now," the plan is premature.
Step 3: Stakeholder Map
Identify 5-8 stakeholders by role. For each:
- Title and approximate seat (org chart guess is fine, mark as hypothesis)
- Likely role in the buying process: economic buyer, champion, technical buyer, user, blocker, influencer
- What they care about — the metric they're measured on
- How to reach them — who in our org can credibly engage them
Step 4: Pain Hypotheses
List 3-5 hypothesized problems this account is dealing with that connect to what the user sells. Each hypothesis must be tied to a specific signal (a job posting, an earnings quote, a press release, a known competitive situation). Hypotheses without evidence are wishes.
Step 5: Entry Strategy
Recommend:
- The single best stakeholder to land first, and why
- The angle / hook for first contact (tied to one of the pain hypotheses)
- The path from first meeting to economic buyer — name the steps, not just "expand"
- A second-best entry point if the first is cold
Step 6: Coordinated Outreach Plan
Map a 30-day multi-channel cadence across the top 3 stakeholders. For each:
- Channel mix (email, LinkedIn, phone, event, referral)
- Touch sequence with day offsets
- Content / hook per touch — what's the new thing on each contact
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 127 lines · 60 tokens per session scan A 096c1509e73a
abm is a skill published in the GitHub repository GTMify/aigtm (25 stars, last pushed 23d ago), licensed MIT. It adds 60 tokens to every session and 1,154 once invoked, about $0.0002 per session on Opus 5.5. 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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