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 shalintripathi/saas-marketing-agents --skill abm-opsgit clone --depth 1 https://github.com/shalintripathi/saas-marketing-agentsWrote 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/shalintripathi/saas-marketing-agents/abm-ops)<a href="https://agentmods.dev/skills/shalintripathi/saas-marketing-agents/abm-ops"><img src="https://agentmods.dev/badge/skills/shalintripathi/saas-marketing-agents/abm-ops/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/shalintripathi/saas-marketing-agents/abm-ops"><img src="https://agentmods.dev/badge/skills/shalintripathi/saas-marketing-agents/abm-ops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00167 | $0.01475 |
| Opus 5.5 | $0.00067 | $0.00590 |
| Sonnet 5.5 | $0.00033 | $0.00295 |
| Haiku 4.5 | $0.00017 | $0.00147 |
Grade A, and why
abm-ops 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 2mo 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Account-Based Marketing Operations
Step 0 (always first): Load brand context
Before producing any deliverable, look for a brand-context.md file in the user's project root (also check ./.claude/brand-context.md and ./docs/brand-context.md). It holds the company's ICP, positioning, messaging pillars, citable proof, voice, banned words, and compliance constraints.
- If it exists: read it in full and treat it as binding for this run. Hand its contents to every specialist agent you route work to, alongside the task brief. Its "Rules for agents reading this file" section overrides an agent's own defaults.
- If it does not exist: say so, point the user at the template (
templates/brand-context.md), and offer to generate a filled draft by interviewing them or by reading their website and existing content. Then proceed with explicitly-labelled assumptions — never silently invented ones.
Non-negotiable regardless of which path applies: do not invent customer names, metrics, funding, integrations, certifications, or outcomes. Only proof recorded in brand-context.md (or supplied directly in the request) may be used as fact. Where a claim would help but no evidence exists, emit a [NEEDS INPUT: …] marker in the deliverable rather than a plausible-sounding guess. Account research is the highest-fabrication-risk work in this repo — firmographics, funding, headcount, tech stack, named contacts and "current initiatives" are all things an agent can invent fluently, and a wrong detail inside a personalized account program is worse than a missing one.
What This Is
Account-Based Marketing Operations owns the named account list itself — the artifact that paid media, outbound, events and content all execute into, and the one thing in a B2B SaaS marketing org that is usually assumed to exist and is nobody's job. It covers account selection from closed-won evidence, list sizing against real sales capacity, the 1:1 / 1:few / 1:many tier model, the signals-to-actions matrix, the multi-channel orchestration contract each tier runs on, the sales-pairing agreement behind it, and account-based measurement — coverage, penetration and pipeline from the list rather than lead volume.
What ships with it
1 file 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.
- 2mo ago First seen · 64 lines · 167 tokens per session scan A 899d0b2af8d7
abm-ops is a skill published in the GitHub repository shalintripathi/saas-marketing-agents (30 stars, last pushed yesterday), licensed MIT. It adds 167 tokens to every session and 1,475 once invoked, about $0.0007 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 2026-08-31.
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