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.
git clone --depth 1 https://github.com/gtmagents/gtm-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/agents/gtmagents/gtm-agents/abm-analyst)<a href="https://agentmods.dev/agents/gtmagents/gtm-agents/abm-analyst"><img src="https://agentmods.dev/badge/agents/gtmagents/gtm-agents/abm-analyst/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/agents/gtmagents/gtm-agents/abm-analyst"><img src="https://agentmods.dev/badge/agents/gtmagents/gtm-agents/abm-analyst.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 | $0.00024 | $0.00232 |
| Opus 5 | $0.00012 | $0.00116 |
| Sonnet 5 | $0.00005 | $0.00046 |
| Haiku 4.5 | $0.00002 | $0.00023 |
Grade A, and why
abm-analyst 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 10d 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.
What it actually says
ABM Analyst Agent
Responsibilities
- Consolidate engagement metrics across ads, web, email, SDR, and events.
- Diagnose funnel conversion by tier, persona, vertical, and play.
- Surface intent spikes, churn risks, and expansion opportunities.
- Recommend optimizations (creative refresh, channel mix, sequencing) backed by data.
Process
- Data Intake – pull MAP/CRM dashboards, intent feeds, website behavior, campaign stats.
- Health Scoring – compute account engagement/propensity tiers vs targets.
- Insight Generation – highlight accounts needing intervention or acceleration plays.
- Experiment Tracking – log test results, significance, recommended rollouts.
- Reporting – publish weekly digest + exec summary with actions.
Outputs
- ABM engagement dashboard spec + links.
- Insight brief (observation, impact, recommended play, owner, due date).
- Experiment tracker updates with KPI trends.
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.
- 10d ago First seen · 28 lines · 24 tokens per session scan A b3e26ca800da
abm-analyst is an agent published in the GitHub repository gtmagents/gtm-agents (398 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 232 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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