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 getaero-io/gtm-eng-skills --skill deepline-startgit clone --depth 1 https://github.com/getaero-io/gtm-eng-skillsWrote 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/getaero-io/gtm-eng-skills/deepline-start)<a href="https://agentmods.dev/skills/getaero-io/gtm-eng-skills/deepline-start"><img src="https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/deepline-start/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/getaero-io/gtm-eng-skills/deepline-start"><img src="https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/deepline-start.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 | $0.00058 | $0.02561 |
| Opus 5.5 | $0.00023 | $0.01024 |
| Sonnet 5.5 | $0.00012 | $0.00512 |
| Haiku 4.5 | $0.00006 | $0.00256 |
Grade A, and why
deepline-start 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 today.
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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discover a Deepline GTM workflow
Quick Start
npm install -g deepline
deepline -h
Use a one-question-at-a-time interview to turn an unclear GTM need into a
specific, executable Deepline plan. This skill adapts the grilling interview
pattern; it does not require that skill to be installed.
Route first
Start this interview only when the user explicitly invokes deepline-start.
Do not invoke it automatically for unclear GTM requests or from another skill.
When the user invokes this skill, keep the discovery and confirmation flow.
If the outcome, inputs, and scope are already clear, skip redundant questions
and propose the plan for confirmation. For a specific execution request that
did not invoke this skill or ask for discovery, use its owning skill directly.
deepline-gtm is the generalist for GTM implementation. A specialist leads
when its narrower job is the user's actual goal; it may route back to
deepline-gtm for execution.
| Emerging need | Likely owner | What to verify before recommending |
|---|---|---|
| Find accounts or people, enrich a list, write outreach, or automate row work | deepline-gtm |
Input identifiers, target criteria, useful output, and batch size |
| Build a TAM, source a portfolio, map an account, or find qualified roles | deepline-gtm recipe |
Which established recipe matches the target and available identifiers |
| Watch for new hiring, funding, or other provider events | deepline-gtm monitor route |
Event definition, cadence, downstream action, and access |
| Discover public/private sources, current market language, or provider coverage | deepline-research |
Research question, evidence needed, recency, and source access |
| Learn ICP signals, audit won/lost evidence, or score accounts/leads | deepline-scoring |
Decision, population, labels or approved rules, and evaluation goal |
| Answer a funnel, pipeline, or RevOps metric question | deepline-analytics |
Metric, period, grain, and governed data source |
| Build or upload an ads audience | deepline-ads-audiences |
Platform, audience, suppression, data rights, and destination |
| Turn a defined state machine into a durable Play | deepline-engine |
States, transitions, inputs, and outputs |
| Review and improve existing Play results with a human | deepline-plays-review |
Play/run, review surface, and acceptance criteria |
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.
- today Changed · -1 lines f1701219d9ff
- yesterday Changed 1a50a61a8341
- 2d ago First seen · 200 lines · 58 tokens per session scan A 59c4df725f56
deepline-start is a skill published in the GitHub repository getaero-io/gtm-eng-skills (68 stars, last pushed today), licensed MIT. It adds 58 tokens to every session and 2,561 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 2026-10-15.
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