agentmods.dev

deepline-gtm

deepline-gtm is a skill for Claude Code, Codex from getaero-io/gtm-eng-skills. It costs 332 tokens per session (3,671 once invoked), scanned A, original, MIT.

A collection of instructions and command-line tools for go-to-market work, including prospecting, contact research, enrichment, and outreach workflows. Go-to-market means finding potential customers and engaging them.

In plain words
What is it for?
Use it to discover companies and people, enrich records, build prospecting workflows, compare data providers, and automate repeatable sales tasks.
Why use it?
It gives these tasks a documented process and provider-specific rules, reducing guesswork when choosing searches or running workflows.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 71repo +2 changed yesterday A scan SkillSpector: warn 332 tokens original MIT

Good fit Use it to discover companies and people, enrich records, build prospecting workflows, compare data providers, and automate repeatable sales tasks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/getaero-io/gtm-eng-skills/deepline-gtm
View source ↗ getaero-io/gtm-eng-skills code.deepline.com
Install

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.

Any agent
npx skills add getaero-io/gtm-eng-skills --skill deepline-gtm
Clone the repo
git clone --depth 1 https://github.com/getaero-io/gtm-eng-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for deepline-gtm

README.md
[![agentmods](https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/deepline-gtm/github.svg)](https://agentmods.dev/skills/getaero-io/gtm-eng-skills/deepline-gtm)
Your own site
<a href="https://agentmods.dev/skills/getaero-io/gtm-eng-skills/deepline-gtm"><img src="https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/deepline-gtm/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.

agentmods 80×15 button for deepline-gtm

Your own site · 80×15
<a href="https://agentmods.dev/skills/getaero-io/gtm-eng-skills/deepline-gtm"><img src="https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/deepline-gtm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 332 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,671 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 15 findings, up to high

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • high Rogue Agent · line 31
    Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.
    Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
  • high Rogue Agent · line 163
    Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.
    Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
  • high Rogue Agent · line 164
    Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.
    Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
  • high Rogue Agent · line 165
    Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.
    Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
  • high Rogue Agent · line 166
    Skill modifies its own code, configuration, or behavior at runtime. Self-modification enables an agent to escalate privileges, disable safety constraints, or install persistent backdoors.
    Fix: Prevent the skill from modifying its own code, SKILL.md, or configuration files. Treat skill files as read-only at runtime.
  • medium Excessive Agency · line 65
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Excessive Agency · line 97
    Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.
    Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
  • medium Memory Poisoning · line 116
    Skill attempts to fill the context window with filler content, displacing legitimate instructions and safety constraints. This can degrade agent performance or bypass safety boundaries.
    Fix: Implement context-window management that detects and rejects padding or stuffing attempts. Prioritize system instructions over user-injected content.
  • medium Prompt Injection · line 116
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 116
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 118
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 118
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 120
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 121
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
  • medium Prompt Injection · line 131
    Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.
    Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00332 $0.03671
Opus 5.5 $0.00133 $0.01468
Sonnet 5.5 $0.00066 $0.00734
Haiku 4.5 $0.00033 $0.00367

Measured yesterday against content hash bb5718372d25, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

deepline-gtm 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 yesterday.

The scan reads SKILL.md. This mod also ships 1 executable file (claude-deepline-statusline.mjs), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/deepline-gtm/SKILL.md · 301 lines

How it starts

The opening of the file, as written. The whole thing — 301 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Deepline GTM

Deepline is a GTM tool routing and automation platform for any ad-hoc or automated GTM task, with thousands of tools for prospecting, enrichment, research, agentic work, and more.

First

Start with a task to complete. Run

deepline billing balance && deepline search "<input you have -> result you need>"

to get the current balance and the relevant tools with their prices. If deepline is not found, install it by following https://code.deepline.com/INSTALL.md. If search fails, follow the printed instructions.

Search and help are how you learn Deepline. Search finds what to run; deepline <command> --help explains how to run it: its purpose, inputs, outputs and cost, with --verbose for field-level detail. Read a command's help before you first use it. deepline --help lists every command.

Final message: read before you reply

Users expect a consistent, familiar experience with Deepline, so always keep these sections in this order:

## Deepline Results

<A compact paragraph or two with useful context, sources, caveats and Deepline
spend. Put any extra explanation here, above the table.>

**Tools Used:**
- [<play name>](https://code.deepline.com/dashboard/plays/<play name, URL-encoded>): <what it did, in a few words>
- <tool name>: <what it did, in a few words>

**<result noun: Contacts, Emails, Companies, Signals, etc>:**
[<file name>](<path to the full CSV or artifact>)
| <high-signal columns> |
| --- |
| <rows> |

**Next steps:** <A useful next step or automation offer, e.g. "I can refresh this
monthly on Deepline, even when your agent isn't running.">

**Bottom line:** <The concrete outcome, e.g. "Found **validated work emails for
18/20 leads**; **2 remain unresolved**.">

Rules:

  1. Start with ## Deepline Results. Put nothing before it.
  2. ## Deepline Results is the only heading. Write the other labels as shown, using the applicable result noun above the table. Always keep the sections in this order, with **Bottom line:** last.
  3. List Plays first. Link each Play to its play page, https://code.deepline.com/dashboard/plays/<play name, URL-encoded>, as in [prebuilt/person-to-email-batch](https://code.deepline.com/dashboard/plays/prebuilt%2Fperson-to-email-batch). List tools after the Plays.
  4. Keep every sentence brief. Every word earns its keep. Give each detail once.
  5. Scale the opening paragraph or two to the job. Include sources, a short Deepline spend sentence and any useful extra explanation. Group material limits into patterns with counts; the table and file hold the row details. Include before-and-after improvements when measured.
  6. Report what you found, how many, and what is missing. Focus on findings and coverage that help the user decide what to do.
  7. Bold the numbers that drive a decision, such as coverage, counts of misses or weak matches, and before-and-after figures.
  8. In the table, show every row the user asked to see. Use the inputs they gave and the outputs they asked for. For a large result, show labeled sample rows. The file link holds the full data. Link only files and pages that exist.
  9. Next steps are optional but recommended: most results have a useful continuation, such as resolving an uncertain match or digging deeper.
  10. Research, discovery and enrichment are usually repeatable. Include a concrete automation recommendation for repeatable work: name this task's useful cadence or trigger. Offer the automation for the user to authorize under **Next steps:**. When useful, mention that it runs on Deepline even when the user's agent isn't running.
  11. Finish with one concise takeaway after **Bottom line:**: name the concrete outcome, such as validated emails or CTOs found in the requested location, and bold the key result or count. Use a second sentence for a material limitation. Users often see the end first, so put the most important takeaway here.

Read the full file on GitHub · 301 lines

Files

What ships with it

60 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.

Changes

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.

  1. yesterday Changed · +8 lines bb5718372d25
  2. 2d ago Changed · +16 lines · -1 tokens per session c1ef57ac905c
  3. 5d ago Changed · +5 lines · +1 tokens per session b7e4d00572e6
  4. 7d ago Changed · +3 lines · +2 tokens per session 872093df52f7
  5. 8d ago Changed · +7 lines · -2 tokens per session fedab2f26aee
  6. 9d ago Changed · +7 lines · -1 tokens per session ae6a7fc09724
  7. 12d ago Changed · -2 lines d5a13f73253d
  8. 13d ago Changed · -50 lines 3e2babd75367
  9. 14d ago Changed 9d8764d183c5
  10. 16d ago First seen · 307 lines · 333 tokens per session scan A 175ce5dc7426

Subscribe to this mod's changes

deepline-gtm is a skill published in the GitHub repository getaero-io/gtm-eng-skills (71 stars, last pushed yesterday), licensed MIT. It adds 332 tokens to every session and 3,671 once invoked, about $0.0013 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.

Claude CodeMarketing and SEOclaude-skillsenrichmentgtmlead-generationsales-automation
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