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-ads-audiencesgit 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-ads-audiences)<a href="https://agentmods.dev/skills/getaero-io/gtm-eng-skills/deepline-ads-audiences"><img src="https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/deepline-ads-audiences/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-ads-audiences"><img src="https://agentmods.dev/badge/skills/getaero-io/gtm-eng-skills/deepline-ads-audiences.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to medium
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 →
- medium Memory Poisoning · line 99 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 99 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 99 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 123 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 119 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 119 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
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 | $0.00133 | $0.07323 |
| Opus 5.5 | $0.00053 | $0.02929 |
| Sonnet 5.5 | $0.00027 | $0.01465 |
| Haiku 4.5 | $0.00013 | $0.00732 |
Grade A, and why
deepline-ads-audiences 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 11d 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 — 339 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deepline Ads Audiences
Quick Start
npm install -g deepline
deepline -h
CLI resolution
Run deepline when it is available. If the shell reports that command is missing, use <workspace-root>/.deepline/runtime/bin/deepline (or the npm-created .cmd shim on Windows). If neither exists, follow https://code.deepline.com/INSTALL.md to set up Deepline.
Build high-quality ABM paid ads audiences from first-party customer or prospect lists. This skill is for paid ads audience upload and evaluation, not outbound.
Names in this skill are starting hints. Run deepline search "contact list -> ad platform custom audience" --type tools and deepline describe <tool_id> before executing because tool names and payload shapes can change. Tool search takes a task: one sentence stating the input you have -> the result you need, not keywords. There is no --prefix flag.
Before You Start
Match the request to a row in the decision matrix and read the linked file before acting. This skill is not for cold outbound, sequencing, or copywriting: personal emails here are used to improve paid ads matching, not to contact people directly.
Decision Matrix
| User says | Do this | Read |
|---|---|---|
| "max coverage", "highest match rate", "maximum match rate", "keep increasing coverage", "get to 75% coverage", exhaust LinkedIn/personal-email/hash options | Run the explicit max-coverage ladder with budget gates. | recipes/max-coverage-audience.md |
/deepline-ads-audience, "enrich and upload to FB/Google" |
Run the full paid ads audience recipe. | recipes/enrich-and-upload-facebook-google.md |
| "sample ABM segment", "do the example workflow" | Follow the reusable high-priority ABM segment recipe. | recipes/sample-abm-segment-example.md |
| "use ContactOut hashes", "hashed identifiers", "LinkedIn URLs to hashes" | Plan a bulk pass beside the ladder, not a waterfall step. | shared/contactout-hash-pool.md |
| "what is a hash", "why is my match rate low", first-time user | Explain the mechanic before quoting a plan. | shared/audience-basics.md |
encoded/internal-identifier LinkedIn URLs (/in/ACwAA…), "API rejected my LinkedIn URLs", "convert LinkedIn URLs" |
Normalize person_linkedin_url before upload: drop encoded, recover vanity. |
Step 4 → "Normalize LinkedIn URLs" (this file) |
| "Make sure hashes are not double hashed" | Run the no-double-hash audit play before upload. | plays/audit-no-double-hash.play.ts |
| "enrich this list", "buy personal emails/hashes", "run the ladder" | Run the waterfall. Each layer only sees rows still missing a hash. | plays/enrich-audience-waterfall.play.ts |
| "Compare enriched versus unenriched" | Build both hash-only datasets and report lift. | plays/enrich-audience-waterfall.play.ts |
| "include phone numbers", "add phones" | Hash existing phones digits-only with country code. | shared/upload-failure-modes.md |
| "what was the match rate", "did it match" | Read contactIdInfo.matchRatePercentage, not the range enum. |
shared/upload-failure-modes.md |
| "put it in a sheet", "customer will upload" | Publish the validated file to Sheets; verify by row count. | shared/upload-failure-modes.md |
| "connect Meta", "Meta not connected", "(#100)", "business_management" | Connect Meta with a system user token; Meta login is not offered. | shared/meta-connection.md |
| "upload keeps failing", "422", "audience is locked" | Meta locks on write. Send the audience in one call. | shared/upload-failure-modes.md |
| "Upload to Google" | Validate hash-only rows, create Google audience, sync, readback. | plays/upload-google-hash-only-audience.play.ts |
| "Upload to Facebook and Google", "upload to FB/Google", "Meta + GAds" | Validate once, then upload to Google and Meta. | plays/upload-facebook-google-hash-only-audience.play.ts |
What ships with it
18 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.
- plays/audit-no-double-hash.play.ts 2.7 KB runs code
- plays/build-contactout-hash-pool.play.ts 9.7 KB runs code
- plays/build-hash-only-audience.play.ts 5.5 KB runs code
- plays/enrich-audience-waterfall.play.ts 17 KB runs code
- plays/evaluate-leadmagic-personal-email.play.ts 3.7 KB runs code
- plays/evaluate-personal-email-provider.play.ts 14 KB runs code
- plays/report-google-coverage-lift.play.ts 8.6 KB runs code
- plays/shared/audience-hash.ts 5.2 KB runs code
- plays/upload-facebook-google-hash-only-audience.play.ts 5.4 KB runs code
- plays/upload-google-hash-only-audience.play.ts 3.3 KB runs code
- recipes/enrich-and-upload-facebook-google.md 7.0 KB
- recipes/max-coverage-audience.md 11 KB
- recipes/sample-abm-segment-example.md 5.0 KB
- shared/audience-basics.md 4.5 KB
- shared/contactout-hash-pool.md 7.6 KB
- shared/meta-connection.md 3.1 KB
- shared/upload-failure-modes.md 6.7 KB
- skill-metadata.json 3.3 KB
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.
- 11d ago Changed · -1 lines e4eddc140063
- 12d ago Changed 9d11df8e8cbf
- 13d ago Changed · -162 lines ffbe61244b9f
- 14d ago Changed 9e5a89810197
- 15d ago Changed 6529c25e74ac
- 16d ago Changed a15906366471
- 17d ago Changed · +6 lines 71709314389d
- 20d ago Changed 30c01c0cf1e6
- 24d ago Changed · -3 lines f596c6daeb5c
- 26d ago First seen · 499 lines · 133 tokens per session scan A 8fe3996ffaf2
deepline-ads-audiences is a skill published in the GitHub repository getaero-io/gtm-eng-skills (71 stars, last pushed yesterday), licensed MIT. It adds 133 tokens to every session and 7,323 once invoked, about $0.0005 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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