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 swan-gtm/gtm-skills --skill linkedin-limits-warmupgit clone --depth 1 https://github.com/swan-gtm/gtm-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/swan-gtm/gtm-skills/linkedin-limits-warmup)<a href="https://agentmods.dev/skills/swan-gtm/gtm-skills/linkedin-limits-warmup"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/linkedin-limits-warmup/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/swan-gtm/gtm-skills/linkedin-limits-warmup"><img src="https://agentmods.dev/badge/skills/swan-gtm/gtm-skills/linkedin-limits-warmup.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00056 | $0.00741 |
| Opus 5.5 | $0.00022 | $0.00296 |
| Sonnet 5.5 | $0.00011 | $0.00148 |
| Haiku 4.5 | $0.00006 | $0.00074 |
Grade A, and why
linkedin-limits-warmup 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- linkedin-limits-warmup — 89% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LinkedIn Limits & Warm-Up Protocol
LinkedIn Limits (2024-2026)
Monthly Limits
- 400 connection requests/month (non-premium)
- 800 Open InMails/month (premium members)
- ~120 interactions/day total (stay well below)
Recommended Daily Limits
- 15-20 Direct Messages/day
- 30-40 Open InMails/day
- 10-15 connection requests/day
- 40 "other interactions"/day
What Counts as Interactions
- DMs, connection requests, InMails
- Profile views
- Post likes/comments
- Page likes
- Endorsements
- Joining events/groups
LinkedIn Warm-Up Protocol
When Needed
- Inactive accounts
- New accounts
- Accounts returning from restriction
Process
Days 1-10:
- 60 interactions/day maximum
- Only manual activity (no automation)
- Mix of views, likes, comments
- Focus on genuine engagement
Days 11-20:
- Gradually increase to 80/day
- Start light connection requests (5-10/day)
- Continue manual engagement
Days 21+:
- Gradual increase to full limits
- Introduce automation carefully
- Monitor for warnings
Red Flags to Avoid
- Sudden activity spikes - Gradual increase only
- Same message to everyone - Vary your copy
- Connecting outside work hours - Stay within 9 AM - 6 PM
- Weekend activity - Weekdays only
- Automation too early - Manual first 2-3 weeks
Account Health Indicators
| Indicator | Healthy | Warning | Danger |
|---|---|---|---|
| Connection acceptance | >30% | 15-30% | <15% |
| Message response | >10% | 5-10% | <5% |
| Profile views | Stable | Declining | Blocked |
| Pending connections | <500 | 500-700 | >700 |
Recovery from Restriction
- Stop all automation immediately
- Manual activity only for 2 weeks
- Respond to existing conversations
- Post valuable content
- Engage with others' content
- Slowly reintroduce outreach
Combines with
| Skill | Why |
|---|---|
linkedin-campaign-complete |
Execute campaigns within limits |
linkedin-success-factors |
Apply success rules while respecting limits |
cold-email-4-sequence |
Coordinate LinkedIn + email to reduce LinkedIn load |
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.
- 1mo ago First seen · 118 lines · 56 tokens per session scan A d629b8a0560c
linkedin-limits-warmup is a skill published in the GitHub repository swan-gtm/gtm-skills (220 stars, last pushed 7d ago), licensed MIT. It adds 56 tokens to every session and 741 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 2026-08-30.
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