Analyze and benchmark outbound campaign performance against real lemlist data from 244K+ campaigns and 249M+ emails.

MITAuto-check passedSales & Support

Install Outbound Analyst

skills CLI
$ npx skills add Othmane-Khadri/YALC-the-GTM-operating-system --skill outbound-analyst -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Othmane-Khadri/YALC-the-GTM-operating-system outbound-analyst --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Othmane-Khadri/YALC-the-GTM-operating-system.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/lemlist/outbound-analyst .claude/skills/outbound-analyst && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
outbound-analyst
GitHub stars
317
Token cost
~1.9k tokens
SKILL.md length
968 words
Files
1
Skills in repo
57
Repo updated
First seen
Licence
MIT

At a glance

Analyze and benchmark outbound campaign performance against real lemlist data from 244K+ campaigns and 249M+ emails.

  • Works in 3 steps: Identify what's being evaluated → Apply the right benchmark → Deliver the verdict
  • Asked are my stats good
  • SKILL.md covers Your job, Step 1 — Identify what's being…, Step 2 — Apply the right… and Step 3 — Deliver the verdict, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Outbound Analyst is an agent skill from Othmane-Khadri/YALC-the-GTM-operating-system. Analyze and benchmark outbound campaign performance against real lemlist data from 244K+ campaigns and 249M+ emails. Use when asked "are my stats good", "is my reply rate good", "why am I not getting replies", "is my open rate normal", "how do I compare to benchmarks", "my campaign is underperforming", "what's a good reply rate", "is X% good for cold email", "my LinkedIn acceptance rate is low", "how many emails should I send per day", "my deliverability is bad", "analyze my campaign stats", or any question…

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Sales & Support, covering Transactional email and Cold outreach. It works with LinkedIn. The repository describes itself as: YALC 1.0, the open-source Clay alternative. MIT, CLI-first, self-hosted, runs in Claude Code. Yalc today is an intelligent orchestration layer that runs pre configured GTM agents…. The licence is MIT.

When your agent uses it

  • Asked are my stats good
  • Is my reply rate good
  • Why am I not getting replies
  • Is my open rate normal

Example prompts

  • “are my stats good”
  • “is my reply rate good”
  • “why am I not getting replies”
  • “/outbound-analyst”

Workflow steps

3 steps, taken from the step headings in SKILL.md.

  1. Identify what's being evaluated
  2. Apply the right benchmark
  3. Deliver the verdict

What it can do on your machine

Read from SKILL.md and the folder at commit 5686d1f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Outbound Analyst loads about 1.9k tokens when it runs. Until then it costs about 186 tokens; SKILL.md has 968 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~186
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Othmane-Khadri/YALC-the-GTM-operating-system at commit 5686d1f, republished under its MIT licence (© Othmane-Khadri). 968 words, ~1,902 tokens.

Download SKILL.mdSave it as .claude/skills/outbound-analyst/SKILL.md (or your agent's skills folder).
name
outbound-analyst
description
Analyze and benchmark outbound campaign performance against real lemlist data from 244K+ campaigns and 249M+ emails. Use when asked "are my stats good", "is my reply rate good", "why am I not getting replies", "is my open rate normal", "how do I compare to benchmarks", "my campaign is underperforming", "what's a good reply rate", "is X% good for cold email", "my LinkedIn acceptance rate is low", "how many emails should I send per day", "my deliverability is bad", "analyze my campaign stats", or any question involving outreach metrics, rates, or performance. Always use this skill before giving any opinion on whether a stat is good or bad. This skill gives instant verdicts with real data — not vague "it depends" answers.

Outbound Analyst

Your job

Give a clear, honest verdict on outreach stats — not "it depends." Every metric has a benchmark. Pull the right one, deliver the verdict, explain the root cause, and give 1–2 concrete fixes. No padding.


Step 1 — Identify what's being evaluated

Check the conversation for:

  • Which metric(s) the user is asking about (reply rate, open rate, accept rate, etc.)
  • Their channel mix (email only / LinkedIn + email / multichannel)
  • Their list size (# of leads in the campaign)
  • Number of steps in the sequence
  • Whether they're asking about a single metric or want a full audit

If they share multiple stats, do a full audit. If they share one number, give a focused verdict on that metric first, then flag if you need more context.


Step 2 — Apply the right benchmark

🎯 Reply Rate — THE metric that matters most

The single KPI to track. If there's only one number to care about, it's this one.

Email-only campaigns (from 244K campaigns, 249M emails):

VerdictRate
❌ Bad< 2%
🟡 Average~2–4%
✅ Good4–10%
🚀 Really good15%+
🏆 Exceptional25%+ (tight list + sharp copy)

Global reply rate by channel (accounts for all touchpoints):

Channel mixGlobal reply rate
Email only1.1%
LinkedIn + Email4.7%
LinkedIn + Email + Call2.8%*
LinkedIn-first sequences5.7%
Email-first sequences2.6%

*Call adds friction at scale — the bottleneck effect kicks in.

By list size (tighter = better):

List sizeGlobal reply rate
6–50 leads5.3%
51–200 leads3.2%
201–500 leads2.3%
501–1,000 leads1.9%
1,000+ leads1.1%

By steps — LinkedIn + Email (sweet spot = 3 steps):

StepsGlobal reply rate
2 steps7.0%
3 steps7.2% ← sweet spot
4 steps5.0%
5+ steps3.4%

By steps — Email only (more steps ≠ better):

StepsGlobal reply rate
2 steps1.9%
3 steps1.3%
4 steps1.1%
5+ steps0.7%

📬 Open Rate — track with caution

Should you track it? Not really. It's unreliable — tracking opens requires a pixel that actively hurts deliverability. Treat it as a rough signal only.

Persona / contextTypical open rate
Global average~25%
C-Levels~15%
Sales reps~25–35%
Marketing~15%
HR~25–35%
Tech~5%
Good (signal of strong subject line)50%+

If open rate is high but reply rate is low: the subject line works, the body doesn't. Fix the copy, not the subject line.


🖱️ Click Rate — red herring

Should you track it? No. Tracking clicks requires links. Links hurt deliverability. Click rate doesn't correlate with pipeline. Drop links from cold emails entirely. If you need one link, use a separate landing page and track traffic there instead.


🧘 Positive Reply Rate (PRR) — meetings booked

The % of all contacted leads who replied with genuine interest (not just "remove me").

VerdictRate
Industry average0.1–0.5% (1–5 meetings per 1,000 emails)
✅ Good1–5%
🏆 Exceptional> 5 meetings per 100 leads contacted

Note: PRR ≠ meetings booked. A "yes send me the resource" is a PRR if you're running a lead magnet campaign — not every PRR needs to end in a calendar invite.


🙆 LinkedIn Connection Accept Rate

Like deliverability for email: if you can't get in, nothing else matters.

PersonaAccept rate benchmark
Individual Contributors~25%
C-Level~35%
Tech profiles40%+

Low accept rate = wrong targeting, generic note, or profile that doesn't build trust at first glance. Fix the profile and the connection message before adjusting anything else.

LinkedIn voice note vs text (from 8,364 campaigns):

  • Text only: 26.9% LinkedIn reply rate
  • With voice note: 29.5% (+10% relative uplift — strongest for young/urban audiences)

Show full SKILL.md (405 more words)Show less
📞 Calling benchmarks
MetricAverageElite
Connect rate5–20%—
Conversation rate5–10%—
Meeting booked rate1–3%3–5%

Best times: 8–10 AM and 4–6 PM. Avoid 12–2 PM. 3–4 call attempts per lead optimal (most reps stop at 2). Cold calling works 10x better when it's not truly cold — always layer with email or LinkedIn first.


🥵 Deliverability / Warmup

Are you healthy? Check your warmup score — you want 90+ before sending cold campaigns. Keep warmup ON permanently. Turning it off signals to email providers that you're done playing by the rules.

Timeline: wait 3–4 weeks on a new domain/inbox before sending cold emails.


🚫 Sending limits
VolumeVerdict
30 emails/day/inbox✅ Safe — lemlist's recommended max
30–50/day⚠️ Acceptable only with 90+ deliverability + 15% reply + >2% PRR
100+/day❌ You will land in spam

The right scaling move: don't push more emails per inbox. Add more inboxes.

  • 5 inboxes × 30 emails/day = 150 emails/day, safely.

Step 3 — Deliver the verdict

Structure every response as:

[Metric]: [X%] Verdict: ❌ / 🟡 / ✅ / 🚀 — [one-line judgment] Benchmark: [relevant reference point from above] Root cause: [most likely explanation given their context] Fix: [1–2 concrete actions, specific and direct]

If they share multiple metrics, prioritize issues in this order:

  1. Deliverability / warmup (if broken, nothing else matters)
  2. Reply rate (the main signal)
  3. Accept rate (LinkedIn entry point)
  4. Positive reply rate (pipeline quality)
  5. Open rate (weak signal, mention last)

Diagnostic logic — common patterns

High open rate + low reply rate → Subject line works, email body doesn't. The copy fails to connect pain to message. Rewrite the first 2 lines and the CTA.

Low open rate + low reply rate → Deliverability or subject line issue. Check warmup score first. If deliverability is fine, rewrite subject lines to be less salesy.

Good reply rate + low PRR → Wrong ICP or wrong CTA. People reply to disengage ("not the right person", "remove me"), not to engage. Sharpen ICP and shift to a PVP-style CTA.

Low LinkedIn accept rate → Profile optimization issue (photo, headline, banner) or connection note is too salesy. Check if the targeting is right (are you reaching decision-makers?).

Good email stats + mediocre overall stats → Sequence is email-only. Adding LinkedIn before email (LinkedIn-first) moves global reply rate from 2.6% → 5.7%. That's the single highest-leverage structural change available.

Good stats on small list, falling off at scale → Expected. Reply rates drop as list size grows (5.3% at 6–50 leads vs. 1.1% at 1,000+). Solution: keep lists tight, split into sub-ICPs instead of scaling one big campaign.

© Othmane-Khadri, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .claude/skills/lemlist/outbound-analyst of Othmane-Khadri/YALC-the-GTM-operating-system.

Open the folder on GitHubat commit 5686d1f

Compare with similar skills

Outbound Analyst next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Outbound Analyst compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Outbound Analyst this skillOthmane-Khadri/YALC-the-GTM-operating-system317—~1.9kAutomated safety check: PassMIT
Cold Outreachericrisco/rsc-harness174—~4.1kAutomated safety check: PassMIT
Prospectingcoreyhaines31/marketingskills54k—~5kAutomated safety check: PassMIT
Sales OsromangojiberryAI/gojiberryai-sales-os139—~2kAutomated safety check: PassMIT
Cold Outreach Personalizeraiskilloftheweek/claude-ai-skill-of-the-week148—~2.6kAutomated safety check: PassNone
B2B Lead Generationminhnv0807/ai-business-skills610—~1.2kAutomated safety check: PassMIT

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Works with

Questions about Outbound Analyst

What does Outbound Analyst do?

Analyze and benchmark outbound campaign performance against real lemlist data from 244K+ campaigns and 249M+ emails. Outbound Analyst is an agent skill from Othmane-Khadri/YALC-the-GTM-operating-system. Analyze and benchmark outbound campaign performance against real lemlist data from 244K+ campaigns and 249M+ emails.

When should I use Outbound Analyst?

Outbound Analyst fits situations like: asked are my stats good; is my reply rate good; why am I not getting replies; is my open rate normal.

How do I install Outbound Analyst in Claude Code?

Run `npx skills add Othmane-Khadri/YALC-the-GTM-operating-system --skill outbound-analyst -a claude-code`. Or copy the skill folder (.claude/skills/lemlist/outbound-analyst in Othmane-Khadri/YALC-the-GTM-operating-system) into .claude/skills/outbound-analyst in your project. Claude Code loads it when a task matches its description.

How do I install Outbound Analyst in Codex?

Run `npx skills add Othmane-Khadri/YALC-the-GTM-operating-system --skill outbound-analyst -a codex`. Or copy the skill folder (.claude/skills/lemlist/outbound-analyst in Othmane-Khadri/YALC-the-GTM-operating-system) into .agents/skills/outbound-analyst in your project. Codex loads it when a task matches its description.

Can I use Outbound Analyst in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Othmane-Khadri/YALC-the-GTM-operating-system --skill outbound-analyst -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/outbound-analyst, .gemini/skills/outbound-analyst, .github/skills/outbound-analyst and .opencode/skills/outbound-analyst in your project.

What does Outbound Analyst need to run?

SKILL.md names no scripts, command-line tools or credentials: Outbound Analyst is instructions for the agent only.

Does Outbound Analyst access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Outbound Analyst safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Outbound Analyst use?

Outbound Analyst is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Outbound Analyst use?

About 1.9k tokens (SKILL.md is roughly 7.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Outbound Analyst?

Skills that share tags, products or a category with Outbound Analyst: Cold Outreach (ericrisco/rsc-harness, 174 stars), Prospecting (coreyhaines31/marketingskills, 54k stars), Sales Os (romangojiberryAI/gojiberryai-sales-os, 139 stars) and Cold Outreach Personalizer (aiskilloftheweek/claude-ai-skill-of-the-week, 148 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Outbound Analyst?

Othmane-Khadri (a GitHub user) maintains it in Othmane-Khadri/YALC-the-GTM-operating-system, which has 317 GitHub stars. The repository holds 57 skills in this directory. The repository was last updated on August 20, 2026.

Source: Othmane-Khadri/YALC-the-GTM-operating-system on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.