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ai-cold-outreach

When the user wants to build an AI-powered outreach system, write cold emails, improve deliverability, or scale personalized outreach. Also use when the user mentions 'cold email,' 'cold outreach,' 'outreach automation,' 'Instantly,' 'Smartlead,' 'Clay,' 'email sequences,' 'deliverability,' 'personalization at scale,' 'reply rate,' or 'outreach stack.' This skill covers the complete AI cold outreach system from signal detection through conversion. Do NOT use for technical implementation, code review, or software architecture.

60

Quality

70%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./packages/skills-catalog/skills/(gtm)/ai-cold-outreach/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill is highly actionable with excellent concrete guidance, specific metrics, and usable frameworks like the 3-line email template. However, it is severely over-length for a SKILL.md overview—most of the detailed tables (tool comparisons, infrastructure sizing, warmup protocols) should live in the referenced files that don't exist in the bundle. The lack of explicit validation checkpoints between pipeline stages is a notable gap for a multi-step workflow.

Suggestions

Move detailed tables (tool comparisons, infrastructure sizing, warmup protocols, signal rankings) into the referenced files (`references/benchmarks-deliverability-tactics.md` and `references/quick-reference.md`) and keep only the essential framework and one example in the main SKILL.md to cut length by 60-70%.

Add explicit validation checkpoints between pipeline stages, e.g., 'Verify bounce rate is under 2% after first 50 sends before scaling' and 'Check open rates exceed 40% before testing new copy variables.'

Remove explanations of concepts Claude already knows (what SPF/DKIM/DMARC are, how waterfall enrichment works conceptually) and replace with just the specific configuration values and rules.

Create the referenced bundle files so progressive disclosure actually functions—currently the references point to non-existent files.

DimensionReasoningScore

Conciseness

This skill is extremely verbose at 500+ lines. It explains concepts Claude already knows (what DMARC is, how waterfall enrichment works, what SPF records do), includes extensive comparison tables that could be in reference files, and repeats information across sections. The ASCII diagrams, while visually helpful, consume significant tokens for information that could be conveyed more concisely.

1 / 3

Actionability

The skill provides highly specific, concrete guidance throughout: exact sending limits per mailbox, specific domain math formulas, concrete email examples (good and bad), specific tool recommendations with decision frameworks, warmup schedules with daily volumes, and precise A/B testing minimums. The 3-line email framework with worked examples is immediately usable.

3 / 3

Workflow Clarity

The six-stage pipeline is clearly sequenced and the warmup protocol has week-by-week steps. However, there are no explicit validation checkpoints or feedback loops between stages. For example, there's no 'verify your deliverability score before scaling volume' step, no 'check bounce rate after first 100 sends' checkpoint, and the DMARC rollout mentions reviewing reports but doesn't specify what to look for or when to stop.

2 / 3

Progressive Disclosure

The skill references two external files (`references/benchmarks-deliverability-tactics.md` and `references/quick-reference.md`) which is good progressive disclosure design, but neither file exists in the bundle. The main SKILL.md contains enormous amounts of detail (tool comparisons, infrastructure sizing tables, enrichment waterfalls) that should be in those reference files rather than inline, making the overview far too long.

2 / 3

Total

8

/

12

Passed

Description

89%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a strong skill description with excellent trigger term coverage and completeness, including both positive triggers and negative boundaries. The main weakness is that the 'what' portion could be more specific about the concrete actions the skill enables (e.g., listing specific deliverables like email templates, sequence structures, warmup strategies). Overall, it would perform well in a multi-skill selection scenario.

Suggestions

Add more specific concrete actions to the 'what' portion, e.g., 'design email sequences, configure warmup schedules, write personalized email templates, optimize subject lines, structure lead scoring criteria' to improve specificity.

DimensionReasoningScore

Specificity

The description mentions some actions like 'build an AI-powered outreach system, write cold emails, improve deliverability, scale personalized outreach' and references 'signal detection through conversion,' but these are more domain-level than concrete specific actions. It lacks the granularity of listing multiple discrete operations (e.g., 'set up email warmup, configure DNS records, write email sequences, build lead lists').

2 / 3

Completeness

Clearly answers both 'what' (build AI-powered outreach system, write cold emails, improve deliverability, scale personalized outreach, complete system from signal detection through conversion) and 'when' (explicit 'Use when' equivalent with detailed trigger terms). Also includes a helpful negative boundary ('Do NOT use for technical implementation, code review, or software architecture').

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms users would actually say: 'cold email,' 'cold outreach,' 'outreach automation,' 'Instantly,' 'Smartlead,' 'Clay,' 'email sequences,' 'deliverability,' 'personalization at scale,' 'reply rate,' 'outreach stack.' These include tool names, common phrases, and natural language variations.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with a clear niche in cold email outreach and specific tool names (Instantly, Smartlead, Clay). The explicit exclusion of technical implementation/code review further reduces conflict risk with engineering-focused skills.

3 / 3

Total

11

/

12

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
tech-leads-club/agent-skills
Reviewed

Table of Contents

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