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.
70
62%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Advisory
Suggest reviewing before use
Optimize this skill with Tessl
npx tessl skill review --optimize ./packages/skills-catalog/skills/(gtm)/ai-cold-outreach/SKILL.mdQuality
Discovery
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 explicit exclusions. The main weakness is that the 'what' portion could be more specific about concrete actions beyond the general 'build an AI-powered outreach system' framing—listing specific deliverables like 'design email sequences, optimize subject lines, configure domain warmup strategies' would strengthen specificity.
Suggestions
Add more concrete specific actions to the 'what' portion, e.g., 'design email sequences, craft personalized openers, optimize subject lines, configure domain warmup strategies, build lead scoring workflows' instead of the vague 'complete AI cold outreach system from signal detection through conversion.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description names the domain (AI-powered outreach) and mentions some actions like 'write cold emails,' 'improve deliverability,' and 'scale personalized outreach,' but it doesn't list multiple concrete, specific actions comprehensively. Phrases like 'complete AI cold outreach system from signal detection through conversion' are somewhat vague about what specific tasks are performed. | 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 trigger terms listed, plus a 'Do NOT use' exclusion clause). The 'Use when' equivalent is explicitly stated. | 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 variations. | 3 / 3 |
Distinctiveness Conflict Risk | Highly distinctive with a clear niche in cold email outreach. The explicit exclusion of 'technical implementation, code review, or software architecture' further reduces conflict risk. The specific tool names (Instantly, Smartlead, Clay) and domain-specific terms make it very unlikely to trigger for the wrong skill. | 3 / 3 |
Total | 11 / 12 Passed |
Implementation
35%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is comprehensive and clearly written by someone with deep domain expertise in cold outreach systems. Its main weakness is extreme verbosity — it tries to be both an overview and a complete reference manual in a single file, resulting in a massive token footprint that includes extensive tables, diagrams, and explanations that should be split into reference files. The actionability is moderate: good frameworks and examples for email writing, but lacking executable configurations or specific tool setup commands.
Suggestions
Move the detailed comparison tables (Instantly vs. Smartlead, signal types, infrastructure sizing, enrichment waterfall) into the referenced files and keep only 2-3 line summaries with links in the main skill body — this could cut the file by 60%+.
Add explicit validation checkpoints to the workflow: e.g., 'After Week 2 warmup, check deliverability score in Instantly — if below 90%, pause and investigate before proceeding to cold sends.'
Replace high-level tool descriptions with specific, copy-paste-ready configurations: e.g., actual Clay column prompts, actual SPF/DKIM DNS record examples, actual Instantly campaign settings.
Remove explanations of concepts Claude already knows (what SPF/DKIM/DMARC are, why waterfall enrichment works, what A/B testing is) and replace with just the specific settings and values to use.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | This is extremely verbose at 500+ lines. It explains concepts Claude already knows (what DKIM is, what DMARC does, how waterfall enrichment works conceptually), includes exhaustive comparison tables that belong in reference files, and provides lengthy explanations of tool ecosystems. The ASCII diagrams, while visually helpful, add significant token cost for information that could be summarized in a few lines with references to detailed docs. | 1 / 3 |
Actionability | The skill provides concrete frameworks (3-line email structure with good/bad examples, domain math formulas, warmup schedules, A/B testing priorities) which are genuinely useful. However, there are no executable code snippets, API calls, or copy-paste-ready configurations. The Clay setup is described at a high level ('Add an AI enrichment column using Claude') rather than with specific steps or actual prompts. Much of the content describes rather than instructs. | 2 / 3 |
Workflow Clarity | The six-stage pipeline is clearly sequenced and the warmup protocol has week-by-week steps. However, there are no validation checkpoints or feedback loops for critical operations like domain warmup (what if deliverability drops?), list verification (what if bounce rate exceeds 2% mid-campaign?), or A/B testing (when to declare a winner). The DMARC rollout sequence is the closest to having validation steps but lacks explicit error recovery. | 2 / 3 |
Progressive Disclosure | The skill does reference two external files (references/benchmarks-deliverability-tactics.md and references/quick-reference.md) and lists related skills, which is good. However, the main file contains enormous amounts of detail that should be in those reference files — the full Instantly vs. Smartlead comparison table, the complete enrichment waterfall diagram, the detailed infrastructure sizing guide, and the signal types table all belong in reference documents rather than the main skill body. | 2 / 3 |
Total | 7 / 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
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Table of Contents
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