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tdg-personal/lead-intelligence

AI-native lead intelligence and outreach pipeline. Replaces Apollo, Clay, and ZoomInfo with agent-powered signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X. Use when the user wants to find, qualify, and reach high-value contacts.

76

Quality

76%

Does it follow best practices?

Impact

Pending

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

Overview
Quality
Evals
Security
Files

Quality

Discovery

85%

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 description that clearly defines a specific niche (sales lead intelligence and outreach) with concrete capabilities and an explicit 'Use when' clause. Its main weakness is the heavy use of specialized/branded jargon ('mutual ranking', 'source-derived voice modeling', 'warm path discovery') that users are unlikely to naturally use when requesting this skill, while missing more common trigger terms like 'prospecting', 'cold email', or 'lead generation'.

Suggestions

Add more natural user-facing trigger terms such as 'prospecting', 'cold email', 'lead generation', 'sales outreach', 'find prospects' to improve discoverability when users phrase requests in everyday language.

Simplify or supplement jargon like 'source-derived voice modeling' and 'mutual ranking' with plain-language equivalents so Claude can better match user intent.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: signal scoring, mutual ranking, warm path discovery, voice modeling, and channel-specific outreach across email/LinkedIn/X. These are detailed, actionable capabilities.

3 / 3

Completeness

Clearly answers both 'what' (lead intelligence and outreach pipeline with specific capabilities) and 'when' ('Use when the user wants to find, qualify, and reach high-value contacts'). The explicit 'Use when' clause is present with clear trigger guidance.

3 / 3

Trigger Term Quality

Includes some natural terms like 'lead', 'outreach', 'email', 'LinkedIn', 'contacts', and competitor names (Apollo, Clay, ZoomInfo). However, it leans heavily on specialized jargon ('signal scoring', 'mutual ranking', 'source-derived voice modeling', 'warm path discovery') that users are unlikely to naturally say. Missing common variations like 'prospecting', 'cold email', 'sales leads', 'lead gen'.

2 / 3

Distinctiveness Conflict Risk

Highly distinctive niche combining lead intelligence, qualification, and multi-channel outreach. The mention of specific competitor tools (Apollo, Clay, ZoomInfo) and specific channels (email, LinkedIn, X) makes it very unlikely to conflict with other skills.

3 / 3

Total

11

/

12

Passed

Implementation

57%

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

This is a comprehensive lead intelligence skill with strong structural organization and good progressive disclosure to related skills and agents. Its main weaknesses are moderate verbosity (anti-patterns, channel descriptions that Claude would intuit), pseudocode rather than executable examples, and missing explicit validation checkpoints between pipeline stages. The weighted scoring models and ranking formulas are genuinely useful additions.

Suggestions

Add explicit validation/approval checkpoints between stages (e.g., 'Present signal scores to user for review before proceeding to mutual ranking' and 'Get user approval on outreach drafts before creating Mail drafts')

Replace pseudocode with more executable examples — show actual MCP tool call signatures for Exa and X API rather than invented function names

Trim the Anti-Patterns and Channel Rules sections significantly — Claude already knows not to use 'fake familiarity' or 'visible merge fields'; focus on project-specific constraints only

DimensionReasoningScore

Conciseness

The skill is fairly long (~250 lines) and includes some unnecessary explanation (e.g., detailed descriptions of what each channel is for, anti-patterns that Claude would already know). The signal scoring table and mutual ranking model are useful but the overall document could be tightened by ~30%. The math formulas and pipeline diagram earn their place, but sections like 'Anti-Patterns' and channel descriptions are somewhat verbose.

2 / 3

Actionability

The skill provides pseudocode rather than fully executable code (e.g., the Python snippets reference `web_search_exa()` and `search_recent_tweets()` without real API signatures). The weighted scoring tables and ranking formulas are concrete and useful, but the outreach drafting section gives guidelines rather than executable templates. The output format example for mutual ranking is helpful but most stages lack concrete output examples.

2 / 3

Workflow Clarity

The 5-stage pipeline is clearly sequenced with a visual diagram, and each stage is well-delineated. However, there are no explicit validation checkpoints between stages — no 'verify signal scores before proceeding to mutual ranking' or 'confirm enrichment data quality before drafting.' For a pipeline that involves outreach (a semi-destructive/irreversible action), the lack of explicit approval gates beyond the final 'do not send automatically' note is a gap.

2 / 3

Progressive Disclosure

The skill references external agents in `agents/` subdirectory, related skills (`brand-voice`, `connections-optimizer`, `social-graph-ranker`), and clearly signals when to use them. Content is well-organized with clear headers and the main SKILL.md serves as an overview that delegates appropriately. No deeply nested references.

3 / 3

Total

9

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Reviewed

Table of Contents