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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.

67

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

71%Weight 40%Scale 1-5

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

The content is well-structured, actionable, and respects the reader's competence, with a clear staged workflow and an explicit send-approval checkpoint. Its main weaknesses are progressive disclosure — an all-inline body plus a non-existent referenced agents/ directory — and the lack of a formal validation/retry loop in the batch outreach workflow.

Suggestions

Move the referenced specialized agents into an actual agents/ directory (or remove the Agents section if they are not bundled) so the body's references point to real files.

Add an explicit validate→fix→retry checkpoint between enrichment (Stage 4) and outreach drafting (Stage 5), e.g. confirm each lead has voice + channel data before drafting, to strengthen the batch-workflow feedback loop.

Consider splitting the channel rules and ranking formula into a reference file so SKILL.md stays a lean overview.

DimensionReasoningScore

Conciseness

The body is efficient and assumes Claude's competence — using compact tables, an ASCII pipeline diagram, and terse Goal/Avoid blocks — with only minor spots (the prose in 'Untrusted Source Content' and the related-skills framing) that could be trimmed further.

4 / 5

Actionability

Provides mostly executable guidance: real Python using web_search_exa/search_recent_tweets in Stage 1, explicit channel rules, a concrete Execution Pattern, and env-var config. The mutual-ranking formula and pipeline diagram are illustrative rather than runnable, which keeps it just below a 5.

4 / 5

Workflow Clarity

A clearly sequenced five-stage pipeline with an explicit human-in-the-loop validation gate ('draft first', 'Do not send messages automatically without explicit user approval') that satisfies the batch-operation validation requirement. Minor gaps remain — no validate→fix→retry loop and no checkpoint confirming enrichment completeness before outreach.

4 / 5

Progressive Disclosure

Sections are well organized, but everything lives inline in a single ~330-line file with no references/ scripts/ or assets/ bundles, and the 'Agents' section points to an agents/ subdirectory that does not exist — a referenced path that cannot be verified and detail (formulas, channel rules) that arguably belongs in separate files.

3 / 5

Total

15

/

20

Passed

Description

92%Weight 40%Scale 1-5

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

The description is specific, complete, and distinctive, clearly stating what the pipeline does and when to use it. Its only weakness is trigger-term breadth, where a few common natural synonyms ('prospects', 'outreach list', 'warm intros') are absent.

Suggestions

Add common synonyms to the trigger clause such as 'prospects', 'outreach list', and 'warm intros' so the description matches the phrases users actually say.

Keep the named-competitor framing but consider trimming 'AI-native' which adds little actionable signal.

DimensionReasoningScore

Specificity

Names the domain plus multiple concrete capabilities — 'signal scoring, mutual ranking, warm path discovery, source-derived voice modeling, and channel-specific outreach across email, LinkedIn, and X' — giving comprehensive coverage of distinct actions.

5 / 5

Completeness

Explicitly answers both 'what' (a five-part pipeline: signal scoring, mutual ranking, warm path discovery, voice modeling, channel-specific outreach) and 'when' ('Use when the user wants to find, qualify, and reach high-value contacts') with concrete trigger phrasing.

5 / 5

Trigger Term Quality

Includes natural trigger phrases ('find, qualify, and reach high-value contacts') but omits common synonyms a user would say such as 'outreach list', 'prospects', 'warm intros', or 'lead generation', so coverage is good rather than comprehensive.

4 / 5

Distinctiveness Conflict Risk

A clearly delineated niche (agent-powered lead intelligence replacing Apollo/Clay/ZoomInfo) with distinct triggers; minimal risk of firing for an unrelated skill.

5 / 5

Total

19

/

20

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

Total

15

/

16

Passed

Repository
affaan-m/ECC
Reviewed

Table of Contents

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