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luma-event-attendees

Find speakers, hosts, and guest profiles at conferences and events on Luma. Two modes - free direct scrape for hosts, or Apify-powered search for full guest profiles with LinkedIn/Twitter/bio.

60

Quality

71%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./skills/lead-generation/capabilities/luma-event-attendees/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

72%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 body is highly actionable with executable commands and clear sections, and includes a sequenced agent workflow, but it lacks validation checkpoints for a batch operation and inlines content that could live in separate reference files.

Suggestions

Add explicit validation checkpoints to the AI Agent Workflow (e.g. verify the exported CSV has expected rows/columns before qualifying against ICP, and retry guidance if a scrape returns no people).

Move the full Options Reference and Troubleshooting sections into a separate references/ file (e.g. references/USAGE.md) and link to it from SKILL.md to improve progressive disclosure.

De-duplicate the mode descriptions and cost/rent URLs that currently appear across 'Two Modes', 'Setup', and 'Usage'.

DimensionReasoningScore

Conciseness

Mostly efficient and action-oriented with executable commands, but some redundancy across the 'Two Modes', 'Usage', and 'AI Agent Workflow' sections and repeated cost/rent URLs could be trimmed.

4 / 5

Actionability

Fully executable copy-paste commands throughout, a concrete options reference, real example URLs, and a complete CSV column table covering the common cases.

5 / 5

Workflow Clarity

The 5-step AI Agent Workflow is clearly sequenced, but this batch prospecting operation lacks explicit validation checkpoints or error-recovery feedback loops, which caps workflow clarity at 3 per the rubric.

3 / 5

Progressive Disclosure

Sections are well-organized and bundle scripts are clearly referenced by path, but there are no references/ or assets/ files and detail like the full options reference and troubleshooting is inlined in SKILL.md rather than split into separate reference files.

3 / 5

Total

15

/

20

Passed

Description

70%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, distinctive, and action-oriented, but lacks an explicit 'Use when...' trigger clause, which caps completeness at 3. Trigger-term coverage is good but would benefit from common synonyms like 'attendees' or 'RSVP'.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user wants to find speakers, hosts, or attendee profiles from Luma events for outreach prospecting.'

Include common synonyms users would naturally say, such as 'attendees', 'RSVPs', or 'guest lists', alongside 'guest profiles'.

State both modes as trigger contexts (e.g. 'Use for free host scraping from event URLs, or paid full guest-profile search via Apify').

DimensionReasoningScore

Specificity

Names the Luma-events domain and several concrete actions ('Find speakers, hosts, and guest profiles', 'free direct scrape for hosts', 'Apify-powered search for full guest profiles with LinkedIn/Twitter/bio'); minor coverage gaps keep it just below comprehensive.

4 / 5

Completeness

Clearly states what the skill does but provides no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the rubric guideline.

3 / 5

Trigger Term Quality

Good natural-term coverage ('speakers, hosts, guest profiles', 'conferences and events on Luma', 'guest profiles with LinkedIn/Twitter/bio'), but misses common synonyms like 'attendees', 'RSVP', or 'event list'.

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (Luma event prospecting via direct scrape or Apify actor) with distinct triggers and minimal overlap risk with other skills.

5 / 5

Total

16

/

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

frontmatter_unknown_keys

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

Warning

Total

15

/

16

Passed

Repository
gooseworks-ai/goose-skills
Reviewed

Table of Contents

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