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deepline-analytics

Use this skill when answering business analytics, RevOps, GTM metric, pipeline, revenue, funnel, customer, or warehouse questions with Deepline. Triggers on phrases like 'query Snowflake', 'analyze pipeline', 'total ACV', 'break down by quarter', 'use the semantic layer', 'run a semantic query', or any use of snowflake_get_semantic_layer / snowflake_run_semantic_query. Skip prospecting, enrichment, contact finding, outbound, or personalization workflows; use deepline-gtm for those.

68

Quality

83%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

This is a strong, highly actionable skill with excellent workflow clarity and concrete executable examples throughout. Its main weakness is length—the document packs a lot of valuable detail inline that could benefit from being split into reference files for progressive disclosure, and some sections could be tightened to reduce token cost. The error handling table and decision matrix are particularly well done.

Suggestions

Trim the 'Before You Start' section to 1-2 sentences since the routing logic is already in the YAML description and decision matrix.

Consider extracting the 'Semantic Query Contract', 'Custom SQL Knobs', and 'Choosing Semantic Objects' sections into a separate REFERENCE.md to reduce the main file's token footprint and improve progressive disclosure.

DimensionReasoningScore

Conciseness

The skill is thorough and mostly earns its tokens—decision matrices, error tables, and contract details are genuinely useful. However, some sections are verbose (e.g., the 'Choosing Semantic Objects' section re-explains concepts multiple times, and the 'Before You Start' preamble restates what the YAML description already covers). It could be tightened by ~20-30% without losing information.

2 / 3

Actionability

The skill provides fully executable CLI commands with exact JSON payloads, concrete bash examples for each step, specific payload shapes for both typed and legacy forms, and clear good/bad examples for filters. Every major workflow step has copy-paste-ready commands.

3 / 3

Workflow Clarity

The Standard Loop is clearly numbered with validation checkpoints (pilot small query first, inspect returned SQL, confirm workspace context). The 'Fastest Metric Path' provides an explicit step-by-step sequence. Error handling includes a comprehensive diagnostic table with specific recovery actions. The 'Latest Periods' section explicitly warns against a common mistake and provides a clear alternative workflow.

3 / 3

Progressive Disclosure

The content is well-structured with clear section headers and a logical flow from decision matrix → standard loop → fastest path → contract details → error handling → reporting. However, with no bundle files, all content is inline in a single long document (~200+ lines). The semantic query contract details, custom SQL knobs, and choosing semantic objects sections could reasonably be split into reference files for better navigation.

2 / 3

Total

10

/

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 clear boundary-setting against a related skill. Its main weakness is that the 'what it does' portion leans more toward listing domains than concrete actions (e.g., it doesn't specify outputs like 'generates reports' or 'creates visualizations'). The use of second person 'Use this skill when...' is a minor voice issue, though it's a common pattern in trigger guidance.

Suggestions

Add more concrete action verbs describing what the skill produces, e.g., 'Queries Snowflake via semantic layer to answer business analytics questions, generate revenue reports, and analyze pipeline metrics.'

DimensionReasoningScore

Specificity

The description names the domain (business analytics, RevOps, GTM metrics, pipeline, revenue) and implies actions like querying and analyzing, but doesn't list multiple concrete actions beyond 'query Snowflake' and 'analyze pipeline'. It's more about when to trigger than what specific capabilities it provides.

2 / 3

Completeness

Clearly answers both 'what' (business analytics, RevOps, GTM metric, pipeline, revenue, funnel questions with Deepline/Snowflake) and 'when' (explicit trigger phrases and tool names). Also includes explicit exclusion criteria ('Skip prospecting, enrichment...use deepline-gtm for those'), which strengthens the 'when' guidance.

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms: 'query Snowflake', 'analyze pipeline', 'total ACV', 'break down by quarter', 'use the semantic layer', 'run a semantic query', plus tool names. These are phrases users would naturally say when needing this skill.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive with explicit boundary-drawing against the related 'deepline-gtm' skill. The specific mention of Snowflake semantic layer tools and the clear exclusion of prospecting/enrichment/outbound workflows makes it very unlikely to conflict with other 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
getaero-io/gtm-eng-skills
Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.