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gtm-engineering

When the user wants to build GTM automation with code, design workflow architectures, use AI agents for GTM tasks, or implement the 'architecture over tools' principle. Also use when the user mentions 'GTM engineering,' 'GTM automation,' 'n8n,' 'Make,' 'Zapier,' 'workflow automation,' 'Clay API,' 'instruction stacks,' 'AI agents for GTM,' or 'revenue automation.' This skill covers technical GTM infrastructure from workflow design through agent orchestration. Do NOT use for technical implementation, code review, or software architecture.

72

Quality

89%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

78%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 well-structured with novel GTM-specific guidance, concrete thresholds, and clean progressive disclosure to two real reference files. Its main weaknesses are minor verbosity in role/career framing and concept-level rather than executable-code presentation of the build workflow.

Suggestions

Trim the career-trajectory and GTM-Engineer-role prose in sections 1 (the job-posting count, compensation, IC-to-architect scaling) to keep the body focused on actionable architecture guidance.

Add a short explicit build/validate workflow with checkpointed validation steps (e.g., confirm scoring thresholds → validate enrichment confidence gates → verify SLA routing → feedback loop review) rather than describing the workflow conceptually across separate tables.

Include at least one copy-paste-ready code or config snippet in the body (e.g., an n8n/Make webhook or an instruction-stack JSON skeleton) to lift actionability from concrete-guidance to executable-ready.

DimensionReasoningScore

Conciseness

Mostly efficient with structured tables and novel GTM-specific content, but some career-trajectory and role-definition prose ('scales from individual contributor to architect…') is tangential to actionable work. Not 3 because padding is minor, not 5 because a few framing passages could be trimmed.

4 / 5

Actionability

Concrete thresholds throughout (0.85 confidence, <5 min hot lead SLA, 30–90d re-enrichment, pricing tables, decision tree), but guidance is instruction-and-table heavy rather than copy-paste executable code, with execution detail offloaded to references. Not 5 due to lack of ready-to-run code blocks in the body itself.

4 / 5

Workflow Clarity

'Before Starting' gives a sequenced discovery checklist and the feedback-loops and troubleshooting tables map signals/cause to action/fix; however the core build workflow is described conceptually rather than as a strict validate→fix→retry checkpoint sequence. Not 5 because explicit validation checkpoints in the main build flow are implicit rather than stepwise.

4 / 5

Progressive Disclosure

Body is a clear overview with two well-signaled, one-level-deep references (references/implementation-guide.md and references/quick-reference.md), both verified to exist, with content appropriately split and easy to navigate.

5 / 5

Total

17

/

20

Passed

Description

100%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 excellent: it specifies concrete actions, enumerates natural trigger terms including platform names, and clearly bounds both when to use and when not to use the skill. Voice is appropriately third-person/neutral.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'build GTM automation with code, design workflow architectures, use AI agents for GTM tasks' and 'workflow design through agent orchestration' — giving comprehensive coverage of the domain's capabilities.

5 / 5

Completeness

Explicitly answers both 'what' (build GTM automation, design architectures, orchestrate agents) and 'when' via a concrete 'Also use when the user mentions…' clause with multiple trigger phrases.

5 / 5

Trigger Term Quality

Comprehensive natural trigger terms including synonyms and product names users actually say: 'GTM engineering,' 'GTM automation,' 'n8n,' 'Make,' 'Zapier,' 'workflow automation,' 'Clay API,' 'instruction stacks,' 'AI agents for GTM,' and 'revenue automation.'

5 / 5

Distinctiveness Conflict Risk

Clear GTM-automation niche with distinct triggers and an explicit exclusion clause ('Do NOT use for technical implementation, code review, or software architecture') minimizing wrong-skill activation.

5 / 5

Total

20

/

20

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
tech-leads-club/agent-skills
Reviewed

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