gamma-deploy-integration

Deploy Gamma-integrated applications to production environments. Use when deploying to Vercel, AWS, GCP, or other cloud platforms with proper secret management and configuration. Trigger with phrases like "gamma deploy", "gamma production", "gamma vercel", "gamma AWS", "gamma cloud deployment".

Quality

77%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

High

Do not use without reviewing

Fix and improve this skill with Tessl

tessl review fix ./plugins/saas-packs/gamma-pack/skills/gamma-deploy-integration/SKILL.md

Quality

Content

65%Weight 40%Scale 1-3

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

Highly actionable copy-paste deployment recipes across four platforms, undermined by missing production-deployment validation/verification steps, some noisy and occasionally incorrect inline comments, and a monolithic single-file structure that forgoes progressive disclosure.

Suggestions

Add explicit verification/rollback checkpoints after each production deploy (e.g., check deployment status, confirm secret resolution, define a rollback command) to satisfy the validation requirement for destructive operations.

Remove low-value or incorrect inline comments such as '# 256 bytes', '# 2010 = configured value', and '# HTTP 200 OK' to tighten token efficiency.

Split the per-platform recipes into one-level-deep reference files (e.g., references/vercel.md, references/aws-lambda.md) referenced from a concise overview so progressive disclosure earns a higher score.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient code/config, but carries noise such as inline comments like '# 2010 = configured value', '# 2016 = configured value', and '# 256 bytes' (which is also incorrect — 256 is MB, not bytes) that Claude does not need.	2 / 3
Actionability	It provides fully executable, copy-paste-ready artifacts per platform — Vercel CLI commands and vercel.json, an AWS SAM template with a TypeScript Lambda handler, a Dockerfile and gcloud commands, and a GitHub Actions workflow.	3 / 3
Workflow Clarity	Steps are clearly sequenced per platform (Step 1/2/3) and an error-handling table exists, but production deployment is a destructive/outward-facing operation with no validation or verification checkpoints (no deploy-success check, log inspection, or rollback guidance), capping this dimension at 2 per the rubric.	2 / 3
Progressive Disclosure	The file is well-organized by platform section, but ~200 lines of per-platform config all live inline in a single SKILL.md with no bundle references — content that could be split into per-platform reference files is presented monolithically, matching the anchor-2 example.	2 / 3
	Total	9 / 12 Passed

Description

90%Weight 40%Scale 1-3

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

A well-formed description with explicit what/when guidance and distinctive gamma-prefixed triggers. It is slightly held back on specificity because the capability list reduces to one deploy verb across platforms rather than multiple distinct actions.

Suggestions

Replace the single 'deploy' verb with a few concrete supporting actions (e.g., store secrets, configure environment variables, wire CI/CD) so specificity reaches a comprehensive list.

Dimension	Reasoning	Score
Specificity	It names the domain ('Deploy Gamma-integrated applications to production environments') and surfaces supporting actions like 'secret management and configuration', but the core action is a single verb ('deploy') repeated across platforms rather than a comprehensive list of multiple concrete actions.	2 / 3
Completeness	It answers both 'what' ('Deploy Gamma-integrated applications to production environments') and 'when' via an explicit 'Use when deploying to Vercel, AWS, GCP...' clause plus enumerated trigger phrases, satisfying the anchor for explicit triggers.	3 / 3
Trigger Term Quality	It gives natural phrases a user would actually say — 'gamma deploy', 'gamma production', 'gamma vercel', 'gamma AWS', 'gamma cloud deployment' — alongside platform names, providing good coverage of likely trigger language.	3 / 3
Distinctiveness Conflict Risk	The 'Gamma' product qualifier and gamma-prefixed trigger phrases carve out a clear niche unlikely to collide with generic deployment skills.	3 / 3
	Total	11 / 12 Passed

Validation

87%

Warnings & errors only

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

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	14 / 16 Passed

Repository: jeremylongshore/claude-code-plugins-plus-skills
Path: plugins/saas-packs/gamma-pack/skills/gamma-deploy-integration/SKILL.md
Commit: 4c47e33

Reviewed: 2 days ago

Table of Contents

Discovery Implementation Validation

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.