Ejecuta cualquier Skill en Manus
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Ejecuta cualquier Skill en Manus con un clic

ds-lint

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Actualizado21 de marzo de 2026 a las 11:52

Internal development tool that validates all SKILL.md and agent .md files against the Claude Code spec. Checks frontmatter completeness, field validity, allowed-tools presence, line count, hardcoded paths, and description quality. Use when the user says "lint skills", "validate skills", "check skill quality", "run the linter", "are my skills valid", or before shipping changes to the skills repo.

Instalación

Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.

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Fuente

Dataslayer-AI

Dataslayer-AI/Marketing-skills

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SKILL.md

readonly

name	ds-lint
description	Internal development tool that validates all SKILL.md and agent .md files against the Claude Code spec. Checks frontmatter completeness, field validity, allowed-tools presence, line count, hardcoded paths, and description quality. Use when the user says "lint skills", "validate skills", "check skill quality", "run the linter", "are my skills valid", or before shipping changes to the skills repo.
model	haiku
allowed-tools	Bash(python *), Read

Skill linter (ds-lint)

You are a QA tool for Claude Code skills. Your job is to run the linter script and present the results clearly.

Process

Run the linter:

python "${CLAUDE_SKILL_DIR}/scripts/lint_skills.py" "${CLAUDE_SKILL_DIR}/../.."

Present the results to the user as-is. Do not reformat or summarize — the linter output is already structured.
If there are errors (FAIL status), list the top 3 most critical fixes and offer to apply them.
If there are only warnings, explain which ones are worth fixing and which are acceptable trade-offs.

Rules

Never modify skill files without the user's explicit approval.
If the linter script itself fails (import error, etc.), fix the script issue first and re-run.
Write in the same language the user is using.

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Internal development tool that performs a comprehensive quality audit of all marketing skills and agents. Reviews description overlap, format consistency, feature adoption, and structural patterns. Use when the user says "audit skills", "skill quality review", "check skill health", "are my skills consistent", "monthly skill review", or before releasing a new version of the skills repo.

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Use this skill when the user wants a strategic, cross-functional analysis that connects paid, organic, content, and retention into one unified view. This is NOT a weekly summary — it is a decision engine that finds the hidden connections between channels. Activate when the user says "full marketing review", "how is everything doing", "weekly brain", "give me the full picture", "marketing intelligence report", "what should I focus on this week", "retention and acquisition together", "connect the dots across channels", or any request that implies synthesizing all marketing dimensions into one strategic recommendation. Do NOT use for simple weekly overviews or single-channel questions — those belong to ds-channel-report or the individual channel skills. This skill launches parallel subagents. Works best with Dataslayer MCP connected. Also works with manual data.

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ds-channel-report

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Use this skill when the user wants a quick, factual weekly or periodic overview of marketing metrics across channels. This is a lightweight report with numbers and anomalies — no subagents, no strategic synthesis. Activate when the user says "weekly report", "how did we do this week", "give me a marketing summary", "cross-channel report", "what happened with our marketing", "channel performance", "marketing digest", "weekly metrics", or asks for a combined view of organic and paid results. Do NOT use when the user wants strategic recommendations or cross-channel connections — that belongs to ds-brain. Works best with Dataslayer MCP connected. Also works with manual data.

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ds-churn-signals

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Use this skill when the user wants to identify accounts at risk of churning, understand why users are cancelling, or find early warning signals before churn happens. Activate when the user says "churn analysis", "who might cancel", "accounts at risk", "why are people leaving", "usage drop", "inactive accounts", "retention analysis", "predict churn", or asks about subscription health, cancellation patterns, or which users are disengaged. Works best with Dataslayer MCP connected (Stripe + analytics). Also works with manual data.

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ds-content-perf

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Use this skill when the user wants to understand how their blog or content is performing in terms of traffic, engagement, and conversions. Activate when the user says "how is our blog doing", "which posts are driving trials", "content performance", "is our content working", "what should we write next", "which articles bring the most signups", "content audit", "blog SEO", "content SEO performance", or asks about the relationship between content and registrations or conversions. Works best with Dataslayer MCP connected (GA4 + Search Console). Also works with manual data.

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ds-eval

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Internal development tool that tests whether skill descriptions trigger correctly for different user inputs. Reads test cases from a YAML file and evaluates each one by matching the input against all skill descriptions. Use when the user says "run triggering eval", "test skill descriptions", "check triggering accuracy", "eval skills", or after editing a skill description to verify it still triggers correctly.

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name	ds-lint
description	Internal development tool that validates all SKILL.md and agent .md files against the Claude Code spec. Checks frontmatter completeness, field validity, allowed-tools presence, line count, hardcoded paths, and description quality. Use when the user says "lint skills", "validate skills", "check skill quality", "run the linter", "are my skills valid", or before shipping changes to the skills repo.
model	haiku
allowed-tools	Bash(python *), Read

Skill linter (ds-lint)

You are a QA tool for Claude Code skills. Your job is to run the linter script and present the results clearly.

Process

Run the linter:

python "${CLAUDE_SKILL_DIR}/scripts/lint_skills.py" "${CLAUDE_SKILL_DIR}/../.."

Present the results to the user as-is. Do not reformat or summarize — the linter output is already structured.
If there are errors (FAIL status), list the top 3 most critical fixes and offer to apply them.
If there are only warnings, explain which ones are worth fixing and which are acceptable trade-offs.

Rules

Never modify skill files without the user's explicit approval.
If the linter script itself fails (import error, etc.), fix the script issue first and re-run.
Write in the same language the user is using.