Name: data-storytelling
Rating: 39.2 (1 reviews)
Author: administrakt0r

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data-storytelling

Transform raw data into compelling narratives that drive decisions and inspire action.

Quality

38%

Does it follow best practices?

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tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/data-storytelling/SKILL.md

The canonical home for this skill is data-storytelling in administrakt0r/AI-Agents-Safe-Coding-Skills

Quality

Content

38%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 offers useful concrete templates but is verbose, explains concepts Claude already knows, and provides only vague operational workflow. Progressive disclosure is weak: nearly everything is inlined and the single external reference is broken.

Suggestions

Trim the conceptual primer (story structure, narrative arc, three pillars) that Claude already knows, and keep the body as a concise overview pointing to detail files.

Move the three full framework templates, presentation templates, and visualization techniques into separate reference files (e.g. references/frameworks.md, references/templates.md) linked one level deep, and fix the 'resources/implementation-playbook.md' path so it resolves to a real file.

Make the matplotlib example copy-paste ready by defining the placeholder variables or explicitly marking them as inputs, and replace generic Instruction bullets with a concrete, sequenced workflow with explicit verification steps.

Dimension	Reasoning	Score
Conciseness	The ~460-line body spends sections explaining concepts Claude already knows (story structure, narrative arc, the three pillars) and pads with large boilerplate templates, matching the 'noticeably verbose; several unnecessary explanations or padded sections' anchor.	2 / 5
Actionability	Concrete markdown framework templates and a matplotlib example are provided, but the Python snippet references undefined variables (dates, revenue, launch_date) and the Instructions section is generic, fitting the 'some concrete guidance but incomplete / missing key details' anchor.	3 / 5
Workflow Clarity	Sequences exist (narrative arc, 7-slide Data Story Flow) but operational instructions like 'Apply relevant best practices and validate outcomes' are vague with no explicit checkpoints, matching the 'steps present but checkpoints missing or implicit' anchor.	3 / 5
Progressive Disclosure	It is largely monolithic with all frameworks, templates, and visualization guidance inlined, and its one external reference ('resources/implementation-playbook.md') points to a non-existent path with no bundle file present, matching the 'content that belongs in separate files is inlined; references buried' anchor.	2 / 5
	Total	10 / 20 Passed

Description

37%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 reads as a marketing tagline: it conveys a clear purpose but lacks concrete capability verbs, natural trigger phrases, and any explicit 'use when' guidance. It is distinguishable but only weakly so due to generic outcome language.

Suggestions

Replace buzzwords with concrete actions, e.g. 'Structure analytics into setup-conflict-resolution narratives, draft executive summaries and QBR decks, and recommend actions backed by metrics.'

Add an explicit trigger clause such as 'Use when presenting analytics to executives, writing data-driven reports, or building investor or quarterly business review presentations.'

Include natural user terms ('executive summary', 'quarterly business review', 'data-driven report', 'investor presentation') so the skill triggers on how users actually phrase these requests.

Dimension	Reasoning	Score
Specificity	The phrase 'Transform raw data into compelling narratives' names the domain and one generic action, but 'drive decisions and inspire action' are outcomes/buzzwords rather than concrete capabilities, matching the anchor where actions are minimal or generic.	2 / 5
Completeness	It states a clear 'what' (transform data into narratives) but provides no explicit 'when' / 'Use when...' clause, so per the missing-trigger cap it sits at the anchor for a clear 'what' with 'when' absent.	3 / 5
Trigger Term Quality	'raw data' and 'narratives' are only one or two generic keywords; natural user phrases like 'presentation', 'executive summary', 'quarterly review', or 'dashboard' are missing, fitting the anchor for sparse generic keywords without natural phrasing.	2 / 5
Distinctiveness Conflict Risk	'data' + 'narratives' carves out a niche but the vague outcome language overlaps with general presentation, reporting, and writing skills, matching the 'somewhat specific but could still overlap' anchor.	3 / 5
	Total	10 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: administrakt0r/AI-Agents-Safe-Coding-Skills
Path: plugins/AI-Agents-Safe-Coding-Skills-claude/skills/data-storytelling/SKILL.md
Commit: 57c135b

Reviewed: 3 days ago

Table of Contents

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