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data-storytelling

Transform data into compelling narratives using visualization, context, and persuasive structure. Use when presenting analytics to stakeholders, creating data reports, or building executive presentations.

70

1.06x
Quality

56%

Does it follow best practices?

Impact

94%

1.06x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./tests/ext_conformance/artifacts/agents-wshobson/business-analytics/skills/data-storytelling/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

46%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-organized and unusually rich in concrete, usable templates, but it is a 450-line monolith: generic storytelling concepts Claude already knows pad the token cost, and all worked examples live inline with zero progressive disclosure to reference files. Workflow sequencing is clear but lacks any verification checkpoints.

Suggestions

Trim sections that restate known knowledge (Narrative Arc, Transition Phrases, Handling Uncertainty, Best Practices do's/don'ts) to a few lines each, keeping only the skill-specific frameworks, headline formula, and templates.

Move the three full worked story frameworks and the three presentation templates into references/ files (e.g., references/frameworks.md, references/templates.md) and keep SKILL.md as a concise overview with one-level-deep, clearly signaled links to them.

Add a short validation step to the story-construction workflow, e.g., a checklist the draft must pass (headline contains a specific number and business impact; every chart is referenced in the narrative; ends with an explicit ask) before it is considered done.

DimensionReasoningScore

Conciseness

Large portions restate knowledge Claude already has: the six-beat narrative arc, transition phrases like "The data reveals...", correlation-vs-causation caveats in "Handling Uncertainty", and generic do's/don'ts ("Start with the 'so what'", "Use the rule of three") — matching anchor 2's "noticeably verbose; several unnecessary explanations or padded sections". It avoids anchor 1 because it is not a beginner tutorial and the worked examples carry genuine value.

2 / 5

Actionability

As an instruction-only skill it delivers concrete guidance: three fully worked story examples with real numbers, BAD/GOOD headline pairs with an explicit formula, three presentation templates, and a matplotlib annotation snippet. It sits at anchor 4 ("mostly executable... minor gaps") rather than 5 because the matplotlib code references undefined variables (dates, revenue, launch_date, growth_start) and is template-style rather than copy-paste runnable.

4 / 5

Workflow Clarity

A clear sequence is present (the Hook → Context → ... → Call to Action arc and the 7-slide story flow), but validation or checkpoints are entirely absent — nothing tells Claude to check a draft against the framework (e.g., verify the headline states a specific insight) before finishing. This matches anchor 3 ("steps listed but validation gaps; checkpoints missing or implicit") rather than anchor 4, which requires most checkpoints present; no destructive or batch operations apply, so no hard cap is triggered.

3 / 5

Progressive Disclosure

No bundle files exist, and roughly 350 of the ~450 lines are complete worked-example stories, slide-flow templates, and ASCII dashboard layouts inlined directly in SKILL.md with no reference files at all — squarely matching anchor 2's "content that clearly belongs in separate files is inlined". Good section headers keep it above the unstructured worst case, but the body is the opposite of an overview pointing to detailed materials.

2 / 5

Total

11

/

20

Passed

Description

66%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 follows the strong what-plus-when pattern with natural trigger phrases in third-person voice. Its main weaknesses are an abstract "what" clause (buzzword-adjacent phrasing like "persuasive structure"), missing common synonyms such as "data storytelling" itself, and moderate overlap risk with presentation-building and charting skills.

Suggestions

Replace abstract phrasing ("compelling narratives", "persuasive structure") with concrete actions, e.g., "Structure analyses as setup-conflict-resolution narratives, write insight-led headlines, and design executive-ready slide flows and one-page dashboard stories."

Add the skill's own distinctive trigger terms and common synonyms — "data storytelling", "data story", "quarterly business review (QBR)", "executive summary" — to both improve trigger coverage and distinguish it from generic presentation or charting skills.

Sharpen the "when" clause toward decision moments, e.g., "Use when turning analysis results into a stakeholder presentation, report, or recommendation the user needs to approve."

DimensionReasoningScore

Specificity

"Transform data into compelling narratives using visualization, context, and persuasive structure" names the domain and its mechanisms, but "compelling narratives" and "persuasive structure" are abstract rather than a list of concrete actions, matching the anchor for 1-2 concrete actions without comprehensive coverage. It is above anchor 2 (which offers only generic actions) but below anchor 4, which requires several distinct specific actions.

3 / 5

Completeness

It answers both questions explicitly: a "what" ("Transform data into compelling narratives using visualization, context, and persuasive structure") and a "when" ("Use when presenting analytics to stakeholders, creating data reports, or building executive presentations"). The "what" clause is somewhat abstract and the triggers lack the concrete variety of the anchor-5 example, placing it at anchor 4 rather than 5.

4 / 5

Trigger Term Quality

"Presenting analytics to stakeholders", "creating data reports", and "building executive presentations" are phrases users would naturally say, giving good keyword coverage. Common variations are missing — notably "data storytelling"/"story" (the skill's own name), "quarterly business review", "executive summary", and "dashboard" — so it does not reach the comprehensive synonym coverage of anchor 5.

4 / 5

Distinctiveness Conflict Risk

"Building executive presentations" overlaps with presentation/deck-creation skills and "visualization" overlaps with charting skills, while the skill's most distinctive trigger term ("data storytelling") is absent from the description. It is more specific than the generic anchor 2 but still carries real overlap risk with closely related communication and visualization skills, matching anchor 3.

3 / 5

Total

14

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
Dicklesworthstone/pi_agent_rust
Reviewed

Table of Contents

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