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arn-spark-discover

This skill should be used when the user says "discover", "product discovery", "arn discover", "help me define this product", "what should I build", "product concept", "define the product", "let's figure out what to build", "vision for this project", "shape this idea", "new project idea", "brainstorm this product", "starting from scratch", or wants to explore and structure a greenfield product idea through guided conversation. Produces a product-concept.md document capturing the product vision, core experience, target users, trust model, platforms, and scope boundaries.

72

Quality

88%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

The body is a highly actionable, well-sequenced conversational orchestration skill with clean one-level-deep references and strong validation checkpoints. Its main weakness is conciseness: a duplicated decision table and repeated dispatch boilerplate could be consolidated.

Suggestions

Consolidate the duplicate 'Agent Invocation Guide' table (lines 265-284) with the inline decision table (lines 188-207) into a single table to remove ~20 lines of restated guidance.

Factor out the verbatim dispatch-convention boilerplate ('passing the model from .arness/agent-models/spark.md ... see ensure-config.md "Dispatch convention" for fallback'), repeated ~4 times, into one note near its first use.

Tighten the fully-scripted AskUserQuestion prompts in Checkpoints B and C to essential intent and options; Claude can adapt tone without complete verbatim dialog scripts.

DimensionReasoningScore

Conciseness

It does not pad with concepts Claude already knows (no basic explanations of what a product concept is), but it carries real redundancy: the 'Agent Invocation Guide' table (lines 265-284) largely restates the inline decision table (lines 188-207), and the dispatch-convention parenthetical is repeated verbatim ~4 times. This fits 'mostly efficient but could be tightened' rather than the every-token-earns-its-place anchor at 3.

2 / 3

Actionability

Provides concrete, copy-paste-ready guidance: exact agent names and modes (arn-spark-product-strategist, arn-spark-persona-architect 'discovery mode', arn-spark-market-researcher 'identification/plan|search|consolidate'), exact reference file paths, full AskUserQuestion prompts, and the output filename product-concept.md. As an instruction-only skill this matches the level-3 'fully executable / copy-paste ready' anchor.

3 / 3

Workflow Clarity

Clear Step 0 -> Step 5 sequence with explicit validation checkpoints (A-D plus a readiness check), feedback loops ('iterate until the user is satisfied'), a coverage-tracking checklist, and a dedicated error-handling section. No destructive/batch cap applies (document writes are guarded by an existence check), so it sits at the level-3 anchor rather than the implicit-checkpoint anchor at 2.

3 / 3

Progressive Disclosure

The four bundle reference files (discovery-questions.md, product-concept-template.md, persona-profile-template.md, competitive-landscape-template.md) all exist and are referenced one level deep with explicit 'Read ...' signals at the point of use; templates and the question bank are appropriately externalized from the orchestration body. Matches the level-3 anchor; not 2 because reference material is genuinely split out rather than inlined.

3 / 3

Total

11

/

12

Passed

Description

92%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.

The description is strong: third-person voice, explicit what-and-when, and rich natural trigger phrases. Its only weakness is a long, broad trigger list that raises overlap risk with general ideation skills.

DimensionReasoningScore

Specificity

Names concrete actions ('explore and structure a greenfield product idea through guided conversation') and a concrete deliverable ('Produces a product-concept.md document capturing the product vision, core experience, target users, trust model, platforms, and scope boundaries') with seven specific output components, matching the 'lists multiple specific concrete actions' anchor rather than the partial domain-only anchor at 2.

3 / 3

Completeness

Explicitly answers both WHAT (structured guided conversation producing a product-concept.md with named fields) and WHEN ('This skill should be used when the user says...'), matching the level-3 anchor; not 2 because the 'when' is explicit, not merely implied.

3 / 3

Trigger Term Quality

Provides thirteen natural phrases a user would actually say ('discover', 'product discovery', 'arn discover', 'help me define this product', 'what should I build', 'brainstorm this product', 'starting from scratch'), exceeding the coverage of the level-3 anchor example.

3 / 3

Distinctiveness Conflict Risk

The product-concept framing and 'arn discover' trigger carve a niche, but broad catch-all phrases ('what should I build', 'starting from scratch', 'brainstorm this product', 'shape this idea') could overlap with generic ideation/brainstorming skills, matching the 'somewhat specific but could still overlap' anchor rather than the clearly-conflict-free anchor at 3.

2 / 3

Total

11

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
AppsVortex/arness
Reviewed

Table of Contents

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