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oma-market

Market research skill for pain-point extraction, trend detection, competitor positioning, and discovery across community sources (Reddit, HN, Bluesky, Mastodon, GitHub Issues, web). Built-in harvest fetchers, deterministic CLI compute, intent-auto SWOT/Porter's 5F/PESTEL frameworks. Use for market research, pain point analysis, trend detection, competitor research, user complaints, voice-of-customer, 시장조사, 사용자 페인, 트렌드, 경쟁구도.

75

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

85%

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 operational spec for a multi-stage CLI pipeline with strong validation and recovery guidance. Its main weakness is redundancy, with the pipeline described across several overlapping sections that could be consolidated for token efficiency.

Suggestions

Consolidate the pipeline description so it appears once (e.g. keep the canonical command path plus Default Workflow, and prune the overlapping Scenes and Actions restatements) to reduce redundancy.

The Expected inputs flag list overlaps with the Routes table weights and flags; merge the per-intent flag/weight detail into the Routes table only.

Tighten the Guardrails section, which mixes behavioral rules with implementation notes that read more like reference material than concise operating constraints.

DimensionReasoningScore

Conciseness

The body is information-dense and avoids explaining concepts Claude already knows, but the same CLI pipeline is restated across the Scenes, Actions table, Canonical command path, Default Workflow, and Routes sections, which could be consolidated; this matches the mostly-efficient-but-could-be-tightened anchor rather than the every-token-earns-its-place anchor at 3.

2 / 3

Actionability

Provides a copy-paste-ready bash pipeline (detect-trap | harvest | score | fuse | cluster | render), explicit subcommands, concrete flags, exit codes, and invocation examples, matching the fully-executable anchor rather than the pseudocode/incomplete anchor at 2.

3 / 3

Workflow Clarity

Multi-step process is clearly sequenced (PREPARE→ACT→ACQUIRE→VERIFY→FINALIZE, numbered Default Workflow) with explicit validation checkpoints ("validate JSON at each pipe stage", mandatory LAW self-check) and a fix-and-retry feedback loop with exit-code recovery, matching the clear-sequence-with-validation anchor.

3 / 3

Progressive Disclosure

A clear References section signals one-level-deep resource files (intent-rules, operator-packs, frameworks, execution-protocol, output-laws, examples, checklist, error-playbook) and shared-core links; no bundle directories are present to verify against, so this is scored on the references, which are well-signaled and easy to navigate.

3 / 3

Total

11

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12

Passed

Description

100%

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 concise, third-person, and explicitly covers both capabilities and use-when triggers with natural user phrasing in English and Korean. It is a strong, distinctive description with no notable weaknesses.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — "pain-point extraction, trend detection, competitor positioning, and discovery" and "Built-in harvest fetchers, deterministic CLI compute, intent-auto SWOT/Porter's 5F/PESTEL frameworks" — matching the multiple-specific-actions anchor rather than the single-domain anchor at 2.

3 / 3

Completeness

Explicitly answers both what ("Market research skill for pain-point extraction, trend detection, competitor positioning, and discovery") and when ("Use for market research, pain point analysis, trend detection..."), satisfying the explicit-trigger anchor; not 2 because the when clause is explicit, not implied.

3 / 3

Trigger Term Quality

Natural user phrasing is well covered ("market research, pain point analysis, trend detection, competitor research, user complaints, voice-of-customer") plus Korean equivalents, matching the good-coverage anchor rather than the partial-coverage anchor at 2.

3 / 3

Distinctiveness Conflict Risk

Narrow community-signal market-research niche with distinct triggers and named frameworks is unlikely to fire for unrelated skills, matching the clear-niche anchor rather than the could-overlap anchor at 2.

3 / 3

Total

12

/

12

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
first-fluke/oh-my-agent
Reviewed

Table of Contents

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