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customer-research

Conduct, analyze, and synthesize customer research including surveys, interviews, and community mining to build personas and uncover jobs-to-be-done.

Quality

78%

Does it follow best practices?

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SecuritybySnyk

Passed

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Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills/skills/customer-research/SKILL.md

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

SKILL.md
Quality
Evals
Security

Quality

Content

82%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.

A well-structured, highly actionable skill body that assumes Claude's competence and offloads platform-specific detail to a real, clearly signaled reference file. Its main weaknesses are minor verbosity and the lack of explicit validate-and-retry loops in the research workflow.

DimensionReasoningScore

Conciseness

The body is directive and table-driven with almost no explanation of concepts Claude already knows, but includes minor padding such as the roleplay line 'You are an expert customer researcher' and framing sentences like 'Online communities are where customers speak without a filter'. Not a 5 because a few sentences could be trimmed without losing guidance.

4 / 5

Actionability

Copy-paste-ready templates (persona structure, research synthesis template), concrete thresholds (5-10 data points per segment, 12-month recency window, 3+ independent sources for High confidence), and explicit extraction fields give fully executable guidance for an instruction-only skill. Not below 5 — every section tells Claude exactly what to produce and by what criteria.

5 / 5

Workflow Clarity

Clear sequence (context check → mode selection → extraction → synthesis → deliverable) with quality checkpoints (confidence labeling, sample bias checks, minimum viable sample, 'Ask the user which deliverable(s) they need'). Not a 5 because there are no explicit validate-and-retry feedback loops, and the guardrails act as implicit rather than enforced checkpoints.

4 / 5

Progressive Disclosure

One clearly signaled, one-level-deep reference ('read references/source-guides.md for detailed playbooks, search operators, and per-platform extraction tips') that exists in the bundle, with per-platform detail correctly offloaded. Not a 5 because the ~270-line body could move a bit more (e.g., persona template or extraction framework) into references to keep SKILL.md a tighter overview.

4 / 5

Total

17

/

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.

A specific, well-scoped description with natural trigger nouns and low conflict risk, but it omits any 'Use when...' clause, forcing users to rely on keywords alone to discover the skill. Adding explicit trigger guidance and a few missing synonyms (voice of customer, review mining) would make it excellent.

Suggestions

Append an explicit trigger clause, e.g. 'Use when the user mentions customer research, ICP research, voice of customer, survey analysis, review mining, or building personas.'

Add missing natural synonyms such as 'voice of customer', 'ICP research', and 'review mining' that the body's When-to-Use section already lists.

Mention review/ticket mining among the covered methods so the 'what' matches the skill's actual Mode 1 scope.

DimensionReasoningScore

Specificity

Lists several concrete actions ('conduct, analyze, and synthesize customer research', 'build personas', 'uncover jobs-to-be-done') with domain-specific objects (surveys, interviews, community mining). Not a 5 because coverage has gaps — review mining, VOC, and win/loss analysis from the skill body are absent.

4 / 5

Completeness

The 'what' is clear and concrete, but there is no 'Use when...' clause or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines. It is not a 2 because the 'what' is specific rather than vague.

3 / 5

Trigger Term Quality

Contains natural phrases users would say ('customer research', 'surveys', 'interviews', 'personas', 'jobs-to-be-done'). Not a 5 because common variations present in the body's When-to-Use list ('voice of customer', 'ICP research', 'review mining') are missing from the description.

4 / 5

Distinctiveness Conflict Risk

Distinct niche vocabulary (personas, jobs-to-be-done, community mining) makes confusion with unrelated skills unlikely. Not a 5 because it could mildly overlap with adjacent research/marketing skills (copywriting research, churn analysis) that share the term 'customer research'.

4 / 5

Total

15

/

20

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.

Validation — 15 / 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

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills/skills/customer-research/SKILL.md

Reviewed

Table of Contents

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