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generic-assistant

Fallback authoring playbook for building general-purpose personal assistant agents that do not fit a more specific archetype. Use this only after checking the other archetype skills (coding, spreadsheet, research, customer-support, content-writer, ops-automation). Examples include summarizing emails, drafting short answers, capturing notes, or generic personal-helper agents.

72

Quality

88%

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

87%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

A concise, highly actionable authoring playbook with ready-to-use templates and a full worked example, organized as a clean single file. The main gap is the absence of an explicit step-by-step authoring workflow with validation checkpoints for the builder.

Suggestions

Add a short numbered authoring workflow (e.g. 1. check archetypes → 2. pick name/description → 3. fill system-prompt template → 4. enforce required rules → 5. verify completion criteria) so the builder has an explicit, checkable sequence.

Add a validation/checkpoint step the builder runs before declaring the agent done, mirroring the completion-criteria checklist that the produced agent itself must satisfy.

DimensionReasoningScore

Conciseness

The playbook is lean: it assumes Claude's competence, avoids explaining what an assistant is, and every section (identity template, system-prompt template, rules, anti-patterns, worked example) earns its place without padded concept exposition.

3 / 3

Actionability

Provides copy-paste-ready fill-in templates (system prompt with explicit placeholders), name/description patterns, required rules, and a complete worked example producing a concrete agent — fully executable guidance.

3 / 3

Workflow Clarity

Sections appear in a logical order, but the authoring process is not framed as a numbered sequence with validation checkpoints; the completion-criteria checklist applies to the produced agent rather than to the author's own steps.

2 / 3

Progressive Disclosure

A single, well-organized SKILL.md (~85 lines) with clear section headings and no nested or broken references; no bundle files are needed at this scope, so the flat structure is appropriate and easy to navigate.

3 / 3

Total

11

/

12

Passed

Description

90%

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 strong description: it states the skill's purpose, gives explicit use-conditions as a fallback, enumerates sibling archetypes to disambiguate, and lists concrete example tasks as natural triggers. The only weakness is that the skill's own actions sit at the meta/authoring level, slightly limiting direct specificity.

DimensionReasoningScore

Specificity

Names the domain ('building general-purpose personal assistant agents') and concrete example tasks ('summarizing emails, drafting short answers, capturing notes'), but the core actions are at the authoring/meta level rather than concrete operations the skill directly performs, so it is not a comprehensive list of specific actions.

2 / 3

Completeness

Clearly answers both what ('Fallback authoring playbook for building general-purpose personal assistant agents') and when ('Use this only after checking the other archetype skills…'), with an explicit trigger clause.

3 / 3

Trigger Term Quality

Includes natural terms users would actually say — 'summarizing emails', 'drafting short answers', 'capturing notes', 'personal-helper agents', 'personal assistant' — giving good coverage of real trigger phrasing.

3 / 3

Distinctiveness Conflict Risk

The fallback framing and explicit 'only after checking the other archetype skills' list (coding, spreadsheet, research, customer-support, content-writer, ops-automation) carve out a clear niche and actively reduce conflict risk with sibling skills.

3 / 3

Total

11

/

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
mastra-ai/mastra
Reviewed

Table of Contents

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