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common-skill-creator

Standardizes the creation and evaluation of high-density Agent Skills (Claude, Cursor, Windsurf). Ensures skills achieve high Activation (specificity/completeness) and Implementation (conciseness/actionability) scores. Use when: writing or auditing SKILL.md, improving trigger accuracy, or refactoring skills to reduce redundancy and maximize token ROI.

65

Quality

80%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.github/skills/common/common-skill-creator/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

70%

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

This is a well-structured meta-skill with excellent progressive disclosure and clear workflows. Its main weaknesses are moderate verbosity (ironic given its own compression guidelines) and guidance that stays at the principle/checklist level rather than providing fully executable examples or commands. The skill practices what it preaches regarding structure and references but could be tighter on conciseness and more concrete on actionability.

Suggestions

Add concrete, executable examples for key steps like 'spawn parallel subagents' — show the actual commands or tool invocations rather than describing the concept abstractly.

Reduce redundancy between sections: 'Anti-Patterns' and 'Content Quality' overlap significantly (e.g., no redundant knowledge appears in both); consolidate into a single authoritative list.

Include a concrete before/after SKILL.md example (or reference one) showing a skill being evaluated and improved, making the quality checklist actionable rather than abstract.

DimensionReasoningScore

Conciseness

The skill uses 'Caveman Compression' in places and avoids explaining basic concepts, but it's still verbose for a meta-skill. Several sections (Behavior Guardrails, Anti-Patterns) repeat similar ideas in slightly different forms, and the document exceeds its own stated 100-line limit. Some content like 'No AI-splaining' explanations are somewhat redundant with the core principle already stated.

2 / 3

Actionability

The workflows provide numbered steps which are helpful, and the Caveman Compression example is concrete and illustrative. However, most guidance remains at the level of principles and checklists rather than executable commands or copy-paste-ready artifacts. The 'Test — spawn parallel subagents' step lacks specific commands or tool invocations, and the quality checklist items are abstract targets without concrete measurement methods.

2 / 3

Workflow Clarity

Both the 'New skill' and 'Existing skill' workflows are clearly sequenced with numbered steps, include validation/testing checkpoints (steps 4-6), and have explicit iteration loops. The existing skill workflow includes a snapshot step before edits (a safety checkpoint), and both workflows reference the eval workflow for detailed testing procedures.

3 / 3

Progressive Disclosure

The References section provides clear, well-signaled one-level-deep links to 8 separate reference files, each with a descriptive label and a 'load when' trigger condition. The three-level loading system (frontmatter → body → references/) is explicitly defined and the body appropriately delegates detailed content to reference files.

3 / 3

Total

10

/

12

Passed

Description

89%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This is a well-structured description with explicit 'Use when' triggers and a clearly distinctive niche. Its main weakness is that the capability descriptions lean toward abstract outcomes ('ensures skills achieve high scores') rather than concrete actions. The trigger term coverage is strong with domain-specific keywords that users would naturally use.

Suggestions

Replace abstract outcome language like 'ensures skills achieve high Activation scores' with concrete actions such as 'generates frontmatter YAML, validates trigger terms, scores description quality against rubric criteria'.

DimensionReasoningScore

Specificity

Names the domain (Agent Skills for Claude, Cursor, Windsurf) and some actions (creation, evaluation, auditing, refactoring), but the actions are somewhat abstract—'standardizes creation' and 'ensures skills achieve high scores' are more about outcomes than concrete steps like 'generates frontmatter YAML' or 'validates trigger terms'.

2 / 3

Completeness

Clearly answers both 'what' (standardizes creation and evaluation of agent skills, ensures high activation and implementation scores) and 'when' with an explicit 'Use when:' clause listing three specific trigger scenarios (writing/auditing SKILL.md, improving trigger accuracy, refactoring skills).

3 / 3

Trigger Term Quality

Includes strong natural keywords users would say: 'SKILL.md', 'trigger accuracy', 'Agent Skills', 'Claude', 'Cursor', 'Windsurf', 'auditing', 'refactoring skills', 'token ROI'. These cover multiple natural variations of how a user might request this capability.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive niche—meta-skill about writing and evaluating SKILL.md files specifically. The combination of 'SKILL.md', 'trigger accuracy', 'Activation/Implementation scores', and agent skill platforms creates a clear, unique identity unlikely to conflict with other skills.

3 / 3

Total

11

/

12

Passed

Validation

81%

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

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

Total

9

/

11

Passed

Repository
HoangNguyen0403/agent-skills-standard
Reviewed

Table of Contents

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