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skill-meta-prompt

Craft better prompts using proven optimization techniques — use when your prompt needs refinement

61

Quality

72%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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tessl review fix ./.claude/skills/skill-meta-prompt/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

77%

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

The content is highly actionable with concrete templates and a clearly sequenced, verification-rich workflow. Its main weaknesses are token verbosity from decorative scaffolding and a monolithic structure that does not offload detail into bundled reference files.

Suggestions

Trim the ASCII flow diagram and the repeated What/When/How/Example scaffolding to reduce token load, assuming Claude's competence with the meta-prompting concepts.

Move the model-specific adjustment details and the full worked example into reference files under references/ and link to them one level deep, keeping SKILL.md an overview.

DimensionReasoningScore

Conciseness

The body is mostly instructional rather than padded with basic concepts Claude knows, but the large ASCII flow diagram and repeated What/When-to-use/How-to-apply/Example scaffolding across five techniques add length that could be tightened.

2 / 3

Actionability

It provides copy-paste-ready templates, an exact mandated output format ("You MUST return the generated prompt in this exact format"), a concrete expert-archetype table, and a fully worked API-documentation example — actionable guidance for an instruction-only skill.

3 / 3

Workflow Clarity

The six phases are clearly sequenced with explicit verification checkpoints, feedback loops (Technique 3 Iterative Verification, verification checklists), and error-handling branches, matching the strong-workflow anchor.

3 / 3

Progressive Disclosure

Sections are well organized, but the ~500-line body is largely a monolithic wall of text and the referenced paths (skills/blocks/*, docs/GPT-5.6-PROMPTING.md) are not present in the bundle, so content that could be split into reference files remains inline.

2 / 3

Total

10

/

12

Passed

Description

67%

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 includes an explicit Use-when trigger, satisfying completeness. It is weakened by abstract capability language and limited trigger-term coverage, leaving it distinguishable but not sharply niche.

Suggestions

Replace the abstract "proven optimization techniques" with concrete actions the skill performs, e.g. "Decompose tasks, assign expert personas, and add verification steps to prompts".

Broaden trigger terms to natural phrasings users would say — "optimize", "improve", "rewrite", or "debug my prompt" — not only "needs refinement".

DimensionReasoningScore

Specificity

"Craft better prompts using proven optimization techniques" names the domain and a broad action but does not list multiple concrete actions; the phrase "proven optimization techniques" is abstract rather than enumerating what the skill actually does.

2 / 3

Completeness

It explicitly answers both what ("Craft better prompts using proven optimization techniques") and when ("use when your prompt needs refinement"), with an explicit Use-when trigger clause present.

3 / 3

Trigger Term Quality

"use when your prompt needs refinement" and "Craft better prompts" are natural terms, but coverage is thin — common variations like "optimize", "improve", "rewrite", or "debug my prompt" are missing.

2 / 3

Distinctiveness Conflict Risk

"Craft better prompts" is a somewhat generic improvement framing that could overlap with general writing or coding-improvement skills, though the prompt-refinement trigger narrows the niche moderately.

2 / 3

Total

9

/

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

skill_md_line_count

SKILL.md is long (503 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
nyldn/claude-octopus
Reviewed

Table of Contents

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