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skill-meta-prompt

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

52

Quality

58%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

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

Quality

Content

62%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.

The skill delivers a clear, well-sequenced six-phase workflow with strong templates, embedded verification checklists, and error-recovery paths — its workflow and actionability are solid. Its weaknesses are verbosity (a redundant ASCII diagram, repeated scaffolding, an overlong worked example) and progressive disclosure: no bundle files exist despite four in-text references to them, and time-sensitive model-version guidance is inlined rather than isolated.

Suggestions

Delete the ASCII flowchart (it duplicates the phase headers) and compress the per-technique What/When/How scaffolding to one line each, moving the full worked example into a separate references file.

Resolve the dangling references: either add the referenced files (skills/blocks/*.md, docs/GPT-5.6-PROMPTING.md) to the bundle or inline their essential content as one-line guidance so the Model-Specific Adjustments section is executable.

Move the time-sensitive model roster (Opus 5, GPT-5.6, Sonnet 5, Fable 5.1, Astra) out of the main body into a dedicated, clearly versioned reference file so stale version claims don't pollute the core workflow.

DimensionReasoningScore

Conciseness

The ~35-line ASCII flowchart restates the six phase headers that immediately follow it, every technique repeats a What/When/How scaffold explaining concepts Claude already knows (task decomposition, verification), and the ~70-line worked example plus disclaimer templates pad the file. Multiple padded sections match anchor 2 rather than 3; not 1 because most of the file is operational template, not tutorial prose.

2 / 5

Actionability

Guidance is concrete and copy-paste ready: an exact mandated output format, a Phase-1 question script, complexity and expert-assignment matrices, and error-handling response templates. It sits at anchor 4 rather than 5 because the Model-Specific Adjustments section depends on files that do not exist in the bundle, so those instructions cannot actually be executed as written.

4 / 5

Workflow Clarity

Six phases are clearly sequenced with explicit feedback loops ("If information is missing, ask ONE clarifying question at a time"), error-recovery branches (unclear requirements, over-complex requests, techniques that don't apply), and verification checklists embedded in the output template. This matches anchor 5 (explicit validation steps, feedback loops, checklists).

5 / 5

Progressive Disclosure

Internal sectioning is good, but the body is a ~500-line single file with no bundle at all, while pointing to skills/blocks/codex-host-adapter.md, skills/blocks/frontier-model-routing.md, skills/blocks/fable5-prompting.md, and docs/GPT-5.6-PROMPTING.md — all dangling paths. Content that belongs in separate files (technique deep-dives, model roster, the full example) is inlined, matching anchor 3; broken references and the inlined time-sensitive model-version section keep it below 4.

3 / 5

Total

14

/

20

Passed

Description

53%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.

The description has an explicit use-when trigger and a named domain, but the capability statement is thin and buzzword-heavy, and trigger coverage misses the natural phrasings users would actually say. It is serviceable but below the quality of the reference good examples.

Suggestions

Replace "proven optimization techniques" with the concrete capabilities the skill applies (e.g., task decomposition, fresh-eyes expert review, iterative verification, uncertainty disclaimers) to lift specificity.

Broaden trigger terms to the natural phrases users say: "improve my prompt", "optimize a prompt", "write a better prompt", "prompt engineering", "refine a prompt".

Tighten the use-when clause to concrete trigger situations (e.g., "when the user asks to write, improve, or optimize a prompt") to sharpen distinctiveness and completeness.

DimensionReasoningScore

Specificity

The description names the domain ("Craft better prompts") but offers only one generic action, with "proven optimization techniques" being buzzword phrasing that names no concrete technique. It matches anchor 2 (domain named, actions minimal/generic) rather than 3 because no specific second capability is listed.

2 / 5

Completeness

Both parts are present: "Craft better prompts using proven optimization techniques" gives the what and "use when your prompt needs refinement" explicitly gives the when. It falls short of anchor 5 because the what lacks concrete capability phrasing, and sits above anchor 3 because the when is explicit rather than weakly implied.

4 / 5

Trigger Term Quality

"prompts" and "prompt needs refinement" are relevant keywords, but common natural phrasings users would say ("improve my prompt", "optimize a prompt", "write a prompt", "prompt engineering") are missing. Anchor 3 (some relevant keywords, missing variations/synonyms) fits; not 4 because keyword coverage is thin.

3 / 5

Distinctiveness Conflict Risk

"Craft better prompts" could overlap with general writing or prompt-engineering skills, though the refinement trigger is moderately distinct. Anchor 3 (somewhat specific but could overlap with similar skills) fits; not 4 because nothing concrete distinguishes it from neighboring skills.

3 / 5

Total

12

/

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

skill_md_line_count

SKILL.md is long (505 lines); consider splitting into references/ and linking

Warning

Total

15

/

16

Passed

Repository
nyldn/claude-octopus
Reviewed

Table of Contents

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