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compress-prompt

Compress a Rosetta KB prompt artifact (skill · workflow · phase · rule · agent · template · generic) by stripping structural tautology and ineffective scaffolding while preserving every importance-bearing token. Use when the user asks to compress, shorten, tighten, densify, or reduce a prompt / skill / workflow / phase / rule file.

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

75%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.

An unusually dense, self-aware skill body that trusts the reader and gives a sequenced, validation-gated workflow with real feedback loops. Its main flaw is ironic: it fails its own anti-echo rules — duplicated HARD CAP/DENSIFY rules, twin HITL presentation steps, and a few garbled filler lines — which cost it both conciseness and workflow precision.

Suggestions

Apply the skill's own CUT pass to its body: the '<10 words' HARD CAP is stated in both '## COMPRESS' and TRANSFORM pass 4, and 'DENSIFY EVERY rule' (Mental model) duplicates '## COMPRESS' — keep one authoritative copy of each.

Differentiate or merge Process steps 4 and 7, which are currently identical 'present to the user → word Δ + where cuts came from + reasoned take' steps; the duplication makes the intended number of user checkpoints ambiguous.

Rewrite garbled or filler lines for precision: 'Restated the same thing in different ways.', 'Cut the fluff', and 'we can loose 2% of value' (typo: 'lose'; also 'less then' → 'less than' in the Lessons-learned template).

DimensionReasoningScore

Conciseness

The body is genuinely dense — terse cues, unicode connectives (→ ⇒ ≠), no explanation of concepts Claude already knows ('Reader is AI like you, capable'). Not 5 because it violates its own anti-echo rule: the <10-word HARD CAP appears both in '## COMPRESS' and verbatim in TRANSFORM pass 4, 'DENSIFY EVERY rule' in the Mental model duplicates '## COMPRESS' content, and filler lines like 'Cut the fluff' and 'Restated the same thing in different ways.' (itself garbled) earn no place.

4 / 5

Actionability

Concrete, executable guidance dominates: an exact grammar-command table with semantics, named schema files to read, four ordered TRANSFORM passes with a fixpoint loop condition, and specific verification questions. Not 5 because some directives are loose — the subagent spec 'Sonnet-5.5 low reasoning or GPT 6 Luna medium class' is non-executable shorthand, and 'take different options, iterate multiple times TRANSFORM' in the Mental model is vague direction rather than instruction.

4 / 5

Workflow Clarity

The 8-step HITL process is clearly sequenced with explicit validation: subagent verification (step 5), critical evaluation of findings before applying (step 6), and a user-approval gate before any overwrite (step 8), plus a repeat-until-no-change loop in TRANSFORM. Not 5 because steps 4 and 7 are word-for-word duplicate 'present to the user' steps and step 3 bundles drafting, fixpoint iteration, and no-overwrite into one multi-action line, which muddies the sequence.

4 / 5

Progressive Disclosure

No bundle files exist, and the single file is well-sectioned (## Mental model, ## CUT, ## COMPRESS, ## TRANSFORM, ## Process, ## Lessons learned) with clear headers. Not 5 because at ~120 lines the grammar-command table and seven-path schema list are stable reference material that could sit in a one-level-deep reference file to keep SKILL.md lean, and Mental-model bullets scatter rules later restated in dedicated sections.

4 / 5

Total

16

/

20

Passed

Description

87%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 strong description: concrete domain, explicit mechanism, third-person voice, and a complete 'Use when' clause with genuine trigger synonyms. The only weakness is modest synonym coverage (missing 'condense'/'trim', including the unnatural 'densify').

DimensionReasoningScore

Specificity

Names the domain (Rosetta KB prompt artifacts, with all seven types enumerated) and several concrete actions — 'stripping structural tautology', removing 'ineffective scaffolding', 'preserving every importance-bearing token'. Not 5 because it covers a single primary action with modifiers rather than multiple specific capabilities (e.g. the verification/HITL process is absent); not 3 because it lists more than the 1-2 concrete actions that anchor requires.

4 / 5

Completeness

Explicitly answers both: the 'what' ('Compress a Rosetta KB prompt artifact ... by stripping structural tautology and ineffective scaffolding while preserving every importance-bearing token') and the 'when' ('Use when the user asks to compress, shorten, tighten, densify, or reduce a prompt / skill / workflow / phase / rule file') with concrete trigger phrases, in third person.

5 / 5

Trigger Term Quality

'compress, shorten, tighten, densify, or reduce a prompt / skill / workflow / phase / rule file' gives good synonym coverage plus the artifact types users would name. Not 5 because common variations like 'condense', 'trim', or 'minify' are missing and 'densify' is author jargon rather than a phrase a user would naturally say.

4 / 5

Distinctiveness Conflict Risk

'Rosetta KB prompt artifact (skill · workflow · phase · rule · agent · template · generic)' pins a clear niche that no general-purpose skill occupies, and the triggers are tied to compressing those specific artifact types — minimal risk of firing for the wrong skill.

5 / 5

Total

18

/

20

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

griddynamics/rosetta

Path

.claude/skills/compress-prompt/SKILL.md

Reviewed

Table of Contents

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