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sporkwace/monkey-thought-translator

translate claude skills into chatgpt or codex skills only after auditing purpose, target host, capability parity, resource portability, tool assumptions, and unrealizable behavior. use when the user uploads or points to a claude skill, asks to port a claude skill to chatgpt, codex, or openai skills, or wants a compatibility review before translation. requires a compatibility report, risk score, capability matrix, and user approval before packaging when behavior cannot be preserved faithfully.

83

2.34x
Quality

90%

Does it follow best practices?

Impact

89%

2.34x

Average score across 2 eval scenarios

SecuritybySnyk

Passed

No known issues

Overview
Quality
Evals
Security
Files

Quality

Content

77%

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, highly actionable skill that defines a rigorous translation workflow with clear approval gates, explicit templates, and concrete classification schemes. Its main weaknesses are moderate verbosity (some redundancy in naming logic and overlapping report/output templates) and the inability to verify referenced bundle files. The meta-commentary at the top about Tessl eval runs detracts from professionalism.

Suggestions

Remove the meta-commentary block at the top about Tessl eval runs and optimization suggestions—it's not part of the skill's operational content.

Consolidate the duplicated naming logic (appears in the workflow step 4, the 'Determine the translated skill name' section, and the fallback rules) into a single authoritative section to reduce redundancy.

DimensionReasoningScore

Conciseness

The skill is reasonably efficient for its complexity, but contains some redundancy—the translated skill naming logic is repeated across multiple sections, the compatibility report template and output contract template overlap in fields, and some rules restate what an intelligent agent would infer (e.g., 'Do not introduce new capabilities to fill the gap'). The meta-commentary at the top about Tessl eval runs and optimization suggestions is noise.

2 / 3

Actionability

The skill provides highly concrete, actionable guidance: exact text templates for the compatibility report and output contract, specific decision prompts to use verbatim, a detailed capability classification scheme with four levels, explicit risk score definitions, kebab-case normalization examples, and a clear install/test checklist. Every step is specific enough to execute.

3 / 3

Workflow Clarity

The 11-step required workflow is clearly sequenced with explicit validation checkpoints: stop-and-ask gates when capabilities are host-dependent or unrealizable, user approval required before packaging for high/blocked risk, and a validation step before final output. Failure conditions are enumerated. The feedback loop of inspect → classify → report → approve → translate → validate is well-defined.

3 / 3

Progressive Disclosure

The skill references `references/compatibility-checklist.md`, `references/translation-examples.md`, and `scripts/inspect_skill.py` appropriately, but no bundle files were provided to verify these exist. The SKILL.md itself is quite long (~200+ lines) and some sections like the detailed naming rules or minimum viable translation mode could potentially be moved to reference files. The structure is reasonable but the main file carries substantial inline detail.

2 / 3

Total

10

/

12

Passed

Description

100%

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 strong, well-crafted description that clearly defines a narrow, distinctive task with explicit trigger conditions and detailed capability enumeration. It covers the what, when, and how (prerequisites) comprehensively. The only minor note is the use of lowercase throughout, but this doesn't materially impact clarity or selection accuracy.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: auditing purpose, target host, capability parity, resource portability, tool assumptions, unrealizable behavior, generating compatibility reports, risk scores, capability matrices, and packaging translated skills.

3 / 3

Completeness

Clearly answers both 'what' (translate Claude skills to ChatGPT/Codex skills after auditing multiple dimensions) and 'when' (explicit 'use when' clause covering uploads, porting requests, and compatibility reviews). Also specifies requirements before output.

3 / 3

Trigger Term Quality

Includes strong natural trigger terms users would say: 'claude skill', 'chatgpt', 'codex', 'openai skills', 'port', 'compatibility review', 'translation'. These cover the main ways a user would phrase such a request.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive niche — translating Claude skills to ChatGPT/Codex skills is a very specific task unlikely to overlap with other skills. The combination of platform-specific terms (Claude, ChatGPT, Codex, OpenAI) and the audit/translation workflow creates a clear, unique identity.

3 / 3

Total

12

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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