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chatgpt-app-submission

Inspect a ChatGPT Apps MCP server codebase and generate chatgpt-app-submission.json with app info suggestions, tool hint justifications, test cases, and negative test cases, then report review-check findings and outputSchema warnings for submission review.

62

Quality

72%

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tessl review fix ./plugins/openai-developers/skills/chatgpt-app-submission/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 a clear, validated workflow and a precise output contract, but it is a single self-contained file whose large inline examples and repeated approval-gate rule leave room for token savings and progressive disclosure via reference files.

Suggestions

Move the full output-contract JSON example and the good/bad justification examples into a references file (e.g. references/output-contract.md) and link to it from the body to improve progressive disclosure.

Consolidate the repeated 'ask the developer for approval before editing source' rule into a single stated policy referenced once, instead of restating it in Workflow, Hint Rules, and Tool Descriptor/CSP Rules.

DimensionReasoningScore

Conciseness

The body avoids explaining concepts Claude already knows and is mostly lean directive prose, but the 'ask the developer for approval before editing source' rule recurs across Workflow, Hint Rules, and Tool Descriptor/CSP Rules and could be consolidated.

2 / 3

Actionability

It provides a complete executable output contract JSON, an exact category enum, the exact warning text and URL, and precise counts (five positive, three negative test cases), giving copy-paste-ready guidance.

3 / 3

Workflow Clarity

The numbered 1–8 workflow is clearly sequenced with explicit validation checkpoints (compare annotations vs. behavior) and a stop-and-ask approval feedback loop when hints mismatch, matching the clear-sequence-with-validation anchor.

3 / 3

Progressive Disclosure

The file is well-organized into clearly labeled sections with no nested references, but it is a single monolithic document with a large inline JSON output contract and justification examples that could be split into reference files.

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 specific and well-scoped to a clear niche, but it omits an explicit 'Use when…' trigger clause and its keywords are more technical than naturally conversational, capping completeness and trigger-term quality at 2.

Suggestions

Add a 'Use when…' clause naming the natural trigger, e.g. 'Use when a developer needs to prepare a chatgpt-app-submission.json for a ChatGPT Apps MCP server submission.'

Soften the technical phrasing with natural user-facing terms (e.g. 'ChatGPT app submission', 'MCP server submission') alongside the precise filename.

DimensionReasoningScore

Specificity

Names multiple concrete actions — 'Inspect a ChatGPT Apps MCP server codebase', 'generate chatgpt-app-submission.json with app info suggestions, tool hint justifications, test cases, and negative test cases', and 'report review-check findings and outputSchema warnings' — matching the multiple-specific-actions anchor.

3 / 3

Completeness

It clearly answers 'what' (inspect, generate, report) but provides no 'Use when…' clause or equivalent explicit trigger guidance, so completeness is capped at 2 per the judging guidelines.

2 / 3

Trigger Term Quality

Relevant domain keywords like 'ChatGPT Apps MCP server', 'chatgpt-app-submission.json', and 'submission review' are present, but they lean technical and lack the common natural variations (e.g. 'ChatGPT app submission', 'MCP submission') that the top anchor expects.

2 / 3

Distinctiveness Conflict Risk

The niche is sharply defined — generating a ChatGPT Apps submission JSON from an MCP server codebase — with distinct triggers that are unlikely to overlap with other skills.

3 / 3

Total

10

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
openai/plugins
Reviewed

Table of Contents

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