Name: gpt-trainer
Rating: 56.8 (1 reviews)
Author: membranedev

gpt-trainer

Gpt-trainer integration. Manage Users, Roles, Goals, Pipelines, Filters, Organizations. Use when the user wants to interact with Gpt-trainer data.

Quality

65%

Does it follow best practices?

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Securityby

Low

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Quality

Content

68%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 body is a strong, executable integration guide: concrete CLI commands, a useful action catalog table, and clear state-handling for connections. Its main weaknesses are an undefined 'Step 2' reference and the absence of validation/confirmation steps for destructive actions like delete.

Suggestions

Define or remove the undefined 'Step 2' (referenced in the 'Connecting to Gpt-trainer' section but never shown), so the workflow does not dead-end.

Add an explicit validate-or-confirm checkpoint before destructive/batch actions (e.g. 'Confirm the UUID before running delete-* actions; deletions are irreversible').

Trim the opening background paragraph ('Gpt-trainer is a platform that allows users to fine-tune...') since Claude can infer it, or move it to a one-line note.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient executable commands and tables with minimal padding; the opening platform description ('a platform that allows users to fine-tune...') is somewhat unnecessary background Claude could infer, but it is short and the rest earns its place.	4 / 5
Actionability	Provides concrete, copy-paste-ready shell commands for install, login, connection, action search, action run, and proxy requests, plus a tabulated action catalog; minor gaps are the placeholder 'CONNECTION_ID' and the glossed-over Step 2 reference.	4 / 5
Workflow Clarity	Connection setup is sequenced with state polling (READY/BUILDING/CLIENT_ACTION_REQUIRED/CONFIGURATION_ERROR), but it references a 'Step 2' that is never defined, and the destructive/batch actions (delete) lack any validation or confirm-before-acting checkpoint, capping this dimension at 3.	3 / 5
Progressive Disclosure	Content is well-organized into headed sections (Install, Authentication, Connecting, Searching, Popular actions, Running actions, Proxy, Best practices) with no bundle files and no nested references; the lone gap is an undefined 'Step 2' pointer that breaks navigation slightly.	4 / 5
	Total	15 / 20 Passed

Description

62%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 is third-person, names the product and its managed objects, and includes a 'Use when' trigger clause, placing it above the midpoint. It is held back by the generic 'Manage' verb and trigger phrasing that omits the natural terms ('fine-tune', 'chatbot', 'train') a user would actually say.

Suggestions

Replace the generic verb 'Manage' with the concrete actions this skill performs, e.g. 'Create, list, update, and delete Users, Roles, Goals, Pipelines, Filters, and Organizations'.

Add natural trigger terms users actually say, e.g. 'Use when the user wants to fine-tune or train a GPT model, manage chatbot data sources and sessions, or administer a Gpt-trainer account'.

Tie the 'when' clause to concrete scenarios rather than the abstract phrase 'interact with Gpt-trainer data'.

Dimension	Reasoning	Score
Specificity	Lists the domain objects ('Manage Users, Roles, Goals, Pipelines, Filters, Organizations') but the action verb 'Manage' is generic, and it does not list multiple concrete distinct actions per object, only an umbrella verb.	3 / 5
Completeness	Answers 'what' ('Manage Users, Roles, Goals, Pipelines, Filters, Organizations') and 'when' ('Use when the user wants to interact with Gpt-trainer data'), though the 'when' clause is broad and could be more specific about the triggering scenarios.	4 / 5
Trigger Term Quality	Includes the product name 'Gpt-trainer' and 'interact with Gpt-trainer data' as triggers, but lacks common synonyms, file extensions, or the natural user phrasings ('fine-tune', 'train a chatbot') that would prompt this skill.	3 / 5
Distinctiveness Conflict Risk	The Gpt-trainer product name plus its specific object list gives it a clear niche with minimal conflict risk against other skills, though the generic 'Manage ... Use when ... interact with ... data' pattern could overlap with other integration skills.	4 / 5
	Total	14 / 20 Passed

Validation

93%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: membranedev/application-skills
Path: skills/gpt-trainer/SKILL.md
Commit: f484c82

Reviewed: 5 days ago

Table of Contents

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