Name: apisecai
Rating: 54.400000000000006 (1 reviews)
Author: membranedev

apisecai

Apisec.ai integration. Manage data, records, and automate workflows. Use when the user wants to interact with Apisec.ai data.

Quality

61%

Does it follow best practices?

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Securityby

Passed

No findings from the security scan

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tessl review fix ./skills/apisecai/SKILL.md

Quality

Content

61%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 highly actionable with copy-pasteable CLI commands and a well-structured connection workflow, but it carries introductory padding and lacks validation/verification steps around action execution. Organization is good for a single file but some reference material could be externalized.

Suggestions

Trim concept-explaining prose such as the Apisec.ai platform description and 'auth plumbing' motivation; assume Claude knows these and lead with the commands.

Add a verification step around action execution, e.g. check the response 'output' field and confirm expected record counts or status before treating a destructive/batch action as complete.

Consider moving the proxy flag reference table and the connection state-machine details into a separate reference file and linking from SKILL.md to keep the overview lean.

Dimension	Reasoning	Score
Conciseness	Quotes like 'Apisec.ai is a platform that helps companies protect their APIs from security threats...' and 'so you can focus on the integration logic rather than auth plumbing' explain context Claude largely already knows and add padding, fitting the 'mostly efficient but includes some unnecessary explanation' anchor. Not a 4 because several introductory and motivational sentences could be trimmed.	3 / 5
Actionability	Quotes 'membrane connection ensure "https://www.apisec.ai/" --json', 'membrane action run <actionId> --connectionId=... --json', and the proxy flag table provide concrete executable commands with minor placeholder gaps, matching the 'mostly executable guidance with minor gaps' anchor. Not a 5 because no concrete action id or real input payload is shown and 'Use action names and parameters as needed' is vague.	4 / 5
Workflow Clarity	The connection flow has a clear state-machine sequence (ensure -> poll -> READY/CLIENT_ACTION_REQUIRED/CONFIGURATION_ERROR), but running actions and automating workflows against the API lacks verification steps, so the destructive/batch validation cap applies. Not a 4 because validation checkpoints for action execution and result verification are missing.	3 / 5
Progressive Disclosure	Quotes the section headers '## Working with Apisec.ai', '### Connecting to Apisec.ai', '## Popular actions', and '## Best practices' show a well-organized single-file structure with clear navigation; no bundle files exist to reference. Not a 5 because at ~120 lines some material (proxy options, action schemas) could be split into reference files, leaving minor organization gaps.	4 / 5
	Total	14 / 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 cleanly answers both what and when and anchors on a distinct named product, but its action language is generic and trigger-term coverage is limited to the product name. It sits solidly above the midpoint across all dimensions without reaching the top anchors.

Suggestions

Replace generic verbs with concrete capabilities, e.g. 'List API endpoints, review security test results, and trigger scans' instead of 'Manage data, records, and automate workflows'.

Add natural trigger terms and synonyms a user might say, such as 'API security testing', 'API vulnerabilities', or 'Apisec scans', to broaden trigger coverage beyond the product name.

Tighten the 'Use when' clause with specific triggers, e.g. 'Use when the user wants to scan APIs, review API test results, or manage Apisec.ai inventory.'

Dimension	Reasoning	Score
Specificity	Quotes 'Manage data, records, and automate workflows' name the domain plus a few actions, but the verbs are generic ('manage', 'automate') rather than concrete, matching the anchor that lists 1-2 actions without comprehensive coverage. Not a 2 because multiple action nouns are named; not a 4 because no specific concrete operations are described.	3 / 5
Completeness	Quotes 'Apisec.ai integration. Manage data, records, and automate workflows' answer the what, and 'Use when the user wants to interact with Apisec.ai data' answer the when, satisfying both. Not a 5 because the 'when' trigger and the 'what' actions are generic rather than concrete trigger phrases.	4 / 5
Trigger Term Quality	Quotes 'Apisec.ai data' and 'interact with Apisec.ai data' provide the natural product name users would say, but synonyms and common variations are missing, fitting the 'some relevant keywords but missing common variations' anchor. Not a 4 because coverage beyond the product name is thin.	3 / 5
Distinctiveness Conflict Risk	Quotes 'Apisec.ai integration' and 'interact with Apisec.ai data' tie the skill to a distinct named product, giving mostly distinct triggers with minimal conflict risk. Not a 5 because the generic action phrasing ('manage data, records, automate workflows') leaves minor overlap risk with other data-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/apisecai/SKILL.md
Commit: f484c82

Reviewed: 3 days ago

Table of Contents

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