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qualiobee

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

59

Quality

68%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

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

The content is a tight, executable Membrane CLI integration guide with concrete commands and a well-structured connection-state workflow. It loses a point mostly to minor verbosity and a few implied recovery steps rather than missing functionality.

Suggestions

Trim the best-practice rationales ('This will burn less tokens...') to one-line imperatives since the reasoning is self-evident.

Make the post-CLIENT_ACTION_REQUIRED recovery loop explicit (re-poll, then proceed) as a numbered feedback loop to strengthen validation checkpoints.

Replace repeated placeholder examples (CONNECTION_ID, QUERY) with one clearly-labeled substitution note to avoid restating them in every command.

DimensionReasoningScore

Conciseness

The body is largely command-driven and assumes Claude's competence (auth, polling, proxy are explained tersely); only minor padding ('This will burn less tokens', restated best-practice rationale) could be trimmed.

4 / 5

Actionability

Provides copy-paste CLI commands with flags and `--json` examples for install, auth, connection, action list/run, and proxying; minor gaps such as placeholder `CONNECTION_ID` and `QUERY` tokens are clearly marked.

4 / 5

Workflow Clarity

The connection lifecycle is sequenced with explicit polling (`--wait`) and branching on `READY` / `CLIENT_ACTION_REQUIRED` / error states, giving clear checkpoints; a couple of recovery transitions (e.g. re-auth after action completion) are implied rather than spelled out.

4 / 5

Progressive Disclosure

No bundle files exist, but the single SKILL.md is well-organized under clear headers (Install, Authentication, Connecting, Searching, Popular actions, Best practices) with no nested references, fitting a self-contained CLI skill.

4 / 5

Total

16

/

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 states both purpose and trigger condition for a named platform, giving it solid completeness and distinctiveness. It is held back by generic capability wording ('data, records') and a near-total reliance on the brand name for trigger terms.

Suggestions

Replace generic verbs with Qualiobee's actual capabilities, e.g. 'Collect, analyze, and act on customer feedback, surveys, and feature requests.'

Add natural trigger phrases users would say, such as 'feedback', 'survey responses', or 'customer insights', not just 'Qualiobee data'.

Make the 'Use when' clause more concrete: 'Use when the user wants to manage Qualiobee feedback, records, or automate review workflows.'

DimensionReasoningScore

Specificity

Names the domain (Qualiobee) and a few concrete actions ('Manage data, records, and automate workflows'), but the actions are generic ('data', 'records') rather than the platform's actual feedback-management operations.

3 / 5

Completeness

Explicitly answers both what ('Manage data, records, and automate workflows') and when ('Use when the user wants to interact with Qualiobee data'); the trigger clause is present but only moderately specific.

4 / 5

Trigger Term Quality

Relies almost entirely on the proper noun 'Qualiobee' repeated ('Qualiobee data', 'interact with Qualiobee data') with no common synonyms or natural variations a user would say beyond the brand name.

3 / 5

Distinctiveness Conflict Risk

Tied to a specific proprietary app (Qualiobee), so trigger risk is low and conflict with other skills is minimal; only slight overlap risk with generic 'data management' skills.

4 / 5

Total

14

/

20

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
membranedev/application-skills
Reviewed

Table of Contents

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