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bland-ai

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

Quality

63%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/bland-ai/SKILL.md
SKILL.md
Quality
Evals
Security

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 content is a highly actionable, executable guide to driving Bland AI through the Membrane CLI, with concrete commands and strong connection-state handling. Its main flaws are leftover placeholder junk in the overview, a dangling "Step 2" reference, and no validation guidance for the destructive/batch operations it advertises.

Suggestions

Delete the placeholder lines ("I don't have enough information about this app..." and the "Official docs: I am sorry, but I cannot provide..." paragraph) and replace them with a two-sentence factual overview of Bland AI.

Fix the dangling "skip to **Step 2**" references by labeling the Searching/Running sections as numbered steps.

Add a brief verification step after running batch or destructive actions (e.g. re-check batch state with get-batch, or confirm call status) so the workflow includes a feedback loop.

DimensionReasoningScore

Conciseness

The bulk of the body is efficient command blocks and tables, but it carries several padded sections: leftover placeholder text ("I don't have enough information about this app to accurately describe it. Please provide more details.", "Official docs: I am sorry, but I cannot provide an official API...") and filler like "Use action names and parameters as needed", placing it between the 2 and 3 anchors.

3 / 5

Actionability

Guidance is fully executable throughout: copy-paste-ready commands for install ("npm install -g @membranehq/cli@latest"), login, connection setup, action discovery/run with JSON inputs, and proxy requests with a complete flag table, plus an 18-row catalog of concrete actions with keys — matching the top anchor.

5 / 5

Workflow Clarity

The setup sequence is clear with a real validation checkpoint (polling connection state through BUILDING/READY/CLIENT_ACTION_REQUIRED), but "skip to **Step 2**" references a step that is never labeled, and destructive/batch operations (Create Batch, Stop Batch, Purchase Phone Number) have no verification guidance, which caps this dimension at 3 per the rubric.

3 / 5

Progressive Disclosure

A single, well-sectioned file with clear headers (Install, Authentication, Connecting, Searching, Running, Proxy, Best practices) and no nested references; the 18-row action catalog and CLI reference could arguably live in a separate reference file, which keeps it at the 'good structure, minor organization gaps' anchor.

4 / 5

Total

15

/

20

Passed

Description

41%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 identifies the target app but describes it in almost entirely generic terms. Both a what and a when are present, yet neither conveys what Bland AI actually does (AI phone calls, pathways, batches, voices), limiting both trigger quality and specificity.

Suggestions

Replace the generic actions with concrete Bland AI operations, e.g. "Send AI phone calls, create conversational pathways, manage batches, voices, and web agents".

Expand the trigger clause with natural user phrases such as "AI phone call", "call batch", "pathway", or "voice agent" instead of the circular "interact with Bland AI data".

Mention the specific artifacts involved (calls, pathways, phone numbers) to sharpen distinctiveness against generic data/automation skills.

DimensionReasoningScore

Specificity

Names the domain ("Bland AI integration") but the actions are purely generic ("Manage data, records, and automate workflows") with no concrete operations like calls, pathways, batches, or voices, matching the 'actions are minimal or generic' anchor rather than the 1-2-concrete-actions anchor.

2 / 5

Completeness

Both a 'what' and a 'Use when...' clause are present, but the 'what' is vague ("Manage data, records, and automate workflows") and the 'when' is circular ("interact with Bland AI data"), falling below the anchor-4 bar of a solid what with only the when needing more specificity.

3 / 5

Trigger Term Quality

The only real keyword is the app name "Bland AI" plus generic words like "data" and "workflows"; natural phrases a Bland AI user would say ("AI phone call", "pathway", "batch", "voice agent") are missing, fitting the 'one or two generic keywords; missing the natural phrases users say' anchor.

2 / 5

Distinctiveness Conflict Risk

"Bland AI integration" names a specific app, giving it a mostly distinct niche with only minor overlap risk against generic data-management or automation skills; not a 5 because the generic action wording blurs the boundary.

4 / 5

Total

11

/

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.

Validation — 15 / 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

Path

skills/bland-ai/SKILL.md

Reviewed

Table of Contents

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