Name: pinecone
Rating: 56.8 (1 reviews)
Author: membranedev

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pinecone

Pinecone integration. Manage Indexs. Use when the user wants to interact with Pinecone data.

Quality

65%

Does it follow best practices?

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Securityby

Passed

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

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 highly actionable with copy-paste Membrane CLI commands and a solid connection-state workflow, but it spends tokens explaining Pinecone basics Claude already knows and lacks validation checkpoints for destructive index/vector operations. Structure is clean and single-file but could offload the proxy/clientAction detail to a reference.

Suggestions

Cut the opening paragraph defining what Pinecone is and remove filler lines like 'This is the fastest way to get a connection.' — Claude already knows the domain.

Add an explicit validation/confirmation step before running destructive actions (e.g. deleting indexes or purging vectors), such as confirming the target index name and dry-running reads first.

Fix the dangling 'Step 2' references by either labeling the step sections or rewording to 'skip to Searching for actions'.

Dimension	Reasoning	Score
Conciseness	The body opens by explaining what Pinecone is ('Pinecone is a vector database that makes it easy to build high-performance vector search applications...') — a concept Claude already knows — plus filler like 'This is the fastest way to get a connection' and 'When to use which actions: Use action names and parameters as needed.', matching the score-3 anchor of mostly efficient with some unnecessary explanation; not 2 because the bulk is lean executable commands.	3 / 5
Actionability	It provides copy-paste-ready commands throughout — 'npm install -g @membranehq/cli@latest', 'membrane connection ensure "https://www.pinecone.io/" --json', 'membrane action run <actionId> --connectionId=CONNECTION_ID --json', plus a flag table — covering install, auth, connection, action discovery, execution, and proxy, matching the score-5 anchor of fully executable copy-paste-ready commands covering common cases.	5 / 5
Workflow Clarity	The connection flow has a sequence (ensure → poll --wait → branch on READY/CLIENT_ACTION_REQUIRED/ERROR → retry), but it references a 'Step 2' that is never labeled, and Pinecone index/vector operations are destructive/batch yet no validation or verification steps precede running actions — the destructive-ops-without-validation cap holds it at 3 rather than 4.	3 / 5
Progressive Disclosure	Content is organized into clear sections (Overview, Working with Pinecone, Install, Auth, Connecting, Searching, Popular actions, Proxy, Best practices) in a single well-structured file with no nested references, matching the score-4 anchor of good structure with minor organization gaps; not 5 because the proxy options table and detailed clientAction handling are somewhat long to inline and could live in a reference file.	4 / 5
	Total	15 / 20 Passed

Description

61%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 names a distinct niche (Pinecone) with an explicit 'Use when' trigger, but its capability statement is thin and generic ('Manage Indexs') and it omits natural synonyms like 'vector database' or 'embeddings'. It is serviceable but could be sharpened with more concrete actions and broader trigger terms.

Suggestions

Replace the generic 'Manage Indexs' with 2-3 concrete actions, e.g. 'Create and manage Pinecone indexes, upsert and query vector embeddings'.

Broaden trigger terms to include natural phrasings users say: 'Use when the user wants to work with a vector database, search embeddings, or manage Pinecone indexes/vectors'.

Fix the 'Indexs' typo and keep the description in third person with concrete verbs.

Dimension	Reasoning	Score
Specificity	Quotes 'Manage Indexs' and 'interact with Pinecone data' — the domain is named but the only action ('Manage Indexs') is generic and minimal with a typo, matching the score-2 anchor of named domain with minimal/generic actions rather than the 1-2 concrete actions of score 3.	2 / 5
Completeness	It states a 'what' ('Pinecone integration. Manage Indexs.') and an explicit 'when' ('Use when the user wants to interact with Pinecone data'), so both are present, but the 'when' could be more specific — matching the score-4 anchor; it is not capped at 3 because a 'Use when...' clause is explicitly present, and not 5 because the triggers lack concrete specificity.	4 / 5
Trigger Term Quality	The trigger 'Use when the user wants to interact with Pinecone data' supplies the relevant keyword 'Pinecone' but misses common natural variations like 'vector database', 'embeddings', 'vector search', or 'query vectors', fitting the score-3 anchor of some relevant keywords but missing variations.	3 / 5
Distinctiveness Conflict Risk	Naming the specific product 'Pinecone' gives a clear niche with a distinct trigger word and minimal conflict risk with other skills, matching the score-5 anchor of a clear niche with distinct triggers.	5 / 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/pinecone/SKILL.md
Commit: f484c82

Reviewed: 5 days ago

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