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invok-it

invokit-mcp

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by invok-it

search_apps

Search invok.it apps (deterministic step pipelines) by query, category, pricing type, or tags to find an AI tool that fits your workflow.

Instructions

Search for apps (deterministic step pipelines) on invok.it.

Args: query: Natural language search query (e.g. "document processing", "image analysis pipeline", "ETL workflow"). category: Filter by category slug. pricing_type: Filter by "free" or "paid". tags: Comma-separated tags to filter by. page: Page number. per_page: Results per page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo
tagsNo
queryNo
categoryNo
per_pageNo
pricing_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must carry the full behavioral burden. 'Search' implies a read-only operation and the pagination parameters imply paged results, but the description does not disclose result semantics, required authentication, or ordering. It adds useful context by defining apps as deterministic step pipelines, but not much else.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the purpose and followed by a tight, complete args list. Every line adds information and there is no filler, making it easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple optional-parameter search with an output schema, the parameter documentation is adequate. However, the description does not address how this search differs from search_tools/search_skills or any behavioral caveats, leaving an agent short of full context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the param descriptions compensate well: query has natural-language examples, category is identified as a slug, pricing_type is constrained to free/paid, and tags are stated as comma-separated. Page/per_page are only minimally elaborated, which keeps this from being a 5.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource: 'Search for apps (deterministic step pipelines) on invok.it.' This clearly identifies what the tool does and the domain of its resource, which helps distinguish it from sibling search_tools and search_skills, though it does not explicitly call out those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance about when to use this tool versus search_tools, search_skills, or get_app. The only signal is the word 'apps' in the description, so an agent must infer the selection criteria rather than being told.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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