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install_stack

Return a curated skill stack (bundle) for bulk pre-installation. Each stack groups 5-15 skills for a common use case. Returns: stack name, description, skills with slugs, install commands. Available stacks: developer-starter, content-creator, data-analyst, crypto-trader, devops-engineer, ai-agent-developer, security-auditor, homework-helper, startup-founders, marketing-team

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoStack name. Available: developer-starter, content-creator, data-analyst, crypto-trader, devops-engineer, ai-agent-developer, security-auditor, homework-helper, startup-founders, marketing-team. Default: "developer-starter".

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It transparently states that the tool returns a stack and describes the return fields ('stack name, description, skills with slugs, install commands'). It stops short of explicitly stating that no installation occurs, but the verb 'Return' makes this apparent. The description provides useful behavioral context beyond the schema.

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 primary purpose, then provides brief elaboration and the list of available stacks. Every sentence earns its place, and there is no fluff or redundancy. The structure is exceptionally clear and easy to parse.

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

Completeness5/5

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

For a tool with one optional parameter, no output schema, and no annotations, the description is highly complete. It explains what the tool does, describes the return shape, lists all available stacks, and covers the key use case. The absence of output schema is mitigated by the explicit return fields. This is complete enough for an agent to invoke correctly.

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

Parameters3/5

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

Schema coverage is 100% for the single 'name' parameter, including the list of available stacks and the default value. The description redundantly lists the stacks and adds context that each stack groups 5-15 skills, but it does not add new parameter-level meaning beyond what the schema already provides. Baseline 3 applies.

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

Purpose5/5

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

The description clearly states the tool's function: 'Return a curated skill stack (bundle) for bulk pre-installation.' The verb 'Return' and resource 'skill stack' are specific, and listing available stacks adds scope. This distinguishes it from sibling tools like get_skill or search_skills by focusing on multi-skill bundles.

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

Usage Guidelines4/5

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

The description clearly conveys the use case: 'for bulk pre-installation' with each stack grouping 5-15 skills for a common use case. It does not explicitly mention when not to use it or name alternative tools, but the context is clear enough for an agent to select this when a predefined bundle is needed.

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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TDQS

A4.1/5.0
Disambiguation3/5

Several tools have overlapping purposes: evaluate_skill and scan_skill both assess skill safety, while generate_usecase, get_workflow, and score_skills all involve skill scoring and recommendation. Description differences exist but boundaries are not always crisp, potentially causing misselection. The unrelated get_deals tool also adds confusion.

Naming Consistency4/5

Tool names mostly follow a consistent verb_noun snake_case pattern (e.g., search_skills, get_skill, submit_request). Minor inconsistencies exist: popular_skills uses an adjective instead of a verb, and generate_usecase uses 'usecase' while search_use_cases uses 'use_cases'.

Tool Count4/5

With 14 tools, the server is on the higher end of the typical range but still well-scoped for its broad functionality (search, evaluation, workflows, community, content pipeline). Each tool serves a distinct functional area, though a few could be consolidated.

Completeness4/5

The core workflow of searching, retrieving, and evaluating skills is well covered, including use cases and community requests. However, there are minor gaps such as lack of a category browsing tool or direct single-skill installation, and the inclusion of unrelated AliExpress deals seems out of place.

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