Agent Router

get_skill

Fetch a ClawHub skill by slug — metadata plus optional SKILL.md body.

Use the slug from search_skills results (e.g. 'agent-browser-clawdbot').
The response includes version, stats, install command, and the SKILL.md content
agents can follow to adopt the skill's behavior.

Free to use — no API key required.

Args:
    slug: ClawHub skill slug (lowercase, from search_skills).
    include_content: If true (default), include SKILL.md text. Set false for metadata only.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`slug`	Yes
`include_content`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedJun 16, 2026

TDQS

A4.4/5.0

Behavior4/5

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

With no annotations, the description carries full burden for behavioral traits. It discloses that the tool returns metadata and optional SKILL.md body, mentions response includes version, stats, install command, and SKILL.md content, and states free usage. It implies read-only operation by 'Fetch', but does not explicitly confirm idempotency or no side effects.

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 concise with no wasted words. It front-loads the purpose, then provides usage context, response summary, and parameter details. Every sentence adds value.

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

Completeness4/5

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

Given the existence of an output schema, the description adequately covers what the tool does, how to use it, and parameter behavior. It could mention error handling (e.g., if slug not found), but overall it is sufficiently complete for a simple fetch tool.

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 description compensates by explaining each parameter: slug is 'ClawHub skill slug (lowercase, from search_skills)' and include_content with default true and effect. This adds valuable meaning beyond the schema definitions.

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 'Fetch a ClawHub skill by slug', specifying the action (fetch) and resource (skill). It differentiates from sibling tools by referencing search_skills for obtaining the slug, making the purpose distinct.

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 provides explicit usage guidance: 'Use the slug from search_skills results' and notes 'Free to use — no API key required.' This helps the agent select the tool correctly. It lacks explicit 'when not to use' but is otherwise clear.

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

C2.7/5.0

Disambiguation3/5

Several tools overlap in purpose, particularly the research/analysis agents (constructivecritic, firstprinciplesanalyst, scientificresearchagent, researchagent) and the three reasoningdelegation agents, which differ only by effort level. Some tools like 'exploitagent' and 'testagent' have vague descriptions that don't clarify distinct roles. However, many tools are clearly distinct (e.g., campbuddy vs. smart_fridge___nutrition), and the core router tools (discover_agents, a2a_call_agent, wait_for_task) are well-defined.

Naming Consistency2/5

Naming is inconsistent: some tools use snake_case (a2a_call_agent, discover_agents, wait_for_task) while most others are camelCase or concatenated lowercase (browsernavigationagent, campbuddy, reasoningdelegationhigh). There's also odd naming like 'smart_fridge___nutrition' with triple underscore, and simple names like 'testagent' and 'exploitagent'. No consistent convention exists across the set.

Tool Count4/5

With 24 tools, this is near the upper limit but still reasonable for an agent router that hosts many pre-defined specialized agents. The core router functions (discover, call, wait) are supplemented by a diverse set of agent tools. It's borderline heavy but each tool represents a distinct agent or action, so it's acceptable.

Completeness4/5

The router functionality is well-covered: discovery (discover_agents), synchronous calling (a2a_call_agent), asynchronous handling (wait_for_task), and skill lookup (search_skills/get_skill) for extension. Missing are explicit cancellation or task management tools, but core workflows are supported. The presence of domain-specific agents (campbuddy, silpo_home_restaurant) doesn't detract from router completeness.

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