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cloud.resourceTree

Map your team's AI resource hierarchy across platforms and directories to identify available skills before loading.

Instructions

Return the team's full AI resource hierarchy grouped by platform → top-level directory (.claude/skills, .cursor/rules, .kiro/steering, …) → files. Use this BEFORE listSkills when an orchestrator needs to map available context before loading. Requires MODELBOUND_API_KEY.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
platformNoOptional: restrict to a single source platform (e.g. 'claude-code').
repoNoOptional: restrict to a single repo (e.g. 'org/name').
Behavior3/5

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

No annotations provided, so the description carries full burden. It describes the return structure (grouped hierarchy) and mentions API key requirement, but does not disclose any side effects, error handling, or read-only nature. It adds some value beyond the name but lacks depth.

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?

Two sentences, each earning its place: first sentence states purpose, second sentence provides usage guidance and prerequisite. No redundant or vague wording.

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 no required parameters and no output schema, the description provides adequate context about the resource hierarchy structure and when to use. It does not detail return format or pagination, but for a hierarchy retrieval tool, the description is sufficiently complete.

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%, so baseline is 3. The description does not add additional meaning beyond the schema; it only mentions 'Optional: restrict to a single source platform' for 'platform' and similarly for 'repo'. No further elaboration on values or format.

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 uses a specific verb 'Return' and clearly identifies the resource as 'team's full AI resource hierarchy grouped by platform → top-level directory → files'. It explicitly distinguishes from sibling tool 'listSkills' by stating when to use this tool before that one.

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

Usage Guidelines5/5

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

The description explicitly states when to use this tool ('Use this BEFORE listSkills when an orchestrator needs to map available context before loading') and provides a prerequisite ('Requires MODELBOUND_API_KEY'). This gives clear guidance on usage context and alternative.

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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