NVIDIA NemoClaw CKG

query_intersect

Answer a conjunctive query: concepts reachable from EVERY anchor at once (A AND B).

query_ckg walks outward from one concept. This intersects the reachable sets of two or more, which is the shape of most real questions — "the component that satisfies A AND applies to B". Neither anchor alone answers it; the answer lives in the overlap.

Every branch is an exact set of declared edges, so the intersection is exact. A concept appears only if a declared path reaches it from each anchor. A relation missing from the graph produces an empty result, never a guess.

Args: branches: Two or more branches. Either a bare anchor ("TensorRT-LLM"), which takes everything within depth hops, or an anchor plus an explicit relation path using '>' ("TensorRT-LLM > REQUIRES > ENABLES"), where each relation replaces the frontier. '*' matches any relation. Mix both forms freely. depth: Hops for bare-anchor branches, 1-5 (default 2). Ignored for explicit paths. direction: 'out' follows dependencies, 'in' follows them backwards, 'both' (default). mode: 'AND' (default) intersects branches; 'OR' unions them. limit: Max concepts listed, 1-200 (default 40). The true count is always shown.

Returns: Markdown with the query plan and its per-step set sizes, then the answer set with taxonomy tags. Reports which branch was empty when the intersection is empty.

Input Schema

TableJSON Schema

Name	Required	Default
`mode`	No	AND
`depth`	No
`limit`	No
`branches`	Yes
`direction`	No	both

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.

AddedAug 2, 2026

TDQS

A5/5.0

Behavior5/5

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

No annotations exist, so the description carries full burden. It discloses exact semantics: 'Every branch is an exact set of declared edges, so the intersection is exact,' and describes failure behavior: 'A relation missing from the graph produces an empty result, never a guess.' It also explains return format and empty-branch reporting.

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 structured into clear paragraphs for overview, behavioral guarantees, Args, and Returns. It is long but every sentence earns its place—no fluff, all high-value information. Front-loaded with the essential purpose and comparison.

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?

Given the tool's complexity (5 params, 0% schema coverage), the description is complete: it explains all parameters, edge cases, return format, and failure modes. It even details the returned Markdown structure and empty-result handling, so no gaps remain.

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

Parameters5/5

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

Schema coverage is 0%, but the description fully compensates with detailed 'Args' section covering every parameter: branch syntax (bare anchor vs '>' path), depth range/default/ignored cases, direction options, mode semantics, and limit behavior (max, default, true count always shown). This goes far beyond the bare schema.

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 opens with a specific verb+resource: 'Answer a conjunctive query: concepts reachable from EVERY anchor at once (A AND B).' It clearly distinguishes itself from sibling query_ckg by contrasting single-anchor walk vs. multi-anchor intersection, and explains the tool's role as 'the shape of most real questions'.

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?

Usage guidelines are explicit: 'query_ckg walks outward from one concept. This intersects the reachable sets of two or more...' and 'Neither anchor alone answers it; the answer lives in the overlap.' This tells the agent exactly when to choose this tool over the sibling.

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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