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Glama

Salesforce AgentForce CKG

by io.github.Yarmoluk

query_ckg

Traverse the AgentForce knowledge graph from any concept.

Returns prerequisites (what this concept needs) and dependents (what it enables). Every relationship traces to an authoritative Salesforce doc URL.

Args: concept: Concept name — e.g. 'Autonomous Resolution', 'Einstein Trust Layer', 'Service Agent', 'Grounding', 'NVIDIA NIM'. depth: Traversal depth 1–5 (default 3).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNo
conceptYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

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

  1. First observed

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. It discloses that the tool is read-only (no mention of side effects), returns prerequisites and dependents, and links to Salesforce docs. It could mention error handling or existence guarantees, but overall is transparent.

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 extremely concise (4 sentences plus args list) with no redundant information. Key points are front-loaded: traversal, return structure, and parameter details.

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 no annotations, an output schema is present (so return values are covered), and the tool has only 2 simple parameters. The description fully covers purpose, behavior, and parameter usage, making it complete.

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?

The schema has 0% description coverage, so the description fully supplements parameter meanings. It provides concrete examples for 'concept' and specifies valid range and default for 'depth' (1–5, default 3), which is not in the 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 clearly states the tool traverses the AgentForce knowledge graph and returns prerequisites and dependents. It uses a specific verb ('Traverse') and resource ('AgentForce knowledge graph'), and distinguishes from sibling tools like search_concepts or list_concepts by focusing on graph traversal.

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

Usage Guidelines3/5

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

The description implies usage for exploring relationships from a concept, but does not explicitly state when to use this tool versus alternatives (e.g., search_concepts, get_prerequisites). No when-not-to-use conditions are provided.

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

All Salesforce AgentForce CKG toolsInspect
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TDQS

A4.1/5.0
Disambiguation4/5

Most tools serve clearly distinct roles: querying, searching, routing, and verification are separate concerns. However, query_ckg and get_prerequisites both return prerequisite information, which could cause an agent to select the wrong tool when a simple prerequisite list is needed. The descriptions do clarify the difference (generic traversal vs. full ordered chain), but some ambiguity remains.

Naming Consistency4/5

The vast majority of tools follow a consistent snake_case verb_noun pattern, such as evaluate_trust_chain, list_concepts, and route_query. The only exception is resolution_path, which is a noun phrase rather than a verb_noun, making it slightly less predictable. This is a minor deviation from an otherwise strong pattern.

Tool Count5/5

With 10 tools, the server has a well-scoped surface area for a knowledge graph that requires discovery, traversal, routing, and audit capabilities. Each tool represents a distinct operation, and there are no redundant or unnecessary entries. This falls comfortably within the ideal range for a domain-specific server.

Completeness5/5

The toolset covers the full read-side lifecycle of the knowledge graph: discovery, traversal, path analysis, routing, and trust verification. It also includes specialized tools for benchmarking and source verification, which are unusual but valuable additions. No obvious critical gaps exist, such as missing search or traversal capabilities.

Resources