ckg-agentforce
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_conceptsA | List all 40 AgentForce concepts in this knowledge graph. |
| search_conceptsA | Find AgentForce concepts by keyword. Args: query: Search term — e.g. 'resolution', 'trust', 'grounding', 'action', 'NIM'. |
| query_ckgA | 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). |
| get_prerequisitesA | Return the full ordered prerequisite chain for an AgentForce concept. Shows everything the concept depends on — the complete upstream path. Args: concept: Target concept — e.g. 'Autonomous Resolution', 'Multi-LoRA Serving', 'Custom Actions', 'Semantic Retrieval'. |
| resolution_pathA | Trace the exact path that determines an AgentForce autonomous resolution event. This is the $2/resolution billing path — what the agent must traverse correctly to resolve autonomously without human handoff. |
| route_queryA | Route an AgentForce question to the optimal model and reasoning approach via graph depth. The CKG graph IS the router. AgentForce dependency chains (e.g. Einstein Trust Layer → Data Cloud → NVIDIA NIM → Resolution Criteria) have typed hops that signal reasoning complexity deterministically. No heuristic: the graph decides. Routing table: hop_depth 1 → haiku · direct (simple concept lookup) hop_depth 2 → sonnet · generic_cot (moderate chain) hop_depth 3+ → opus · sparql_cot (deep dependency, structured reasoning) Args: question: Concept name or natural language question about Salesforce AgentForce. Returns: model_tier + reasoning_approach + why + context subgraph to inject before LLM call. |
| verify_sourceA | Return the source URL and content hash for an AgentForce concept node. Audit chain: edge answer → graph commit → source_hash → source_url (fetch hint) Verification: curl -s | sha256sum # compare output to source_hash Args: concept: Concept label (partial match supported). receipt: If True, also return a signed BoundaryAttest receipt envelope (experimental-interop-v0.1) binding concept_label + source_url + source_hash + timestamp to this server's ed25519 session key. |
| export_benchmark_receiptA | Generate a signed BoundaryAttest receipt for the agentforce CKG benchmark result. Produces a Result: F1 0.471 over 30 queries · ckg-benchmark v0.6.2 · 4× over RAG baseline (0.123). |
| evaluate_trust_chainA | Return a machine-readable JSON trust chain + ROI analysis + payment recommendation. Designed for autonomous agent consumption. The agent reads the JSON, evaluates the ROI gate, selects the cheapest positive-ROI payment option, and purchases autonomously if budget is pre-authorized. Trust chain closes the audit gap that RAG cannot: source_hashes → SHA-256 of source docs (what was known at extraction time) graph_hash → SHA-256 of the installed graph file (what is declared now) signer_key_id → Ed25519 public key fingerprint (who is attesting) benchmark_receipt → BoundaryAttest-signed F1 claim (cryptographic performance proof) scitt_status → SCITT ledger submission status (public audit anchor) ROI gate: if total_value_per_call_usd > payment_option.price_per_call_usd → autonomous_pay = true. Returns: JSON string (schema: ckg-trust-chain-v1). |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| show_burn | Show the AgentForce token burn before/after — RAG vs CKG traversal |
| map_agentforce_stack | Map the full AgentForce platform — agent to billing path |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| get_nodes_resource | All 40 AgentForce concepts — full node list with taxonomy. |
| get_resolution_chain_resource | The $2/autonomous-resolution billing chain — declared traversal path. |
TDQS
Scored across 9 tools
Most tools have distinct purposes, but 'get_prerequisites' overlaps with the prerequisite functionality of 'query_ckg', which could cause confusion. Overall, boundaries are mostly clear.
Most tools follow a verb_noun pattern, but 'resolution_path' is a noun_noun, breaking the consistency. Otherwise, naming is predictable.
With 9 tools, the set is well-scoped for a knowledge graph server, covering query, exploration, and trust verification without being excessive or thin.
The tool set covers core exploration, verification, and trust operations. However, a dedicated tool to retrieve full concept details is missing, creating a minor gap.