{ "specVersion": "1.0", "host": { "displayName": "TensorPM — Project Agent Harness", "documentationUrl": "https://tensorpm.com/for-agents", "logoUrl": "https://tensorpm.com/TensorPM.svg" }, "entries": [ { "identifier": "urn:air:tensorpm.com:manifest:agent-discovery", "displayName": "TensorPM Agent Discovery Manifest", "type": "application/json", "url": "https://tensorpm.com/.well-known/agent.json", "description": "Public TensorPM discovery manifest for the local project agent, MCP tools, A2A JSON-RPC interface, installation, commerce and documentation. TensorPM is an AI agent harness purpose-built for project management and anchored on a persistent, typed project graph. Distilled inputs and proposed changes to core project context require human confirmation; authorized typed MCP operations such as action-item and decision CRUD can apply directly and remain visible in project history. The manifest describes the localhost interfaces but is not itself an A2A Agent Card.", "tags": [ "project-management", "project-agent-harness", "agentic-project-management", "context-driven-project-management", "cdpm", "risk-analysis", "critical-path", "decision-management", "portfolio-steering", "local-first" ], "capabilities": [ "ProjectContextAnalysis", "RiskAndDependencyAnalysis", "BottleneckAndCriticalPathAnalysis", "OptionEvaluation", "NextStepGuidance", "DecisionTracking", "AgentSelfScheduling", "MilestoneCheckIn", "StatusReporting", "ContextDistillation" ], "representativeQueries": [ "which risks in my project are about to hit the critical path", "what is actually blocking the September milestone and who owns it", "record the decision we just made and supersede the old one, keeping the audit trail", "remind me next Tuesday to re-evaluate the budget risk with full project context", "give me a status report for the steering committee from confirmed project context" ], "version": "1.0.0", "updatedAt": "2026-08-18T00:00:00Z" }, { "identifier": "urn:air:tensorpm.com:descriptor:mcp-project-graph", "displayName": "TensorPM Project Graph MCP Descriptor", "type": "application/json", "url": "https://tensorpm.com/.well-known/mcp/server-card.json", "description": "Experimental detailed descriptor for TensorPM's local, stdio-based MCP server. It follows the current SEP-2127 discussion where useful but does not claim conformance to a published MCP Server Card schema. The server exposes governed read/write access to a typed project graph: goals, requirements, action items, work packages, milestones, risks, decisions and history. Core-context proposals require human confirmation; authorized typed CRUD tools can apply directly. TensorPM is bidirectional MCP, local-first and localhost-scoped.", "tags": [ "mcp", "mcp-server", "mcp-client", "bidirectional-mcp", "project-management", "agent-memory", "project-graph", "decision-log", "audit-trail", "human-in-the-loop", "local-first" ], "capabilities": [ "ProjectGraphRead", "ProjectGraphWrite", "ActionItemManagement", "WorkBreakdownStructure", "MilestoneManagement", "RiskRegister", "DecisionRecord", "DecisionSupersede", "DecisionLink", "ProjectHistoryQuery", "AgentDelegation", "ExternalMcpClient" ], "representativeQueries": [ "read the confirmed project context before you start working on this ticket", "create the action items for this work package and assign owners", "list every active decision that governs this milestone", "what changed in the project graph since my last run", "persist what we agreed in this session as structured project memory" ], "version": "1.0.0", "updatedAt": "2026-08-18T00:00:00Z" }, { "identifier": "urn:air:tensorpm.com:skill:tensorpm", "displayName": "TensorPM Agent Skill", "type": "text/markdown; profile=\"urn:air:agent-skills\"", "url": "https://tensorpm.com/SKILL.md", "description": "The agent-facing skill definition: when to reach for TensorPM, how to connect, and how to behave once connected. Install it into Claude Code, Codex, Cursor, OpenClaw or another MCP/A2A runtime so the agent reads confirmed project context, uses direct typed operations or human-reviewed proposals according to the documented boundary, and verifies the resulting state. Companion documents carry the full tool catalog (MCP-TOOLS.md), the JSON-RPC surface (A2A-API.md), the action-item schema (ACTION-ITEMS.md) and the pricing rules an agent needs before it spends anything (PRICING.md).", "tags": [ "agent-skill", "claude-code", "codex", "cursor", "openclaw", "mcp", "a2a", "project-management", "onboarding", "structured-memory" ], "capabilities": [ "SkillInstallation", "AgentOnboarding", "ToolCatalogReference", "UsagePolicyGuidance", "StructuredProjectMemory" ], "representativeQueries": [ "how do I give my coding agent long-term project memory", "install the TensorPM skill into Claude Code and verify the connection", "which TensorPM tool should I call to record a stakeholder commitment", "when should an agent use TensorPM instead of its own scratchpad" ], "version": "1.0.0", "updatedAt": "2026-08-18T00:00:00Z" }, { "identifier": "urn:air:tensorpm.com:tool:api", "displayName": "TensorPM API (commerce, credits, local A2A)", "type": "application/openapi+json", "url": "https://tensorpm.com/openapi.json", "description": "OpenAPI 3.1 description of the TensorPM commerce and credit endpoints plus the local A2A endpoint of the desktop app. An agent can read its own credit balance, understand what a call will cost before it makes it, and complete a purchase without a human ever touching a pricing page. Credits are billed on one published formula (input x 1, cached input x 0.2, output x 4) and only for calls routed through the TensorPM proxy — bring-your-own-key traffic bypasses it entirely and costs nothing.", "tags": [ "openapi", "rest-api", "agentic-commerce", "credits", "billing-transparency", "a2a", "byok" ], "capabilities": [ "CreditBalanceQuery", "PricingLookup", "SubscriptionInspection", "LocalA2AEndpoint" ], "representativeQueries": [ "how many TensorPM AI credits does this account have left", "what does this project agent call cost before I run it", "which TensorPM plan includes bring-your-own-key" ], "version": "1.0.0", "updatedAt": "2026-08-18T00:00:00Z" }, { "identifier": "urn:air:tensorpm.com:tool:acp-catalog", "displayName": "TensorPM Agentic Commerce Catalog (ACP)", "type": "application/json", "url": "https://api.tensorpm.com/acp/catalog", "description": "The machine-readable product catalog behind Agentic Commerce Protocol checkout: every plan, price and entitlement an agent needs to buy on a human's behalf, with no marketing page in the loop. Cloud Sync and unlimited free members are on every tier, Trial included. Trial is free with no time limit, 2,000,000 lifetime credits and several own cloud workspaces under a fair-use limit; Pro adds 10,000,000 hosted credits per month and unlimited own cloud workspaces; Business is the only tier with bring-your-own-key and is quoted individually. Sold as a discoverable catalog rather than a checkout funnel, because an agent that has to parse a pricing page is an agent that gets it wrong.", "tags": [ "acp", "agentic-commerce", "checkout", "product-catalog", "pricing", "subscriptions" ], "capabilities": ["ProductCatalog", "AgenticCheckout", "EntitlementLookup"], "representativeQueries": [ "buy a TensorPM Pro subscription on my behalf", "how many cloud workspaces can a TensorPM account own on each plan", "list TensorPM products and prices in machine-readable form" ], "version": "1.0.0", "updatedAt": "2026-08-18T00:00:00Z" } ] }