artefact-mcp-server

Pipeline Health Score

score_pipeline_health

Read-onlyIdempotent

Assess pipeline health by calculating a 0-100 score based on velocity, conversion rates, and funnel signals. Detect bottlenecks, stalled deals, and test deals against exit criteria to prioritize actions.

Instructions

Analyze pipeline health with velocity metrics, signal detection, and exit criteria testing.

Calculates overall health score (0-100), identifies bottleneck stages, measures stage-to-stage conversion rates, flags stalled deals, detects pipeline signals, and optionally tests deals against exit criteria.

Args: pipeline_id: Optional HubSpot pipeline ID to filter. Default: all pipelines. source: "auto" (uses HubSpot if API key is set, otherwise sample data), "hubspot" for live data, "sample" for built-in demo data. exit_criteria: Optional JSON string with exit criteria to test against. List of objects: [{stage, test_name, required_field, is_blocking}].

Returns: JSON with health score, velocity, conversion rates, at-risk deals, signals, and optional exit criteria test results.

Input Schema

TableJSON Schema

Name	Required	Default
`pipeline_id`	No
`source`	No	auto
`exit_criteria`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedApr 30, 2026

addedInput schema / properties / exit_criteria

Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null
+}

changedInput schema / properties / source / default
```
Previous value: -"hubspot"New value: +"auto"
```

First observedv0.1.1Feb 11, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnlyHint and idempotentHint, so the description's addition of source options (auto, hubspot, sample) and optional exit criteria testing provides helpful behavioral context beyond annotations.

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?

Well-structured with a concise overview, a bullet list of capabilities, and an Args section. Every sentence adds value; the description is front-loaded and not bloated.

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?

Despite lack of output schema in provided context, the description explicitly lists return fields. All three optional parameters are well documented. Sufficient for an agent to understand and use the tool correctly.

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?

With 0% schema description coverage, the description compensates superbly by explaining each parameter: pipeline_id filtering, source with its three modes, and exit_criteria with its JSON structure and fields.

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?

Clearly states the tool analyzes pipeline health with velocity metrics, signal detection, and exit criteria testing, listing specific outputs. Differentiates from sibling tools like detect_signals or identify_constraint by focusing on overall health scoring.

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

Usage Guidelines4/5

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

Implies usage for holistic pipeline analysis with optional exit criteria testing, but does not explicitly state when to use versus alternatives or when not to use.

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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