Tenrung

Score how AI-native a team is

score_ai_native_team

Read-onlyIdempotent

Score a team or company on the 10-line AI-native scorecard and get a 90-day plan. Each line is scored 0 to 3 by the user: a named AI owner with hours for it, department reps meeting every 2 weeks, a pinned 1-page AI policy, monthly live training on their own workflows, training in 3 tracks, a recorded session library checked monthly, a use-case list ranked by hours saved, wins posted company-wide, weekly blocked AI time, and hours saved measured and shown to leadership. Ask the user for each of the 10 scores first (the input schema says what 0, 1, 2 and 3 mean on each line); never guess one. Returns the total out of 30, the band (You bought seats, A start no engine, Almost there, AI native), the 3 first moves, a 90-day plan in 3 months with each step marked start, tighten or keep, the AI champion role card, and a share_url to a public result page. Nothing is stored; the link holds only the 10 numbers and the optional team name.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "scores": "<scores>"
    },
    "name": "score_ai_native_team"
  }
}

Input Schema

Name	Required	Description	Default
`scores`	Yes	The team's 0 to 3 score on each of the 10 lines. Ask the user for each line; never guess a score they did not give.
`team_name`	No	Optional team or company name shown on the result and in the share link. Leave it out to keep the link anonymous.

Output Schema

Name	Required	Description
`max`	Yes
`band`	Yes
`code`	Yes	The 10 scores as digits in line order.
`plan`	Yes
`lines`	Yes
`total`	Yes
`method`	Yes
`next_band`	Yes
`role_card`	Yes
`share_url`	Yes	A public page with this result. It holds only the 10 numbers and the team name.
`team_name`	Yes
`first_moves`	Yes
`scorecard_version`	Yes
`points_to_next_band`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 16, 2026

TDQS

A4.1/5.0

Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, and the description usefully adds statelessness and privacy context: 'Nothing is stored; the link holds only the 10 numbers and the optional team name.' That is genuine behavioral disclosure beyond the annotations, though it says little about validation or failure behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The purpose and constraints are front-loaded, but the middle sentence enumerates all ten scorecard lines in prose, duplicating content already fully present in the 100%-covered schema. That enumeration is largely redundant length rather than earning its place.

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?

For a scoring tool with a full output schema, the description covers the required input flow, the no-guess rule, statelessness, the share link's contents, and even the returned artifacts. Nothing an agent needs to call it correctly is missing.

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

Parameters3/5

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

Schema description coverage is 100% and every 0-3 meaning is already spelled out per line, so the schema does the heavy lifting. The description names the 10 lines and the required input flow but mostly defers to the schema ('the input schema says what 0, 1, 2 and 3 mean'), which is the baseline-3 case.

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?

States a specific verb and resource ('Score a team or company on the 10-line AI-native scorecard') plus the concrete deliverable (a 90-day plan). An agent immediately knows this is an assessment/scoring tool, and the unrelated siblings (feedback tools) pose no confusion.

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?

Gives explicit invocation guidance: 'Ask the user for each of the 10 scores first ... never guess one,' which is a real workflow directive. It doesn't compare against alternatives, but the sibling tools are in a different domain so no routing exclusion is needed.

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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