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aidesignblueprint

AI Design Blueprint

Official
by aidesignblueprint
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Python
Remote

team.summarize

Read-onlyIdempotent

Summarize your team's Blueprint usage over a configurable window, revealing tool-call counts, top principles, value events, and readiness trends to guide what to explore next.

Instructions

Pro/Teams — summarises the caller's tool-usage patterns and value signals over a configurable window (default 30 days). Returns tool_call_counts, top principles cited in validate runs, value_event_counts by event_type, and an aggregate readiness trend. WHEN TO CALL: the user asks 'how is the Blueprint helping me/my team', 'what should I explore next', or 'show me my Blueprint usage'. WHEN NOT TO CALL: proactively or on every conversation turn (the summary is an explicit retrospective, not telemetry); to compare users (returns only the caller's own data). BEHAVIOR: read-only, idempotent over the same window. Aggregates from AIToolCallLog + ValueEvent + AIValidationRunLog. Pass private_session=true to bypass server-side logging for this summary call (the underlying historical data still exists; only this read is untracked). Auth: Bearer , Teams plan only; Pro and beta plans are refused. UK/EU residency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
days_backNoNumber of days of usage history to include in the summary.
private_sessionNoSet to true to skip logging this summary call.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.2.0
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "title": "summarize_team_usageDictOutput",
+  "type": "object"
+}
  2. Changed1 schema field changedv1.1.0
    • changedOutput schema / (root)
      Previous value: -{
-  "additionalProperties": true,
-  "title": "summarize_team_usageDictOutput",
-  "type": "object"
-}New value: +null
  3. First observedv1.0.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly, idempotent, and non-destructive. The description adds depth: it names the data sources (AIToolCallLog, ValueEvent, AIValidationRunLog), explains that private_session bypasses only the read logging while historical data persists, and notes plan/residency restrictions (Teams only, UK/EU). No contradiction with annotations.

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

Conciseness4/5

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

The description is longer than a one-liner but structured with clear headings (WHEN TO CALL, WHEN NOT TO CALL, BEHAVIOR) and front-loaded purpose. Every sentence earns its place; the verbosity is justified by the tool's complexity and the need to clarify plan restrictions and private_session semantics.

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 read-only aggregation tool with an output schema, the description covers the core question triggers, exclusions, data sources, authentication and plan requirements, and the private_session edge case. Nothing an agent needs to decide or execute a call 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 both parameters (days_back, private_session) are fully described in the schema with defaults and purpose. The description re-echoes the window default but adds no new meaning beyond what the schema already provides, so baseline 3 applies.

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 states a specific verb ('summarises') and resource (caller's tool-usage patterns and value signals) with configurable window and default. It clearly distinguishes this tool from all siblings by describing the unique aggregation and output fields, so an agent can tell it apart without opening schemas.

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

Usage Guidelines5/5

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

Explicit WHEN TO CALL and WHEN NOT TO CALL sections give concrete trigger phrases ('how is the Blueprint helping me/my team') and exclusions (proactive use, every turn, comparing users). This is model guidance for tool selection.

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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