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Andru

Andru

by geter-andru
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Remote

Build an asset

generate_asset

Build an asset from Andru's catalog using company knowledge, save it to the Andru library, and return a job ID to fetch as markdown.

Instructions

Building the material a step needs, often what the champion carries into rooms the person won't be in: use this when the person picked an asset from Andru's catalog (find it with list_assets), e.g. 'Board Presentation', 'Buying Committee Navigation'. Built from everything Andru knows about their company and saved to their Andru library. Takes up to a few minutes: returns a job_id; call get_asset with it to receive the asset as markdown.

Input Schema

NameRequiredDescriptionDefault
assetYesThe asset name from list_assets.
prospectCompanyNoFor a prospect asset (Pre-Call Intelligence Brief, Deal Reengagement Strategy, Personalized Cost of Inaction One-Pager): the company it is for.
prospectContactNoFor a prospect asset: the person it is for, name and title.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv1.4.8
    • addedInput schema / properties / prospectCompany
      Added value: +{
+  "description": "For a prospect asset (Pre-Call Intelligence Brief, Deal Reengagement Strategy, Personalized Cost of Inaction One-Pager): the company it is for.",
+  "type": "string"
+}
    • addedInput schema / properties / prospectContact
      Added value: +{
+  "description": "For a prospect asset: the person it is for, name and title.",
+  "type": "string"
+}
  2. Addedv1.4.1

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that the asset is built from Andru's company knowledge, saved to the user's library, takes up to a few minutes, and is asynchronous: it returns a job_id that must be passed to get_asset to receive markdown. This is strong behavioral context for a non-read-only, open-world generation tool.

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?

The description is front-loaded with the purpose, then usage context, then persistence and async behavior. Every sentence contributes actionable information, and the examples clarify acceptable asset inputs without padding.

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 generation tool with no output schema, the description explains the return value (a job_id), the retrieval path (get_asset), the output format (markdown), and the expected latency. Combined with full schema coverage and annotations, an agent has enough information to call and follow up correctly.

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%, so the schema already documents all three parameters. The description adds useful examples for the asset parameter and contextualizes prospect assets, but it does not materially expand the meaning of prospectCompany or prospectContact beyond the schema descriptions. The baseline 3 is appropriate.

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 generation action for an asset from Andru's catalog and distinguishes it from the prerequisite list_assets and follow-up get_asset. An agent can understand what the tool produces without opening the schema.

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?

It gives explicit triggering context: use this when the person picked an asset from Andru's catalog, and it names list_assets as the way to find that asset. It also explains the follow-up retrieval call. It does not state when not to use it or compare against the sibling generate_portfolio_brief, so it falls short of the full 5 criteria.

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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