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Personalize

personalize

Personalize — Choose which content to show a specific user and how to present it. Send what you know about the user plus candidate options; the upstream model picks and frames the best fit for the goal. Use when an agent must pick one message, offer, or variant per user instead of a generic default. Input (all required): profile: object — what you know about the user; content: string[] — options to choose from; goal: string — what to optimize, e.g. 'maximize trial signup'. Proxied to api.meshtool.ai. (2 MESH/call, a tool · personalization)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputYesPayload for personalize

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark readOnlyHint=false and openWorldHint=true, and the description adds valuable context: it reveals the tool is 'Proxied to api.meshtool.ai' and mentions a cost of '2 MESH/call'. It also explains the upstream model's role in picking and framing content, which goes beyond the annotation hints.

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 well-structured with a summary sentence, usage guidance, and inline parameter explanations. It includes necessary details like proxying and cost without excessive fluff. Slightly dense but each sentence serves a purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (nested input object, no output schema), the description covers purpose, usage, all required parameters with examples, and external behavior (proxying, cost). It does not specify the return format, but that is somewhat implied by 'picks and frames the best fit,' and the lack of an output schema reduces the need for detail.

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

Parameters4/5

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

Schema coverage is 100%, so the baseline is 3. The description adds meaningful examples: profile as {segment: pro, locale: en-US} and goal as 'maximize trial signup', which clarify expected formats beyond the schema's generic descriptions. This adds practical value for the agent.

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 clearly states a specific verb and resource: 'Choose which content to show a specific user and how to present it.' It distinguishes the tool's role from generic alternatives by focusing on per-user personalization, which aligns with the tool's title and avoids ambiguity.

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?

The description explicitly states when to use it: 'Use when an agent must pick one message, offer, or variant per user instead of a generic default.' It does not provide when-not-to-use or name alternatives, but the context is clear and sufficient given no direct sibling tool overlaps.

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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TDQS

B3.4/5.0
Disambiguation2/5

Several tools have overlapping purposes: search and mesh_discover both enumerate the catalog, while biz-analyze, task-analysis, and task-orchestrate all produce structured plans from a described situation. This will cause agents to misselect between them despite otherwise distinct tools.

Naming Consistency2/5

Naming is inconsistent: mesh_* tools use snake_case, most capability tools use hyphenated lowercase names, and a few (fetch, search) are bare verbs. There is no single verb-object or noun-verb pattern that holds across the set.

Tool Count3/5

28 tools is on the heavy side, but the marketplace concept justifies including many callable capabilities. However, the mix of platform tools and unrelated utilities makes the surface feel cluttered and hard to navigate.

Completeness4/5

The core marketplace lifecycle is well covered: signup, discover, fetch, publish, delegate, refer, follow, subscribe, and balance. Minor gaps exist (no unpublish or edit for listings), but most agent workflows can proceed without dead ends.