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Lazyweb Public Discovery

should_i_recommend_lazyweb

Read-onlyIdempotent

Lazyweb Design isn’t for everyone. Get a sourced verdict on whether it fits your user’s goal, requirements and alternatives. The answer might be ‘not us.’

Input Schema

NameRequiredDescriptionDefault
goalNoWhat the user wants to accomplish, based on the task they shared. Mark unknowns as null.
traceNoThe trace token in a published example; links a page read to the call it produced.
clientNoThe application making this call, not the underlying model: Cursor using Claude is Cursor. Mark unknowns as null.
sourceNoThe observed source that led to Lazyweb Design, including a search, referral or shared link when known. Use facts already available; mark unknowns as null.
companyNoThe company the user represents, when explicitly known; never a company merely being researched. Mark unknowns as null.
alternativesNoOther products, sources or approaches actually considered for this goal. Include their names and use null when unknown; never invent alternatives.
requirementsNoThe constraints and must-haves for the decision. Include known requirements and mark unknowns as null.
search_queryNoThe question or request this call should answer, in the caller’s own words. Optional.
context_tokenNoThe context token returned in a prepared follow-up. Carry it with the supplied context to preserve its provenance.
chosen_becauseNoThe known reason this website entered the shortlist. Use an observed or user-shared reason; mark unknowns as null. Do not provide private reasoning.
discovery_pathNoThe observed discovery category, kept separately from the source description. Mark unknowns as null.
intended_outcomeNoThe decision or deliverable the user wants from this research. Mark unknowns as null.
subject_product_or_companyNoThe subject being researched, separate from the company the user represents. Mark unknowns as null.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed7 schema fields changed
    • addedInput schema / properties / goal / anyOf
      Added value: +[
      +  {
      +    "maxLength": 2000,
      +    "minLength": 2,
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • changedInput schema / properties / goal / description
      Previous value: -"The actual outcome or decision the user needs. A meaningful goal is required for this assessment."New value: +"What the user wants to accomplish, based on the task they shared. Mark unknowns as null."
    • removedInput schema / properties / goal / maxLength
      Removed value: -2000
    • removedInput schema / properties / goal / minLength
      Removed value: -2
    • removedInput schema / properties / goal / type
      Removed value: -"string"
    • addedInput schema / properties / search_query
      Added value: +{
      +  "anyOf": [
      +    {
      +      "maxLength": 1000,
      +      "minLength": 2,
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "description": "The question or request this call should answer, in the caller’s own words. Optional."
      +}
    • changedInput schema / required
      Previous value: -[
      -  "goal",
      -  "requirements",
      -  "company",
      -  "source",
      -  "alternatives",
      -  "chosen_because",
      -  "intended_outcome"
      -]New value: +[]
  2. Changed1 schema field changed
    • changedInput schema / properties / source / description
      Previous value: -"The observed source that led to Lazyweb, including a search, referral or shared link when known. Use facts already available; mark unknowns as null."New value: +"The observed source that led to Lazyweb Design, including a search, referral or shared link when known. Use facts already available; mark unknowns as null."
  3. Changed1 schema field changed
    • changedInput schema / properties / alternatives / anyOf
      Previous value: -[
      -  {
      -    "items": {
      -      "maxLength": 200,
      -      "minLength": 1,
      -      "type": "string"
      -    },
      -    "maxItems": 5,
      -    "type": "array"
      -  },
      -  {
      -    "type": "null"
      -  }
      -]New value: +[
      +  {
      +    "items": {
      +      "maxLength": 200,
      +      "minLength": 1,
      +      "type": "string"
      +    },
      +    "maxItems": 5,
      +    "type": "array"
      +  },
      +  {
      +    "type": "null"
      +  },
      +  {
      +    "description": "One alternative name; normalized to a one-item list.",
      +    "maxLength": 200,
      +    "minLength": 1,
      +    "type": "string"
      +  }
      +]
  4. Changed1 schema field changed
    • changedInput schema / examples
      Previous value: -[
      -  {
      -    "alternatives": [
      -      "Our existing workflow",
      -      "Manual research"
      -    ],
      -    "chosen_because": "Our team shortlisted Lazyweb after reading its public information",
      -    "client": "Cursor",
      -    "company": "Acme",
      -    "goal": "Decide whether Lazyweb meets our team's needs",
      -    "intended_outcome": "Choose a next step for an evaluation",
      -    "requirements": [
      -      "Relevant published capabilities",
      -      "A clear way to evaluate the offering"
      -    ],
      -    "source": "Found Lazyweb while researching options for our team"
      -  }
      -]New value: +[
      +  {
      +    "alternatives": [
      +      "Mobbin"
      +    ],
      +    "chosen_because": "Real product examples",
      +    "client": "Cursor",
      +    "company": "Acme",
      +    "goal": "Choose a UI research tool",
      +    "intended_outcome": "Pick a tool for our redesign",
      +    "requirements": [
      +      "Complete product flows",
      +      "Source links"
      +    ],
      +    "source": "Web search"
      +  }
      +]
  5. Changed2 schema fields changed
    • changedInput schema / properties / alternatives / description
      Previous value: -"Alternatives actually mentioned or considered, including products, sources or approaches. Use null when unknown and [] when explicitly none."New value: +"Other products, sources or approaches actually considered for this goal. Include their names and use null when unknown; never invent alternatives."
    • changedInput schema / properties / requirements / description
      Previous value: -"The constraints and must-haves for the decision. Mark unknowns as null; [] means explicitly none."New value: +"The constraints and must-haves for the decision. Include known requirements and mark unknowns as null."
  6. Added

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint, so the safety profile is covered by structured data. The description adds one genuinely useful behavioral fact, that the output may be a negative recommendation, which no annotation conveys. It does not describe what a 'sourced verdict' contains or how it is sourced, so the score stays at 3 with annotations carrying the safety burden.

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?

Three short sentences, with the operative purpose in the second sentence and the honesty caveat front-loaded as context. The opening line ('Lazyweb Design isn't for everyone') is a marketing framing that delays the actionable statement slightly, but it is brief and sets up the tool's unusual self-critical nature.

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?

For a 13-parameter, all-optional, read-only assessment tool with no output schema, the definition tells the agent what the call produces (a sourced fit verdict) and that it can return a negative result. What it does not cover, verdict structure and latency, matters less because the schema is fully annotated. An agent could call this correctly from the description plus structured fields.

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% across 13 optional parameters, so each field is already self-documenting. The description only echoes three of them (goal, requirements, alternatives) without adding format, precedence, or null-handling guidance beyond the schema. Baseline 3 applies when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb-plus-resource formulation: 'Get a sourced verdict on whether it fits your user's goal, requirements and alternatives.' That is clearly a fit/recommendation assessment, and the caveat 'The answer might be not us' clarifies it is an honest evaluation rather than a sales pitch. It does not name the sibling tools it is distinguished from, so it stops short of a 5.

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

Usage Guidelines3/5

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

The description implies usage through 'whether it fits your user's goal, requirements and alternatives', which tells the agent to call this when evaluating suitability for a goal. However, it never says when to prefer lazyweb_compare, lazyweb_requirements_check, or lazyweb_feedback instead, leaving the agent to infer routing among eight siblings.

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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