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Lookup

lookup
Read-only

Get everything you need about a service before using it. Default: tips (auth setup, pitfalls, workarounds). Add detail: true for full connection guide, insights: true for usage data. Pass goal: 'workflow description' to find multi-service recipes. This is step 2 of the standard KanseiLink flow: search_services → lookup → (execute) → report.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
goalNoWorkflow goal — triggers recipe mode (e.g., 'onboard employee')
modeNoExplicit mode override
detailNoGet full connection guide (auth, endpoints, rate limits)
periodNoTime period — triggers history mode
serviceNoFuzzy service name — triggers combinations mode
insightsNoGet aggregated usage data (success rate, trends, errors)
servicesNoYour available service IDs — for recipe coverage calculation
service_idNoService ID (from search_services)
compare_withNoCompetitor service_id for comparison — triggers history mode
feedback_typeNo[feedback] Filter by feedback type
feedback_limitNo[feedback] Max results (default 20)
feedback_statusNo[feedback] Filter by status. Triggers feedback mode when present.
voice_agent_typeNo[voices] Filter by agent type (claude, gpt, gemini)
voice_question_filterNo[voices] Filter by question_id

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the description need not repeat safety info. It adds valuable behavioral context: default mode is tips, detail:true triggers full connection guide, insights:true returns usage data, goal triggers recipe mode. This goes beyond the annotations and schema.

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 three sentences, front-loaded with the core purpose, then mode options, then flow. Every sentence earns its place with no fluff. It is concise, well-structured, and easy to scan.

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?

The description covers the main modes and the overall flow, which is sufficient for typical usage. It doesn't detail all special modes (feedback, voices, combinations, history), but the schema provides those details. Without an output schema, it doesn't explain return values, but for a lookup tool the return is implied. It's complete enough given the schema and annotations.

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 baseline is 3. The description adds some context by referencing key parameters (detail, insights, goal) and their effects, but most parameter semantics are already fully documented in the schema. It doesn't compensate significantly for the 14 parameters, but it doesn't need to given the schema richness.

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 the tool's purpose: 'Get everything you need about a service before using it.' It distinguishes from sibling search_services by positioning as step 2 of the flow and listing distinct capabilities (tips, detail, insights, recipes). This is a specific verb+resource with clear scope.

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 provides an explicit usage context: 'This is step 2 of the standard KanseiLink flow: search_services → lookup → (execute) → report.' This tells the agent when to use it relative to other tools. However, it does not explicitly state when not to use it or name alternative tools, so it's only a 4 rather than 5.

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

A4/5.0
Disambiguation5/5

Each tool targets a distinct step in the workflow: search_services for finding services, lookup for getting detailed information, and report for recording outcomes. There is no overlap in purpose, making it easy for an agent to select the correct tool.

Naming Consistency3/5

The naming uses lowercase with underscores, but the pattern is inconsistent: 'search_services' follows a verb_noun pattern, while 'lookup' and 'report' are single words. This mix of patterns could be confusing for an agent expecting a uniform convention.

Tool Count4/5

With 3 tools, the server is at the lower end of the typical 3–15 range, but each tool earns its place by covering the essential steps of the described workflow (search, lookup, report). The count feels slightly minimal but still appropriate for the focused scope.

Completeness3/5

The server covers the search, lookup, and report steps well, but it lacks tools for executing the actual service integration, retrieving stored reports, or updating/deleting records. This leaves notable gaps in the lifecycle, especially for a server that guides API integrations.