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Sandypaluk

K4G Application Triage MCP Server

by Sandypaluk

Search K4G Applications

k4g_search_applications
Read-onlyIdempotent

Search startup applications by text, sector, stage, or impact score to locate candidates for review.

Instructions

Search the incubator application pipeline by text, sector, stage, or score.

This tool searches across all applications in the current cycle. It does NOT modify any data - use k4g_flag_for_review for that.

Args:

  • query (string, optional): matches against org name, founder name, one-liner

  • food_sector (string, optional): e.g. "alt-protein", "fermentation", "policy"

  • stage (enum, optional): pipeline stage to filter on

  • min_impact_score (number, optional): 1-10, minimum impact score

  • limit (number, optional): max results, default 20

Returns JSON with: { total, count, applications: [ { id, org_name, founder_name, country, food_sector, one_liner, stage, review_status, assigned_reviewer, impact_score, feasibility_score, team_score } ] }

Examples:

  • "Which alt-protein applications scored 7 or higher on impact?" -> food_sector="alt-protein", min_impact_score=7

  • "Find anything from Kenya" -> query="Kenya"

  • Don't use when: you already have the application ID (use k4g_get_application instead)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMaximum number of results to return (default 20).
queryNoFree-text match against org name, founder name, or one-liner. Omit to skip text filtering.
stageNoFilter by pipeline stage.
food_sectorNoFilter by sector, e.g. 'alt-protein', 'fermentation', 'policy', 'packaging', 'education'.
min_impact_scoreNoOnly return applications with impact_score >= this value.
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint false, so the safety profile is covered. The description adds useful behavioral context beyond annotations: it searches across all applications in the current cycle, returns a specific JSON shape, and reinforces that it does not modify data. This exceeds the baseline but is not a 5 because it omits details like result ordering or pagination behavior beyond the limit parameter.

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 well-structured with clear sections (overview, args, returns, examples, exclusions). It is front-loaded with the purpose, every sentence serves a function, and the content is comprehensive without being bloated. Despite being longer than typical tool descriptions, the structure makes it highly scannable and useful.

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?

Given the tool's moderate complexity (5 optional parameters, no output schema), the description is highly complete. It documents the full return payload shape, parameter semantics, example usage, and relationships to sibling tools. With rich annotations and a thorough description, the agent has everything it needs to invoke the tool correctly.

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 description coverage is 100%, so the baseline is 3. The description adds meaningful value via concrete examples ('Which alt-protein applications scored 7 or higher on impact?' -> food_sector='alt-protein', min_impact_score=7) and clarifies that query matches org name, founder name, or one-liner. This goes beyond simple schema repetition and earns a 4.

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 verb and resource: 'Search the incubator application pipeline by text, sector, stage, or score.' It also specifies scope ('all applications in the current cycle') and explicitly contrasts with k4g_get_application for when an application ID is already available, making sibling differentiation strong.

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?

Usage guidance is explicit and thorough. It names alternatives (k4g_flag_for_review for modifications, k4g_get_application when an ID is known), provides example natural-language queries with parameter mappings, and includes an explicit 'Don't use when' section.

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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