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cstillick

guardian-contributions-mcp

by cstillick

get_flags

Retrieve computed alerts for campaign finance issues such as large-loan self-dealing, sub-$1,000 continuing receipts, amended reports, and more. Identify potential violations in Oklahoma campaign finance data.

Instructions

Computed alerts: large-loan self-dealing (loan ≥ raised), sub-$1,000 continuing receipts, amended-report-used, multiple committees, no Pre-Primary, no committee found, identity mismatches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
districtNo
org_idNo
yearNo
Behavior2/5

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

No annotations are present, so the description carries full burden. It mentions 'computed alerts' but does not state if the tool is read-only, whether it requires specific authentication, or what side effects occur. The list of alert types gives some output context but no behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (one line with a colon-separated list) but lacks structure. It front-loads 'Computed alerts:' then enumerates types, but no sentences or logical flow. It is appropriately short but could be better organized.

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

Completeness1/5

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

For a tool with no output schema, no annotations, and 0% parameter coverage, the description is severely incomplete. It fails to explain what the tool returns, how parameters affect results, or any fundamental behavior, making it nearly unusable.

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

Parameters1/5

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

With 0% schema description coverage, the description must explain parameters. It does not mention 'district', 'org_id', or 'year' at all, leaving the agent without any understanding of how to use these optional parameters to filter results.

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 lists specific types of alerts (e.g., 'large-loan self-dealing', 'amended-report-used'), which clarifies that the tool returns computed flags. The verb is implied ('get') but missing the resource object; however, the list of alert types provides a clear purpose and distinguishes from sibling tools that fetch different data.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives. There is no indication of prerequisites, filtering logic, or scenarios where this tool is appropriate, leaving the agent to guess.

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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