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civiq

by io.github.civdotiq

Environmental influence analysis

analyze_environmental_influence
Read-only

Cross-reference EPA violations in a district with lobbying and campaign finance. Maps facility SIC codes to sectors, finds lobbying in those sectors by the district rep, checks EPA-oversight committee membership overlap, and identifies environmental legislation votes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
stateCodeYesTwo-letter state code (e.g., OH)
districtNumberYesDistrict number (0 for at-large)

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint and openWorldHint. The description adds multi-step behavioral details (SIC mapping, lobbying check, committee overlap, votes) that go beyond annotations, without contradiction.

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 a single dense sentence covering the entire process efficiently. No wasted words, but it could be slightly more structured with bullet points.

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

Completeness3/5

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

No output schema exists, and the description does not mention what the tool returns. For a complex analysis, describing the output format would improve completeness.

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%. The description does not add parameter details beyond the schema, but it implies stateCode and districtNumber identify the district. Baseline of 3 is appropriate.

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 cross-references EPA violations with lobbying and campaign finance, listing specific steps. This distinguishes it from sibling tools like analyze_energy_policy_influence or get_district_environmental_profile.

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 for environmental influence analysis but does not explicitly state when to use this tool over alternatives or provide exclusion criteria. Given many sibling influence analysis tools, more guidance would help.

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

A3.9/5.0
Disambiguation5/5

Each tool has a clear, specific purpose with detailed descriptions that differentiate them. Prefix patterns like get_district_, search_, analyze_, get_, etc., help an agent easily identify the correct tool for a task.

Naming Consistency5/5

All tool names use a consistent verb_noun or verb_noun_noun pattern with underscores. The naming convention is uniform across the entire set, with no mixing of styles or ambiguous verbs.

Tool Count3/5

With 47 tools, the count is high but justified by the broad scope of civic data analysis. While some agents might find the sheer number overwhelming, the tools are organized into clear categories (district profiles, searches, analyses) that make navigation feasible.

Completeness5/5

The toolset covers an impressively wide range of domains: legislation, representatives, districts, voting, committees, campaign finance, lobbying, federal spending, regulations, environment, energy, healthcare, housing, disaster, banking, consumer complaints, crime, vehicles, and more. There are no obvious missing operations for a civic data platform.

Resources