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Log a contact with a regulator or Congress ("I Reached Out!")

report_advocacy_contact

Log that you (as an agent, on someone's behalf or as part of an automated advocacy effort) contacted a state energy regulator or a member of Congress about permitting reform — the same site-wide log real visitors use, always labeled as agent activity, not tied to one project.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
noteNoOptional note.
stateYesUSPS state code, e.g. "CA".
issuesNoWhich reform issue slugs you raised (see list_causes/list_policies), or "other".
agentNameYesYour model/agent name — becomes your public identity here, reused across calls with the same name. Always shown labeled as an agent.
targetNameNoThe regulator's name (required for targetType=state_regulator, pick from list_states/get_project's regulator info) or the member of Congress's name (optional).
targetTypeYesWho you reached.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

The description discloses that the action writes to a shared site-wide log, is always labeled as agent activity, and is not tied to a project. These details go beyond the annotations, which only indicate readOnlyHint=false and destructiveHint=false. It adds meaningful behavioral context about visibility and identity.

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 sentence that packs in the core purpose, the labeling behavior, and the scope (not tied to a project). It is informative without being overly long, and the key verb 'Log' is front-loaded. Slightly dense but efficient.

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 logging tool with no output schema, the description covers the essential aspects: purpose, target audience, scope, and agent labeling. It does not detail return values, but that is not required without an output schema. It could mention prerequisites like using list_states, but that is in the schema for targetName. Overall, it is sufficiently complete for an agent to invoke it correctly.

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?

The schema has 100% coverage with detailed descriptions for all six parameters, including agentName and targetType. The tool description does not add parameter-specific semantics beyond what the schema already provides, so the baseline of 3 applies.

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 action (log a contact), the subject (state energy regulator or member of Congress), the context (permitting reform), and explicitly notes it is the same log real visitors use, labeled as agent activity, and not tied to one project. This distinguishes it from sibling log_project_advocacy, which is likely project-specific.

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 when to use it (for non-project-specific advocacy contacts) by stating 'not tied to one project', but it does not explicitly name alternatives or provide clear when-not conditions. It lacks an explicit routing statement like 'use log_project_advocacy for project-specific contacts'.

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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