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energy-permitting-tracker

by com.waitingforpower

Search energy projects

search_projects

Search the WaitingForPower dataset of U.S. energy projects (generation, transmission, storage, LNG, pipelines) currently stuck waiting on permitting approval. Returns a paginated summary; call get_project with a slug for full detail (sources, milestone timeline).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results to return (1-100).
stageNoFilter to one or more current permitting stages.
stateNoUSPS state code, e.g. "CA". Omit for all states.
offsetNoNumber of matching results to skip, for paging.
statusNoWhich status bucket to search. Defaults to "in_permitting" (the site's original "still waiting" scope) if omitted — pass "permits_complete", "cancelled_suspended", "no_longer_reported", or "all" to reach approved, cancelled, or untracked-by-source projects too.
fuelTypeNoFilter to one or more fuel/technology types.
minCapacityNoOnly projects with capacity at least this many MW.
projectTypeNoFilter to one or more project types.
minYearsWaitingNoOnly projects waiting at least this many years.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does disclose that results are a paginated summary and that full detail lives elsewhere, but it doesn't mention pagination response shape, ordering, limits, or any access/error behavior. It is adequate but not richly transparent.

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?

Two sentences, front-loaded with purpose and dataset scope, and ends with a useful routing hint. Every phrase earns its place; no redundancy or filler.

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?

The description covers dataset scope, filtering context, and the relationship to get_project. However, there is no output schema and the description only says 'paginated summary' without describing what fields each result contains or how pagination is represented, leaving an important gap for a 9-parameter search tool.

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 doesn't add parameter-specific detail, but none is needed because every parameter already has a meaningful schema description.

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 identifies a specific resource (WaitingForPower U.S. energy projects waiting on permitting) and a clear verb (search). It also contrasts with get_project by mentioning that full detail requires that sibling tool, so an agent can distinguish the two.

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?

It clearly states this tool is for searching and returning paginated summaries, and explicitly routes to get_project for full detail. It doesn't enumerate exclusions for the other list_* siblings, but the core search-vs-detail decision is unambiguous.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All energy-permitting-tracker toolsInspect
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TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct role: search, detail lookup, aggregate stats, neutral cause categories, policy proposals, and state reference data. Even the two list tools are explicitly separated as neutral versus argued content, so an agent should not confuse them.

Naming Consistency5/5

All tool names consistently follow a verb_noun snake_case pattern: get_project, get_stats, list_causes, list_policies, list_states, search_projects. The pattern is predictable and readable.

Tool Count5/5

Six tools is well-scoped for a specialized read-only energy permitting dataset. Each tool earns its place: two for project discovery/detail, one for aggregate stats, and three for supporting reference and policy content.

Completeness5/5

The surface covers the core workflows for this domain: searching projects, retrieving full details, summarizing aggregate statistics, and accessing the supporting reference data. There are no obvious dead ends or missing operations for a read-only tracker.

Resources