get_projectFull detail for one WaitingForPower project by slug — cited sources, milestone timeline, capacity, and estimated investment waiting. Get a slug from search_projects first.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | Project slug, as returned by search_projects. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does describe what the returned detail contains and that it is for one project, but it does not disclose error behavior, authentication needs, rate limits, or field availability caveats. This is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences: the first front-loads the tool's purpose and return scope, and the second gives the exact prerequisite. There is no filler or duplication.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, no-output-schema tool, the description is complete enough: it explains what the return value includes, how to obtain the required slug, and the scope of a single project. Nothing critical is missing for an agent to call this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% and the single parameter's schema description already says it is a project slug '"as returned by search_projects."' The tool description repeats the same guidance without adding new parameter-specific semantics, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description states a specific operation: fetch full detail for exactly one WaitingForPower project by slug, and enumerates the included content (cited sources, milestone timeline, capacity, estimated investment waiting). This clearly distinguishes it from the list/search siblings such as search_projects and get_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent to obtain the slug from search_projects first, establishing a clear prerequisite and workflow. It implies this tool is for a single project's full detail, though it does not enumerate when-not-to-use alternatives beyond that sequencing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.