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GitHub + Linear Dev Workflows

GitHub + Linear Dev Workflows

by r28ai
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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github_actions_list_pending_deployments

Read-onlyIdempotent

List the environments a workflow run is waiting on for approval and identify who can approve them, so you can unblock stalled deployments.

Instructions

List the environments a run is waiting on for approval, and who can approve them. This is where a run sits when it is neither failing nor progressing.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "owner": "<owner>",
      "repo": "<repo>",
      "runId": "<runId>"
    },
    "name": "github_actions_list_pending_deployments"
  }
}

Input Schema

NameRequiredDescriptionDefault
repoYesThe name of the repository without the `.git` extension. The name is not case sensitive.
ownerYesThe account owner of the repository. The name is not case sensitive.
runIdYesThe ID of the workflow run.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description adds domain context about the blocked-run state, but says nothing about approval mechanics, pagination, or result shape. Moderate added value over the annotations.

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?

Two sentences, front-loaded with the action and returned content. The second sentence is arguably flavor rather than instruction, but it does add interpretive value for the blocked-state case, so it earns its place without bloat.

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 read-only three-parameter list operation with no output schema and full annotation coverage, the description conveys what is listed and in what state. Missing only minor operational detail such as pagination or typical follow-up actions.

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 owner/repo/runId are fully documented in the schema and the description adds no syntax, format, or sourcing detail (e.g. which endpoint yields runId). This is the expected baseline when the schema does the heavy lifting.

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 names a specific verb and resource ('List the environments a run is waiting on for approval') and even specifies the returned fields (who can approve them). It does not explicitly contrast with the sibling github_actions_review_pending_deployments, whose name is close enough to confuse an agent, so it falls short of the top tier.

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?

'This is where a run sits when it is neither failing nor progressing' implies the situation in which the tool is relevant, but there is no explicit when-to-use/when-not guidance and no alternative named (e.g. review_pending_deployments for acting on the same state). Usage is inferable rather than stated.

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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