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Ankra

by ai.ankra
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Run pipeline

run_pipeline

Start a manual run of a connected repository's Ankra pipeline (its definition of record) at a branch, tag or commit, on the organisation's CI cluster. Give ref (refs/heads/main or main), head_sha (a full commit sha that must be the ref's tip or an ancestor of it), or both. inputs are the pipeline's on.manual.inputs. full_run runs every stage, ignoring path filters. A dispatch identical to a queued one joins it (already_queued). Follow the run with watch_pipeline_run. Address the repository with exactly one of repository_id, application_id, or owner and repo. Needs pipelines.operate.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "run_pipeline"
  }
}

Input Schema

NameRequiredDescriptionDefault
refNoBranch or tag to run at, for example main or refs/tags/v1.2.0.
repoNoRepository name, with owner.
ownerNoRepository owner (organisation or user), with repo, instead of repository_id.
inputsNoDispatch inputs by name, as the pipeline's on.manual.inputs declares them; every value is a string.
reasonNoA short note stored on the run.
full_runNoRun every stage, ignoring path filters (default false).
head_shaNoFull commit sha to run at.
providerNoNarrows owner and repo when the same repository is connected on two providers.
repository_idNoThe connected repository's id, from list_pipeline_repositories.
application_idNoAn application whose linked repository to address, instead of repository_id.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

The description provides key behavioral constraints not found in annotations, such as the requirement that head_sha must be the tip or an ancestor of the ref, and explains the outcome of identical dispatches (joining existing runs). This adds vital execution logic beyond safety hints.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The definition is extremely dense and written as a single complex block of text, making it difficult for an agent to quickly parse requirements. While efficient in information density, its lack of structure lowers its score.

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

Completeness5/5

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

Given the high parameter count (10) and specific technical constraints, the description is highly complete. It covers the required addressing methods, input formats, and the necessary follow-up steps for monitoring, leaving no major operational gap for a determined agent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema coverage is 100%, the description adds essential semantic context, particularly detailing how inputs are handled (matching on.manual.inputs) and explaining the functional impact of the full_run parameter. This justifies a score higher than the baseline 3.

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 defines the action (Start manual run), the resource (Ankra pipeline), and the operational context (organisation's CI cluster). It functions as an excellent starting point for an agent understanding the tool's primary function.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit rules for usage, including the constraint that only one of three methods (id, application_id, or owner+repo) must be used for addressing the repository. It also guides the agent on sequencing by recommending watch_pipeline_run.

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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