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hydra-mcp

hydra-mcp

by slopwife
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_build_log

Read-onlyIdempotent

Retrieve the last lines of a Hydra build log or a specific build step to diagnose failures, optionally choosing an instance and tail length.

Instructions

Get the last lines of a build's log, or of one of its build steps (e.g. the failed dependency).

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": {
      "build_id": "<build_id>"
    },
    "name": "get_build_log"
  }
}

Input Schema

NameRequiredDescriptionDefault
stepNoBuild step number from get_build; omitted = the build's own derivation
build_idYes
instanceNoConfigured Hydra instance; omitted uses the default
tail_linesNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare this as read-only, idempotent, non-destructive, and open-world, so the safety profile is covered. The description adds that only the tail of the log is returned and that step logs are supported, but it omits behavioral details such as truncation behavior, permissions, or how missing logs are handled.

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?

The description is a single front-loaded sentence with no wasted wording. It immediately communicates the core action and the optional step-level scope.

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?

Given the output schema and rich annotations, the description covers enough for an agent to understand this as a log-tail retrieval tool. The main missing piece is explicit routing guidance relative to sibling build tools.

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 description maps naturally to tail_lines ('last lines') and step ('one of its build steps') and adds the useful failed-dependency example. However, with only 50% schema description coverage, it does not explain instance or give details about tail_lines limits/defaults, so it only partially compensates for the schema gap.

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 states a specific verb and resource: retrieving the last lines of a build log or one of its step logs. It clearly distinguishes log retrieval from general build inspection, though it does not explicitly name sibling tools such as get_build.

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 phrase 'or of one of its build steps (e.g. the failed dependency)' implies when step-level logs are useful, but the description does not explicitly state when to use this tool versus get_build or other alternatives. Usage context is present but mostly left to inference.

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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