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RikiGomes

woodpecker-mcp

by RikiGomes

Get step logs

get_step_logs

Fetch trailing log lines for a specific pipeline step by step ID, with configurable tail count.

Instructions

Fetches the log output of one pipeline step (use the step ids from get_pipeline). Returns the last tail lines.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesRepository as "owner/name" (e.g. "acme/webapp") or a numeric Woodpecker repo id.
tailNoNumber of trailing log lines to return (default 100, max 2000).
numberYesPer-repo pipeline number the step belongs to.
step_idYesStep id from get_pipeline (not the step name).
instanceYesWoodpecker instance name. Configured instances: default.
Behavior4/5

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

With no annotations, the description carries the burden and does well: 'Fetches' indicates a non-destructive read, and 'Returns the last tail lines' discloses the output limiting behavior. It does not cover error handling or auth, but for a read-only log tool this is sufficient.

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 two concise sentences, front-loaded with the main purpose and a useful behavioral detail. Every word earns its place, with no redundancy or filler.

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 simple read tool with fully documented parameters, the description covers the core action and the tail output limitation. Without an output schema, it could specify the log format, but 'log output' implies plain text, and the edge cases are minor for this use case.

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 coverage is 100%, so the baseline is 3. The description adds minimal new meaning beyond the schema—it repeats the get_pipeline dependency for step_id and mentions tail, but the schema already describes each parameter in detail, including defaults and max values.

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 states the tool fetches log output for one pipeline step, using a specific verb and resource. It also distinguishes itself from siblings by referencing get_pipeline for step IDs, making clear it's for step-level logs rather than pipeline-level information.

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 description implies usage by noting step IDs come from get_pipeline, but it does not explicitly state when to use this tool versus alternatives like get_pipeline. It gives a prerequisite but no exclusions or direct comparison.

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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