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RikiGomes

woodpecker-mcp

by RikiGomes

Recent pipeline activity

recent_activity
Read-only

List recent pipelines across all accessible repositories to identify failing or running builds without knowing a specific repo.

Instructions

Lists the most recent pipelines across the repositories the token has push or admin access to, newest first: repo full_name, repo_id, pipeline number, status, event, branch, title, short commit, author, ISO created time and duration_s; get_pipeline gives the web URL. Use it to answer "what is failing / running right now?" without knowing a repo. Woodpecker returns only the 50 newest pipelines; status filters within those (e.g. failure) and limit caps the result (default 10, max 50). For older history of one repo use list_pipelines.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum entries (default 10, max 50).
statusNoOnly pipelines in this status, e.g. failure, running, success.
instanceYesWoodpecker instance name. Configured instances: default.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already cover read-only and open-world safety, so the bar is lower; the description adds real behavioral context beyond them — auth scope (push/admin access), the Woodpecker 50-pipeline ceiling, and the fact that `status` filters only within that window. It stops short of return-size or rate-limit detail, but the core caveats are disclosed.

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?

Purpose and scope are front-loaded, then alternatives, then caveats — a sensible ordering. The run-on field enumeration is long, though it is justified by the absence of an output schema, so most of it earns its place.

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?

With no output schema, the description supplies the return fields itself, names alternatives, and discloses the 50-item cap and filter semantics. An agent has everything it needs to call this correctly without guessing.

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?

Schema coverage is 100% so the baseline is 3, but the description adds semantics the schema cannot express: `status` filters within the 50 newest pipelines only, and `limit` caps that same window (default 10, max 50). That interaction between the two parameters materially changes how an agent should call the tool.

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?

Specific verb+resource ('Lists the most recent pipelines') with an explicit scope (repos the token has push/admin access to) and an enumerated return shape. It clearly demarcates itself from list_pipelines (older history of one repo) and get_pipeline (web URL), so an agent can route without opening schemas.

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?

Gives the driving question ('what is failing / running right now?') plus the preconditions ('without knowing a repo'), and names the alternative for the contrasting case ('For older history of one repo use list_pipelines'). When-to-use and when-to-use-something-else are both covered.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.