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h-kazuki-pixel

release-announcer-mcp

Build announcement brief

build_announcement_brief
Read-onlyIdempotent

Generate a writing brief for release announcements across X, Reddit, GitHub, awesome-list, and MCP directories by analyzing a repository's README, release notes, and metadata.

Instructions

Gather a repository's facts (README, latest release notes, metadata) and return a complete writing brief: source material plus strict per-target writing instructions. The calling LLM then writes the final draft texts from this brief.

Targets available:

  • x_post: X/Twitter announcement (Japanese + English, ~160 chars)

  • reddit_draft: understated Reddit post draft (English, title + body)

  • profile_readme_row: GitHub profile README table row

  • awesome_mcp_pr: awesome-mcp list entry + PR title/body

  • directory_listing: MCP directory (mcp.so etc.) descriptions + tags

Args:

  • owner (string): GitHub user/org name

  • repo (string): repository name

  • targets (string[], optional): subset of targets; defaults to all five

Returns: a Markdown brief. After calling this tool, write the requested draft texts following the brief's rules exactly. All output is draft-only for human review — never post anywhere automatically.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesRepository name, e.g. 'jp-dates-mcp-server'
ownerYesGitHub user or organization name, e.g. 'h-kazuki-pixel'
targetsNoWhich announcement targets to include (default: all)
Behavior5/5

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

Annotations indicate readOnlyHint, openWorldHint, idempotentHint, and non-destructive. The description adds that it returns a Markdown brief with source material and per-target instructions, emphasizes it never posts automatically, and describes the gathering process (README, releases, metadata). No contradictions with annotations.

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 well-structured: purpose paragraph, target list with descriptions, argument list, and return/usage note. Every sentence is necessary and front-loaded. No repetition or verbosity.

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?

The tool is complex with five targets and multiple data sources. The description provides a good overview and step-by-step instructions, but lacks details on the exact structure of the returned Markdown brief. However, given the annotations and schema richness, it is mostly complete for an AI agent without an output schema.

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% with descriptions for owner, repo, and targets. The description restates these briefly but adds useful context: targets can be a subset with a default of all five. It also gives the enum values inline. This adds slight value beyond the schema, justifying a score above 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 states it gathers repository facts and returns a writing brief with per-target instructions. The verb 'build' and resource 'announcement_brief' are specific. It distinguishes from siblings fetch_repo_info (which just fetches info) and check_publish_readiness (which checks readiness), making the purpose unambiguous.

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

Usage Guidelines4/5

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

The description explains the workflow: call this tool to get a brief, then write drafts following its instructions, and notes that output is draft-only for human review, never auto-posted. It lists available targets but does not explicitly contrast with sibling tools or state when not to use it. However, the context is clear enough for the AI agent.

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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