mcp-release-prep

mcp-release-prep is a skill for Claude Code, Codex from dathere/qsv. It costs 24 tokens per session (2,409 once invoked), scanned A, original, no licence file.

A release-preparation tool for MCP servers and plugins. MCP is a standard way for an AI assistant to connect to external tools and data.

In plain words
What is it for?
It is for bumping versions throughout an MCP server or plugin and updating its changelog before publishing.
Why use it?
It keeps version changes and the changelog aligned across the files in a release.

Skill for Claude CodeCodex

Part of the qsv-data-wrangling plugin — 20 skills, 3 agents, 4 hooks shipped together

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/dathere/qsv/mcp-release-prep
Any agent
npx skills add dathere/qsv --skill mcp-release-prep
Clone the repo
git clone --depth 1 https://github.com/dathere/qsv

Made for: Claude Code, Codex.

Or install qsv-data-wrangling, the plugin that ships this one along with the rest of its 20 skills, 3 agents, 4 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for mcp-release-prep

README.md
[![agentmods](https://agentmods.dev/badge/skills/dathere/qsv/mcp-release-prep.svg)](https://agentmods.dev/skills/dathere/qsv/mcp-release-prep)
Your own site
<a href="https://agentmods.dev/skills/dathere/qsv/mcp-release-prep"><img src="https://agentmods.dev/badge/skills/dathere/qsv/mcp-release-prep.svg" alt="Measured on agentmods" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,409 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00024 $0.02409
Opus 5 $0.00012 $0.01205
Sonnet 5 $0.00005 $0.00482
Haiku 4.5 $0.00002 $0.00241

Measured 4d ago against content hash 75a3220285c1, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mcp-release-prep scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/skills/mcp-release-prep/SKILL.md · 184 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 184 lines · 24 tokens per session scan A 75a3220285c1

Subscribe to this mod's changes

mcp-release-prep is a skill published in the GitHub repository dathere/qsv (3,775 stars, last pushed today), with no licence file. It adds 24 tokens to every session and 2,409 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

sq-site-dependabot

Reviews, validates, and safely merges Dependabot pull requests for the sq.io site (site/, Bun lockfile). Use when clearing site dependency PRs, triaging Dependabot failures, or checking Lighthouse impact before merge.

neilotoole/sq · 50 tokens

sq-actions-dependabot

Reviews and merges Dependabot pull requests for GitHub Actions (the github-actions ecosystem) that bump uses: pins in .github/workflows/. Use for Dependabot githubactions PRs (branches like dependabot/githubactions/...), not go.mod or site/ Bun PRs.

neilotoole/sq · 65 tokens

sq

Guides use of the sq CLI to query SQL databases and tabular files with SLQ (sq's jq-like query language) or native SQL, manage sources, choose output formats, and run inspect, diff, and table commands. Use when the user mentions sq, SLQ, wrangling CSV/Excel/JSON/DB data, cross-source joins, or command-line data…

neilotoole/sq · 89 tokens

sq-gomod-dependabot

Reviews and merges Dependabot pull requests for Go modules (gomod) at the sq repo root. Use for dependabot gomod PRs, go.mod/go.sum updates, and Go module security bumps—not site/ Bun PRs.

neilotoole/sq · 54 tokens

portaljs-add-dataset

Add a dataset (CSV, TSV, JSON, or GeoJSON) to an existing PortalJS portal. Appends an entry to datasets.json so the catalog and showcase render it automatically; routes the data by source (local file vs remote URL) — R2 via Git LFS by default, remote URLs by passthrough. Use when registering a new dataset in a…

datopian/portaljs · 84 tokens

portaljs-check-data-quality

Audit a local or remote tabular file (CSV/TSV) for common data quality issues — schema, nulls, types, duplicates. Read-only. Use when a dataset needs a quality check before publishing, or a showcase renders wrong (blank cells, garbled numbers, an unsortable date column) and the cause needs isolating.

datopian/portaljs · 76 tokens