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AB release-note-writer

Write grouped, user-friendly release notes from git history, changelogithub output, GitHub releases, PR lists, or raw commit logs. Use when Codex needs to turn technical changelogs into English-only release notes for AIRI or similar products, including end-user highlights, developer/API notes, contributor-facing internal tooling notes, upgrade notes, or follow-up style-rule updates after wording feedback.

moeru-ai/airi Agent Skills author: moeru-ai MIT 2 files body ≈ 2 172 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Write grouped, user-friendly release notes from git history, changelogithub output, GitHub releases, PR lists, or raw commit logs.

As a process B 69/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice

GeneratorGitHubSoftware developmentWriting and documentsMarketingtype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
100
Quality 40%
87
Run on models
none yet
Process rating
B
69/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
20
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 0

    ✓ No critical or high findings

    Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 69/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 22 mutating operations with no state check
    • 60Result and completion. Output format stated, no completion criterion
    • 100Tools and files. No external tools needed
    • 100Steps. 56 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 2172 tokens
    • low 11 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +5Description has no quoted example phrases that should trigger the skill
    • +4Description does not say when NOT to use the skill (false activations)
    • +1No license
    • +2Single-language instructions
    • +3Description length 408: enough signal without eating the budget
    • +4Structure: 12 headings
    • +3Step-by-step instructions: 56 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.