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.
npx agentmods add skills/dirien/yet-another-agent-harness/pull-request-msgnpx skills add dirien/yet-another-agent-harness --skill pull-request-msggit clone --depth 1 https://github.com/dirien/yet-another-agent-harnessWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00067 | $0.00976 |
| Opus 5 | $0.00034 | $0.00488 |
| Sonnet 5 | $0.00013 | $0.00195 |
| Haiku 4.5 | $0.00007 | $0.00098 |
Grade A, and why
pull-request-msg-with-gh 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pull Request Message Generator
Generate a PR_MESSAGE.md file summarizing the current session's work.
Requires gh CLI authenticated with the target repository.
Prerequisite check
gh --version 2>/dev/null && gh auth status 2>/dev/null
If gh is not installed, stop and report:
- Install from https://cli.github.com
ghcannot be installed via npm- After install, run
gh auth loginto authenticate
Do not proceed without a working, authenticated gh CLI.
Workflow
- Analyze session context — review changes made in the current
session. Explore changed files with
git diffandgit statusto understand the full scope of work, in addition to reviewing conversation history. Both sources inform the PR message. - Detect issue number — use the issue detection algorithm below.
If the user indicates there is no associated issue, omit the
Closes #<issue-number>footer entirely. - Determine commit type — based on the nature of changes (see
references/pr-message-format.mdfor the list of types) - Write PR_MESSAGE.md — using the format in
references/pr-message-format.md - Add to .gitignore — add
PR_MESSAGE.mdif not already present - Validate — run commitlint and markdownlint checks
Issue number detection
The issue number MUST be determined by searching GitHub, NOT by extracting numbers from branch names.
Algorithm
# Step 1: Get branch name
BRANCH=$(git branch --show-current)
# Step 2: Extract keywords (strip leading numbers and hyphens)
# Example: "125-greenops-equivalencies" → "greenops equivalencies"
KEYWORDS=$(echo "$BRANCH" | sed 's/^[0-9]*-//' | tr '-' ' ')
# Step 3: Search GitHub issues
gh issue list --search "$KEYWORDS" --state all \
--json number,title --limit 5
Evaluation rules
- Exactly 1 result with title containing most keywords → use it
- 0 results → ask the user for the issue number
- 2+ results → show options and ask the user to pick
- Ambiguous match → ask the user to confirm
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 119 lines · 67 tokens per session scan A 53f50f6c44a0
pull-request-msg-with-gh is a skill published in the GitHub repository dirien/yet-another-agent-harness (20 stars, last pushed 3mo ago), licensed MIT. It adds 67 tokens to every session and 976 once invoked, about $0.0003 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
agent-host-chat-contributions
Build and review cross-cutting agent-host chat behavior through lifecycle contributions. Use when adding turn lifecycle side effects, prompt or context injection, restored-history transformation, protocol-action observation, or when reviewing changes that add code to AgentSideEffects or AgentService.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.