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/chen3feng/agent-skills/agent-work-artifacts-layoutnpx skills add chen3feng/agent-skills --skill agent-work-artifacts-layoutgit clone --depth 1 https://github.com/chen3feng/agent-skillsWrote 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.
[](https://agentmods.dev/skills/chen3feng/agent-skills/agent-work-artifacts-layout)<a href="https://agentmods.dev/skills/chen3feng/agent-skills/agent-work-artifacts-layout"><img src="https://agentmods.dev/badge/skills/chen3feng/agent-skills/agent-work-artifacts-layout.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00027 | $0.02410 |
| Opus 5 | $0.00014 | $0.01205 |
| Sonnet 5 | $0.00005 | $0.00482 |
| Haiku 4.5 | $0.00003 | $0.00241 |
Grade A, and why
agent-work-artifacts-layout 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 5d 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 — 242 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent work artifacts: where do they go?
When to use
Any task where the agent produces files that are not the user's
intended deliverable: PR body drafts for gh pr create --body-file,
throwaway repro_*.py / check_*.sh scripts, audit reports,
analysis dumps, temporary fixtures. Without a convention these end
up either polluting the working tree (triggering "do I need to
delete this?" round-trips) or getting lost across sessions even
when they had reuse value.
Problem
Three recurring failure modes:
- PR body files left in the repo root (e.g.
pr_body.md), forcing the user to confirm deletion after every PR. - One-off scripts committed to random places — sometimes in the repo root, sometimes nowhere — making future contributors unsure whether they are project tooling or dead weight.
- Fixed temp paths like
/tmp/pr_body.mdthat collide between parallel agent sessions.
Solution
Route every artifact through this four-way decision:
1. Single-use (PR body, gh intermediate, shell pipe)?
→ system temp via mktemp -t <slug>.XXXXXX.<ext>
(POSIX: $TMPDIR or /tmp; Windows: %TEMP%)
2. Repo-scoped helper, human-authored, part of project lifecycle?
→ scripts/ (or tools/ if the repo already uses that)
with argparse CLI, docstring, usage example.
3. Repo-scoped helper, agent-authored, reviewed and reusable?
→ .agent/tools/ (tracked subdirectory of the agent working area,
see the four-cell layout below)
4. General-purpose, useful across projects?
→ offer to publish as a GitHub Gist.
5. Agent working notes / drafts / caches NOT meant for sharing?
→ .agent/scratchpad/ | .agent/artifacts/ | .agent/context/
(gitignored, local-only)
If none apply, delete the file rather than leaving it ambiguous.
.agent/ four-cell layout
.agent/ is not a single bucket — split it by lifetime and
tracking intent:
| Subdirectory | Purpose | Tracked? |
|---|---|---|
.agent/scratchpad/ |
Free-form notes, pseudo-code, drafts. | No |
.agent/artifacts/ |
Generated deliverables (exported docs, images, one-off reports). | No |
.agent/tools/ |
Reviewed agent-authored helpers for this repo. | Yes |
.agent/context/ |
Project index / knowledge-base caches / embeddings. | No |
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.
- 5d ago First seen · 242 lines · 27 tokens per session scan A 86cd739291ee
agent-work-artifacts-layout is a skill published in the GitHub repository chen3feng/agent-skills (5 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 27 tokens to every session and 2,410 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 2026-08-31.
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development
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post-build-flow
Handles workflow verification and setup after build-workflow succeeds, or when the message contains workflow-verification-follow-up or workflow-setup-required. Load after direct builds, when verificationReadiness requires action, or on orchestrator verify/setup follow-up turns.
n8n:human-like-code-review
Reviews a GitHub pull request like a thoughtful human reviewer and writes the feedback to a markdown file. Prioritizes context, architecture fit, solution complexity, bugs, security edge cases, and missing tests. Use when given a PR URL to review, or when the user says /human-like-code-review.