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 skills add jmagly/aiwg --skill steward-prep-deliverygit clone --depth 1 https://github.com/jmagly/aiwgWrote 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/jmagly/aiwg/steward-prep-delivery)<a href="https://agentmods.dev/skills/jmagly/aiwg/steward-prep-delivery"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/steward-prep-delivery/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jmagly/aiwg/steward-prep-delivery"><img src="https://agentmods.dev/badge/skills/jmagly/aiwg/steward-prep-delivery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00032 | $0.01337 |
| Opus 5.5 | $0.00013 | $0.00535 |
| Sonnet 5.5 | $0.00006 | $0.00267 |
| Haiku 4.5 | $0.00003 | $0.00134 |
Grade A, and why
steward-prep-delivery 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 1mo 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Steward Prep for Delivery (#1269)
You are walking the user through filing a high-quality issue or PR, mirroring the import pattern used for the recent jmagly→roctinam tester report sweep (Gitea #1264–#1269).
When this fires
- "I want to file an issue"
- "I want to open a PR"
- "Help me file a bug report"
- "Should this be a new issue or a comment on an existing one?"
- "Walk me through the import flow for this tester report"
The walkthrough
Step 1: Triage
Ask the user: "Is this one bug, or did you find multiple issues in a single session?"
- One issue → use
bug-report.md(orfeature-request.mdif it's a proposal, not a defect) - Multiple findings → use
tester-report.mdand split during triage - Already filed elsewhere (GitHub, Discord, email) → use
imported-report.md
Don't make this decision for them — surface the templates and let them pick.
Step 2: Environment capture (for bug reports)
For bug-report.md, the operator needs to fill in environment info. Help them collect it:
aiwg version
aiwg doctor
node --version
uname -a # OS / kernel
If they're filing on behalf of an agent platform (Claude Code, hermes, Codex, …), make sure the platform name is captured — the same bug can manifest differently across providers.
Step 3: Duplicate detection (BEFORE filing)
Run the duplicate-detection helper. The skill's script: entrypoint
(find-duplicates.sh) searches the local aiwg discover index plus the Gitea
issue tracker for likely duplicates of the proposed title or keywords:
aiwg run skill steward-prep-delivery -- "<keywords from the issue title>"
Output: ranked list of existing open issues that match. If any look like duplicates, prefer commenting on them over filing a new one. If none match, proceed to filing.
Step 4: Draft assembly
Help the user fill out the chosen template. Specifically:
- For bug-report.md: insist on a copy-paste-able repro (not "X seems broken"). Paste exact error text in code blocks.
- For feature-request.md: insist on a concrete proposal (interfaces, file paths, command syntax) — not "we should make X better."
- For tester-report.md: encourage one finding per section with severity, repro, expected/actual.
- For imported-report.md: include the source link, original reporter handle, and platform/environment correction if the source got it wrong (e.g., the jmagly tester report cited Claude Code, but the actual harness was hermes).
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.
- 1mo ago First seen · 120 lines · 32 tokens per session scan A 2111c56e5fb9
steward-prep-delivery is a skill published in the GitHub repository jmagly/aiwg (225 stars, last pushed today), licensed MIT. It adds 32 tokens to every session and 1,337 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-05.
Other skills, from other repositories
launch
Planning releases and reporting delivery work from GitHub PR history. Use when versioning, CHANGELOGs, rollout or rollback plans, engineering metrics, retrospectives, or stakeholder reports are needed.
missive
Invoke only when spawning a quest from a GitHub issue reference. Fetches GitHub issue context for quest spawning. Parses issue references, retrieves structured data via gh, and produces branch suggestions and PR keywords. Used standalone or as input to quest orchestration.
implement-spec
A coding workflow that implements a written specification through a set of linked tickets. It creates a branch and draft pull request, assigns independent work to separate agents, combines their changes, and prepares the result for review.
monorepo-architect
Expert guide for designing and managing scalable monorepos using Turborepo, pnpm workspaces, and shared packages / Panduan ahli untuk merancang dan mengelola monorepo skalabel menggunakan Turborepo dan pnpm workspaces.
gear
Managing dependencies, CI/CD, advanced GitHub Actions workflows, containers, secrets, and operational config. Use for build, workflow, or environment work.
pdm
Navigating delivery status read-only: reconciles planned scope (specs/roadmap/PRD) against implemented code for what's built vs left. Not for priority scoring (Rank) or AC conformance (Attest).