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/jcottam/agent-resources/shipnpx skills add jcottam/agent-resources --skill shipgit clone --depth 1 https://github.com/jcottam/agent-resourcesWhat 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 | $0.00099 | $0.03636 |
| Opus 5 | $0.00049 | $0.01818 |
| Sonnet 5 | $0.00020 | $0.00727 |
| Haiku 4.5 | $0.00010 | $0.00364 |
Grade A, and why
ship 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 3d 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 — 295 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ship
Pre-flight checklist that validates the branch, runs quality gates, updates documentation and changelog, and opens a pull request.
GitHub is the primary host; Azure DevOps is secondary. The scripts detect the provider from the git remote (github.com vs dev.azure.com). When the remote is ambiguous, they try GitHub first, then Azure DevOps.
Workflow overview
- [ ] Step 0: Verify CLI tools and host auth (GitHub or Azure DevOps)
- [ ] Step 1: Preflight (rebase, branch, existing PR, provider)
- [ ] Step 2: Quality gates (lint → typecheck → test → build)
- [ ] Step 3: Documentation (README.md, AGENTS.md)
- [ ] Step 4: Changelog bump
- [ ] Step 5: Push and open or update PR
- [ ] Step 6: Post-flight report
Script path placeholder
$SCRIPTS is a placeholder for the absolute path to the scripts/ directory next to this file — not a predefined shell or PowerShell variable. Resolve it before running any command:
- bash/zsh:
SCRIPTS=/abs/path/to/scripts - PowerShell:
$SCRIPTS = 'C:\abs\path\to\scripts'
Running helper scripts (cross-platform)
The helper scripts (preflight.sh, detect-gates.sh, changelog-bump.sh, backfill-pr.sh) are bash and require bash, jq, node, and git on PATH. PR operations also need gh (GitHub) and/or az (Azure DevOps), depending on the repo remote.
- macOS / Linux: run directly — e.g.
bash "$SCRIPTS/preflight.sh". - Windows (PowerShell): use Git Bash, not WSL
bash.exe(which cannot see Windows-installed tools). Discover Git Bash from the git install, then invoke each script through it:
$gitRoot = Split-Path (Split-Path (Get-Command git).Source) # e.g. C:\Program Files\Git
$bash = Join-Path $gitRoot 'bin\bash.exe'
& $bash "$SCRIPTS/preflight.sh" # repeat per script + args
If bin\bash.exe does not exist under the git root, stop and tell the user to install Git for Windows (bundles Git Bash).
Throughout the steps below, every $SCRIPTS/<name>.sh reference means run that script using the OS-appropriate invocation above.
What ships with it
5 files 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.
- 3d ago First seen · 295 lines · 99 tokens per session scan A cfbb383331ed
ship is a skill published in the GitHub repository jcottam/agent-resources (30 stars, last pushed 27d ago), licensed MIT. It adds 99 tokens to every session and 3,636 once invoked, about $0.0005 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
sandbox-next
Use when building or changing Cloudflare Sandbox apps on @cloudflare/sandbox@next (Sandbox SDK 1.0 preview)—code execution, AI runners, interpreters, CI-like jobs, terminals, files, mounts, tunnels, preview URLs, lifecycle, or errors. Not for the default stable package (use sandbox-stable) or for porting stable to…
durable-objects
Create and review Cloudflare Durable Objects. Use when building stateful coordination (chat rooms, multiplayer games, booking systems), implementing RPC methods, SQLite storage, alarms, WebSockets, or reviewing DO code for best practices. Covers Workers integration, wrangler config, and testing with Vitest. Biases…
80-livekit-agents-majiayu000-claude-skill-registr
Create your LiveKit Agents skill from official documentation, then learn to improve it throughout the chapter.
turnstile-spin
Set up Cloudflare Turnstile end-to-end in a project. Scan the codebase, create the widget via the Cloudflare API, embed it where user requests need bot verification (form submissions, SPA actions, API endpoints, download links, comment or vote submissions, etc.), wire canonical server-side siteverify in the customer's…
dag-factory
Authors Apache Airflow DAGs declaratively from dag-factory YAML configs. Use when building DAGs declaratively from YAML via dag-factory; creating/editing dag-factory templates/YAML configs,reating/editing dag-factory YAML configs, defaults, dynamic tasks, datasets, or callbacks; or validating dag-factory…
deploying-airflow
Deploys Airflow DAGs and projects. Use when deploying Airflow or answering anything about deployment - deploying DAGs/projects, pushing code, setting up CI/CD, deploying to production or deployment strategies for Airflow.