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/shipwithai/shipwithai-plugins/setup-agentsnpx skills add ShipWithAI/shipwithai-plugins --skill setup-agentsgit clone --depth 1 https://github.com/ShipWithAI/shipwithai-pluginsWhat 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 | $0.00048 | $0.00939 |
| Opus 5 | $0.00024 | $0.00469 |
| Sonnet 5 | $0.00010 | $0.00188 |
| Haiku 4.5 | $0.00005 | $0.00094 |
Grade A, and why
setup-agents 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/setup-agents
Configures .claude/agents/ with specialized sub-agents for the project.
Mode Detection
Read .claude/starter-context.json if it exists
→ Exists: use fields agents_selected, project.type, project.team_size, project.tier — skip suggest
→ Does not exist (standalone): load catalog → detect context → suggest → confirm
Argument Handling
If an agent name is passed directly (e.g. /setup-agents pr-review): skip the suggestion
step and go straight to that agent's entry in the catalog.
Context Detection
Load agents-catalog.json. For each entry, evaluate suggestWhen:
- files: check whether any listed glob exists in the project root
- context: if
.claude/starter-context.jsonexists, evaluate conditions against its fieldsteamSize > N→ readproject.team_sizetier == N→ readproject.tier
- always: if
alwaysIncludeistrue, suggest unconditionally — present first
In standalone mode without starter-context.json: ask the user for context that cannot
be inferred from files (e.g. "How many people work on this project?").
For each suggested agent: show preview → confirm before writing.
How Sub-Agent Context Works
Sub-agents receive only two inputs when invoked:
- Their agent file content (system prompt)
- The prompt string passed by the main agent at invocation time
They do not inherit the main agent's conversation history or open files.
Two patterns handle this:
Autonomous agents — self-orient by reading project files on startup. No runtime input needed beyond a trigger phrase. Examples: drift-monitor, dependency-scanner, test-coverage.
Task-specific agents — require runtime context passed in the invocation prompt. The caller must include specific parameters (e.g. PR number, branch name). Examples: pr-review.
Use contextType in the catalog to identify which pattern each agent follows.
Agent File Format
Write to .claude/agents/[id].md using this structure:
What ships with it
2 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 · 126 lines · 48 tokens per session scan A 09c74ba857e5
setup-agents is a skill published in the GitHub repository ShipWithAI/shipwithai-plugins (10 stars, last pushed 21d ago), licensed MIT. It adds 48 tokens to every session and 939 once invoked, about $0.0002 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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