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/parkerm2/create-claude-workflow/wf-spawnnpx skills add ParkerM2/create-claude-workflow --skill wf-spawngit clone --depth 1 https://github.com/ParkerM2/create-claude-workflowWhat 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 | $0.00027 | $0.00815 |
| Opus 5 | $0.00014 | $0.00407 |
| Sonnet 5 | $0.00005 | $0.00163 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade B, and why
wf-spawn scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
cat .claude/.workflow-state/setup-complete.json How it starts
The opening of the file, as written. The whole thing — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
WF: Spawn Wave
Gate Check
cat .claude/.workflow-state/setup-complete.json
If the file does not exist: STOP — "Team setup not complete. Run Step 3
(wf-setup) first."
Load: TICKET, TEAM_LEADER_NAME, currentWave, waveMap, PLUGIN_ROOT,
workPrefix, worktreeDir. Also check for a wave-specific gate:
# If currentWave > 1, previous wave must be complete
cat .claude/.workflow-state/wave-$((currentWave - 1))-complete.json 2>/dev/null
If previous wave stamp missing and currentWave > 1: STOP — "Wave
<N-1> not complete. Run wf-qa-gate for that wave first."
Your Task
Spawn agent pairs for the current wave. Both the coder and QA agent are spawned in the same message (parallel tool calls).
Checklist
1. Identify This Wave's Tasks
From waveMap, get the list of task slugs for currentWave. For each slug,
read the corresponding task file to get: taskNumber, taskName, taskSlug,
agentRole, agentDefinition, workbranch, worktreePath.
2. Read Spawn Templates
cat {PLUGIN_ROOT}/prompts/implementing-features/THIN-SPAWN-TEMPLATE.md
Use the Coding Agent and QA Agent templates from this file.
3. Spawn Pairs (one message per task, both agents in parallel tool calls)
For each task, in a single message, call the Agent tool twice:
Coder:
Agent tool:
description: "<taskSlug> coder"
subagent_type: general-purpose
team_name: "<TICKET>"
name: "coder-task-<N>"
mode: bypassPermissions
model: sonnet
run_in_background: true
isolation: worktree (only if useWorktrees is false)
prompt: <substitute THIN-SPAWN-TEMPLATE.md coding template>
QA:
Agent tool:
description: "<taskSlug> QA"
subagent_type: general-purpose
team_name: "<TICKET>"
name: "qa-task-<N>"
mode: bypassPermissions
model: haiku
run_in_background: true
prompt: <substitute THIN-SPAWN-TEMPLATE.md QA template>
Save the returned task_id for each agent.
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 · 114 lines · 27 tokens per session scan B 75046b109a80
wf-spawn is a skill published in the GitHub repository ParkerM2/create-claude-workflow (4 stars, last pushed 5mo ago), licensed MIT. It adds 27 tokens to every session and 815 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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.
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.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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…