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 commands/parkerm2/create-claude-workflow/settingsgit 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 | $0.00015 | $0.00359 |
| Opus 5 | $0.00008 | $0.00179 |
| Sonnet 5 | $0.00003 | $0.00072 |
| Haiku 4.5 | $0.00002 | $0.00036 |
Grade A, and why
settings 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 2d 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.
What it actually says
/settings — Workflow Settings & Audits
Manage workflow configuration, toggle guard hooks, audit agent definitions, and diagnose performance bottlenecks.
Phase 1: Present Menu
Use AskUserQuestion to ask the user what they want to do:
Question: "What would you like to configure or audit?"
Options:
- Guard Permissions — Toggle branch guard, destructive guard, and config guard on/off. Controls which PreToolUse hooks are active.
- Audit Agents — Scan agent definitions, validate scopes against project structure, flag stale paths, overlaps, and uncovered directories.
- Audit Performance — Diagnose workflow performance bottlenecks: file sizes, hook overhead, context budget, progress file growth.
Phase 2: Execute Selected Flow
Based on the user's selection, read and follow the corresponding sub-flow file:
If "Guard Permissions" selected:
Read and follow: prompts/settings/guard-permissions.md
(This file contains the full guard permissions workflow — reading current settings, presenting the toggle checklist, and updating .claude/workflow.json.)
If "Audit Agents" selected:
Read and follow: prompts/settings/audit-agents.md
(This file contains the full agent audit workflow — scanning definitions, indexing project structure, detecting stale paths/overlaps/uncovered directories, and generating a report with fix suggestions.)
If "Audit Performance" selected:
Read and follow: prompts/settings/audit-performance.md
(This file contains the full performance audit workflow — measuring file sizes, counting hooks, checking context budgets, and generating a 10-category report with recommendations.)
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.
- 2d ago First seen · 46 lines · 15 tokens per session scan A 75608eddd8ad
settings is a command published in the GitHub repository ParkerM2/create-claude-workflow (4 stars, last pushed 5mo ago), licensed MIT. It adds 15 tokens to every session and 359 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.
Other commands, from other repositories
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.