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/catlog22/claude-code-workflow/completegit clone --depth 1 https://github.com/catlog22/Claude-Code-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 | $0.00020 | $0.01116 |
| Opus 5 | $0.00010 | $0.00558 |
| Sonnet 5 | $0.00004 | $0.00223 |
| Haiku 4.5 | $0.00002 | $0.00112 |
Grade A, and why
complete scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Complete Workflow Session (/workflow:session:complete)
Mark the currently active workflow session as complete, archive it, and update manifests.
Pre-defined Commands
# Phase 1: Find active session
SESSION_PATH=$(find .workflow/active/ -maxdepth 1 -name "WFS-*" -type d | head -1)
SESSION_ID=$(basename "$SESSION_PATH")
# Phase 3: Move to archive
mkdir -p .workflow/archives/
mv .workflow/active/$SESSION_ID .workflow/archives/$SESSION_ID
# Cleanup marker
rm -f .workflow/archives/$SESSION_ID/.archiving
Key Files to Read
For manifest.json generation, read ONLY these files:
| File | Extract |
|---|---|
$SESSION_PATH/workflow-session.json |
session_id, description, started_at, status |
$SESSION_PATH/IMPL_PLAN.md |
title (first # heading), description (first paragraph) |
$SESSION_PATH/.tasks/*.json |
count files |
$SESSION_PATH/.summaries/*.md |
count files |
$SESSION_PATH/.review/dimensions/*.json |
count + findings summary (optional) |
Execution Flow
Phase 1: Find Session (2 commands)
# 1. Find and extract session
SESSION_PATH=$(find .workflow/active/ -maxdepth 1 -name "WFS-*" -type d | head -1)
SESSION_ID=$(basename "$SESSION_PATH")
# 2. Check/create archiving marker
test -f "$SESSION_PATH/.archiving" && echo "RESUMING" || touch "$SESSION_PATH/.archiving"
Output: SESSION_ID = e.g., WFS-auth-feature
Phase 2: Generate Manifest Entry (Read-only)
Read the key files above, then build this structure:
{
"session_id": "<from workflow-session.json>",
"description": "<from workflow-session.json>",
"archived_at": "<current ISO timestamp>",
"archive_path": ".workflow/archives/<SESSION_ID>",
"metrics": {
"duration_hours": "<(completed_at - started_at) / 3600000>",
"tasks_completed": "<count .tasks/*.json>",
"summaries_generated": "<count .summaries/*.md>",
"review_metrics": {
"dimensions_analyzed": "<count .review/dimensions/*.json>",
"total_findings": "<sum from dimension JSONs>"
}
},
"tags": ["<3-5 keywords from IMPL_PLAN.md>"],
"lessons": {
"successes": ["<key wins>"],
"challenges": ["<difficulties>"],
"watch_patterns": ["<patterns to monitor>"]
}
}
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.
- yesterday First seen · 140 lines · 20 tokens per session scan A 2ac0dc5a3658
complete is a command published in the GitHub repository catlog22/Claude-Code-Workflow (2,135 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 1,116 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 2026-08-30.
Other commands, from other repositories
kaizen
Session-end continuous-improvement capture for Untether. Record 0-3 evidence-linked process-learnings as bullets on the permanent [kaizen] GitHub collector issue. Read-only except ONE gh issue comment. Zero captures is a valid outcome. Self-invokes at session end; propose-only downstream via /kaizen-review.
remember
Explicitly save something to memory as an experience.
crossframe-teach
Use CrossFrame Teach to explain CrossFrame concepts in plain Chinese.
revise-claude-md
이번 세션에서 학습한 사실을 Hames 라우팅 매트릭스에 따라 적절한 모듈/워크스페이스 CLAUDE.md 에 반영.
bmad-correct-course
Assess the impact of a significant change during sprint execution across the PRD, epics, architecture, and UX documents, and produce a sprint change proposal. Use when the user says "correct course" or "propose sprint change".
bmad-agent-builder
Builds, edits or analyzes Agent Skills through conversational discovery. Use when the user requests to "Create an Agent", "Analyze an Agent" or "Edit an Agent".