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/sakrut/ai-code-graph/smart-workflowgit clone --depth 1 https://github.com/sakrut/ai-code-graphWhat 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 | $0.00000 | $0.00316 |
| Opus 5 | $0.00000 | $0.00158 |
| Sonnet 5 | $0.00000 | $0.00063 |
| Haiku 4.5 | $0.00000 | $0.00032 |
Grade A, and why
smart-workflow 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.
This is a copy
98% identical to smart-workflow — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Smart Workflow
Arguments: $ARGUMENTS Execute an intelligent workflow based on current project state and recent commands.
This command analyzes:
- Recent commands you've run
- Current project state
- Time of day / day of week
- Your working patterns
Arguments: $ARGUMENTS
Intelligent Workflow Selection
Based on context, I'll determine the best workflow:
Context Analysis
- Previous command executed
- Current task states
- Unfinished work from last session
- Your typical patterns
Smart Execution
If last command was:
status→ Likely starting work → Run daily standupcomplete→ Task finished → Find next tasklist pending→ Planning → Suggest sprint planningexpand→ Breaking down work → Show complexity analysisinit→ New project → Show onboarding workflow
If no recent commands:
- Morning? → Daily standup workflow
- Many pending tasks? → Sprint planning
- Tasks blocked? → Dependency resolution
- Friday? → Weekly review
Workflow Composition
I'll chain appropriate commands:
- Analyze current state
- Execute primary workflow
- Suggest follow-up actions
- Prepare environment for coding
Learning Mode
This command learns from your patterns:
- Track command sequences
- Note time preferences
- Remember common workflows
- Adapt to your style
Example flows detected:
- Morning: standup → next → start
- After lunch: status → continue task
- End of day: complete → commit → status
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 · 58 lines · 0 tokens per session scan A ddfe64fc34e5
smart-workflow is a command published in the GitHub repository sakrut/ai-code-graph (3 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 316 tokens. A static security scan graded it A with 0 findings. It is 98% identical to smart-workflow, differing in 3 lines, and is treated as a copy.
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