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/next-taskgit 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 | $0.00424 |
| Opus 5 | $0.00000 | $0.00212 |
| Sonnet 5 | $0.00000 | $0.00085 |
| Haiku 4.5 | $0.00000 | $0.00042 |
Grade A, and why
next-task 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
95% identical to next-task — 5 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
Next Task
Arguments: $ARGUMENTS Intelligently determine and prepare the next action based on comprehensive context.
This enhanced version of 'next' considers:
- Current task states
- Recent activity
- Time constraints
- Dependencies
- Your working patterns
Arguments: $ARGUMENTS
Intelligent Next Action
1. Context Gathering
Let me analyze the current situation:
- Active tasks (in-progress)
- Recently completed tasks
- Blocked tasks
- Time since last activity
- Arguments provided: $ARGUMENTS
2. Smart Decision Tree
If you have an in-progress task:
- Has it been idle > 2 hours? → Suggest resuming or switching
- Near completion? → Show remaining steps
- Blocked? → Find alternative task
If no in-progress tasks:
- Unblocked high-priority tasks? → Start highest
- Complex tasks need breakdown? → Suggest expansion
- All tasks blocked? → Show dependency resolution
Special arguments handling:
- "quick" → Find task < 2 hours
- "easy" → Find low complexity task
- "important" → Find high priority regardless of complexity
- "continue" → Resume last worked task
3. Preparation Workflow
Based on selected task:
- Show full context and history
- Set up development environment
- Run relevant tests
- Open related files
- Show similar completed tasks
- Estimate completion time
4. Alternative Suggestions
Always provide options:
- Primary recommendation
- Quick alternative (< 1 hour)
- Strategic option (unblocks most tasks)
- Learning option (new technology/skill)
5. Workflow Integration
Seamlessly connect to:
/project:task-master:start [selected]/project:workflows:auto-implement/project:task-master:expand(if complex)/project:utils:complexity-report(if unsure)
The goal: Zero friction from decision to implementation.
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 · 69 lines · 0 tokens per session scan A 837aa31bb36b
next-task 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 424 tokens. A static security scan graded it A with 0 findings. It is 95% identical to next-task, differing in 5 lines, and is treated as a copy.
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.
constitution
Create or update the project constitution from interactive or provided principle inputs.
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.