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/to-cancelledgit clone --depth 1 https://github.com/sakrut/ai-code-graphWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/sakrut/ai-code-graph/to-cancelled)<a href="https://agentmods.dev/commands/sakrut/ai-code-graph/to-cancelled"><img src="https://agentmods.dev/badge/commands/sakrut/ai-code-graph/to-cancelled.svg" alt="Measured on agentmods" height="20"></a>What 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 | $0.00251 |
| Opus 5 | $0.00000 | $0.00125 |
| Sonnet 5 | $0.00000 | $0.00050 |
| Haiku 4.5 | $0.00000 | $0.00025 |
Grade A, and why
to-cancelled 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 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.
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
94% identical to to-cancelled — 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
To Cancelled
Arguments: $ARGUMENTS Cancel a task permanently.
Arguments: $ARGUMENTS (task ID)
Cancelling a Task
This status indicates a task is no longer needed and won't be completed.
Valid Reasons for Cancellation
- Requirements changed
- Feature deprecated
- Duplicate of another task
- Strategic pivot
- Technical approach invalidated
Pre-Cancellation Checks
- Confirm no critical dependencies
- Check for partial implementation
- Verify cancellation rationale
- Document lessons learned
Execution
task-master set-status --id=$ARGUMENTS --status=cancelled
Cancellation Impact
When cancelling:
-
Dependency Updates
- Notify dependent tasks
- Update project scope
- Recalculate timelines
-
Clean-up Actions
- Remove related branches
- Archive any work done
- Update documentation
- Close related issues
-
Learning Capture
- Document why cancelled
- Note what was learned
- Update estimation models
- Prevent future duplicates
Historical Preservation
- Keep for reference
- Tag with cancellation reason
- Link to replacement if any
- Maintain audit trail
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 · 58 lines · 0 tokens per session scan A 3303d6840129
to-cancelled 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 251 tokens. A static security scan graded it A with 0 findings. It is 94% identical to to-cancelled, differing in 3 lines, and is treated as a copy.
Other commands, from other repositories
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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.
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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.