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 skills/dcc-mcp/dcc-mcp-core/cancellable-loopnpx skills add dcc-mcp/dcc-mcp-core --skill cancellable-loopgit clone --depth 1 https://github.com/dcc-mcp/dcc-mcp-coreWrote 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/skills/dcc-mcp/dcc-mcp-core/cancellable-loop)<a href="https://agentmods.dev/skills/dcc-mcp/dcc-mcp-core/cancellable-loop"><img src="https://agentmods.dev/badge/skills/dcc-mcp/dcc-mcp-core/cancellable-loop.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 5.1 | $0.00045 | $0.00454 |
| Opus 5 | $0.00023 | $0.00227 |
| Sonnet 5 | $0.00009 | $0.00091 |
| Haiku 4.5 | $0.00005 | $0.00045 |
Grade A, and why
cancellable-loop 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 5d 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
Cancellable Loop
A minimal example that shows how to write a skill script that honours
notifications/cancelled from the MCP client.
The pattern is simple: call check_cancelled() at the top of every
iteration of a long-running loop. When the dispatcher installs a
CancelToken and the client cancels the request, check_cancelled()
raises CancelledError and the script unwinds cleanly. Outside of a
request context (REPL, unit tests) check_cancelled() is a no-op, so
the same script remains easy to run in isolation.
Tools
cancellable_loop__count— Iterateiterationstimes, sleepingsleep_msmilliseconds per step, checking for cancellation each iteration.
Example
{"name": "cancellable_loop__count", "arguments": {"iterations": 100, "sleep_ms": 50}}
# → {"success": true, "message": "Completed 100 iterations", "context": {"iterations": 100}}
If the client sends notifications/cancelled while the loop is
running, the next check_cancelled() call raises CancelledError and
the @skill_entry wrapper converts it into a standard error dict.
Related
dcc_mcp_core.check_cancelled— the API this skill demonstrates.- Issue #329 — cooperative cancellation checkpoints.
- Issue #318 — async dispatcher integration (wires the CancelToken).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 53 lines · 45 tokens per session scan A d7d8a5217ab0
cancellable-loop is a skill published in the GitHub repository dcc-mcp/dcc-mcp-core (42 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 454 once invoked, about $0.0002 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.
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