QM is a shared work environment for coding agents that gives each employee and conversation an isolated workspace while allowing collaboration in Slack and on the web. Startups use it to run agents for individuals, teams, and company operations, with selectable harnesses and models. The catalogue entries extend QM with skills, instructions, and settings.
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 skills add yc-software/qm --skill sendgit clone --depth 1 https://github.com/yc-software/qmWrote 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/yc-software/qm/send)<a href="https://agentmods.dev/skills/yc-software/qm/send"><img src="https://agentmods.dev/badge/skills/yc-software/qm/send/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/yc-software/qm/send"><img src="https://agentmods.dev/badge/skills/yc-software/qm/send.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00025 | $0.01468 |
| Opus 5.5 | $0.00010 | $0.00587 |
| Sonnet 5.5 | $0.00005 | $0.00294 |
| Haiku 4.5 | $0.00003 | $0.00147 |
Grade A, and why
send 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.
How it starts
The opening of the file, as written. The whole thing — 118 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Babysit
Make a pull request for the change we just discussed, file it, babysit CI, fix any issues that come up, and merge once CI is fully green.
Steps
-
Make the PR. Commit the discussed change on a feature branch (create one off the default branch if currently on it). Push it.
-
File it. Open a pull request with a clear title and description covering why and what changed. Use
ghfor GitHub orglabfor GitLab. Detect from the remote. -
Wait for CI in one blocking process, with bounded transport retries. Load the
github-gitlabskill; it reports the directory holding its scripts. For GitHub, capture the PR's full head SHA and use its bundled helper, not baregh pr checks --watch:node <github-gitlab dir>/scripts/watch-ci.mjs --repo OWNER/REPO --pr NUMBER --head REVIEWED_HEAD_SHARun this with
execute, an explicitsandbox_id,background:true, and authorized credentials; subscribe withbackgroundactionwatchand the returnedprocess_id. Keep that sandbox ID throughout the checkout, checks, and push. Keep one watcher per PR; hand off if another agent already owns it. The helper polls internally, retries recognized transport/server errors with bounded backoff, and has a 30-minute overall deadline. Set the background lifetime longer than that. Do not wake the model repeatedly to report pending checks.Read the helper's JSON status, not just the exit code. Pending is not failure; TLS timeouts and connection resets are not logout or permission expiry. Failed checks, auth failures, rate limits, unknown errors, exhausted retries, and deadlines all remain nonzero. Keep
set -e; never mask failure with a success marker or merge. A changed head invalidates successful checks and reviews: restart both on the new SHA. Empty, skipped, or cancelled checks do not count as success.For GitLab, use
glab ci status --live; the GitHub helper does not cover it. Preserve its nonzero status and investigate failures before proceeding.
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 Changed · +2 lines 60b1741fe960
- 27d ago Changed · +1 lines 37e32af24e3d
- 29d ago First seen · 115 lines · 25 tokens per session scan A 81963e455806
send is a skill published in the GitHub repository yc-software/qm (15,434 stars, last pushed today), licensed MIT. It adds 25 tokens to every session and 1,468 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-18.
Other skills, from other repositories
release-creator
Cuts a new release of a software project or plugin, coordinating release configuration, version files, changelog, validation, and the fixed git/PR/tag/CI sequence. Not for: PHP package publication or ordinary commits. Output: a validated release preparation or publication result with the human merge gate preserved.
open-code-review
Performs AI-powered code review on Git changes using the ocr CLI from alibaba/open-code-review. Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches for code quality issues. Produces line-level review comments and can automatically apply…
deployment-patterns
Deployment workflows, CI/CD pipeline patterns, Docker containerization, health checks, rollback strategies, and production readiness checklists for web applications. Use when setting up deployment infrastructure or planning releases.
agent-github-modes
Agent skill for github-modes - invoke with $agent-github-modes.
baby-sit
Monitor a GitHub pull request until CI is green, diagnose failures, and rerun only evidence-backed flaky GitHub Actions jobs.
atmos-hooks
Atmos hooks: lifecycle events, hook kinds, command/store/git/security hooks, step/steps hooks, when: conditions, scoping and overrides, toolchain integration, --skip-hooks, and Atmos Pro/local output.