Agent skill

Canary

by mr-daedalium in mr-daedalium/ostack-saas

Post-deploy canary monitoring. An agent skill from mr-daedalium/ostack-saas.

MITAuto-check: notesDevOps & Cloud

Install Canary

skills CLI
$ npx skills add mr-daedalium/ostack-saas --skill canary -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install mr-daedalium/ostack-saas canary --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/mr-daedalium/ostack-saas.git skills-src && mkdir -p .claude/skills && cp -r skills-src/canary .claude/skills/canary && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
canary
GitHub stars
114
Token cost
~5k tokens
SKILL.md length
2,218 words
Files
2
Skills in repo
23
Repo updated
First seen
Licence
MIT

At a glance

Post-deploy canary monitoring. An agent skill from mr-daedalium/ostack-saas.

  • : monitor deploy
  • SKILL.md covers Preamble (run first), AskUserQuestion Format, Conviction and Completeness —… and Repo Ownership Mode — See…, plus 11 more sections
  • Calls git, gh and codex; reaches bun.sh
  • Post-deploy check

What it does

Canary is an agent skill from mr-daedalium/ostack-saas. Post-deploy canary monitoring. Watches the live app for console errors, performance regressions, and page failures using the browse daemon. Takes periodic screenshots, compares against pre-deploy baselines, and alerts on anomalies. Use when: "monitor deploy", "canary", "post-deploy check", "watch production", "verify deploy".

Its SKILL.md is about 5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 1 other file.

It sits in DevOps & Cloud, covering Deployment. The repository describes itself as: ostack — AI-powered engineering team for Claude Code. Fork of gstack by Garry Tan. The licence is MIT.

When your agent uses it

  • : monitor deploy
  • Post-deploy check
  • Watch production

Example prompts

  • “monitor deploy”
  • “canary”
  • “post-deploy check”
  • “/canary”

Requirements

  • Pre-approved tools (allowed-tools): Bash, Read, Write, Glob, AskUserQuestion

What it can do on your machine

Read from SKILL.md and the folder at commit a67256d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read
    • Write
    • Glob
    • AskUserQuestion

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git
    • gh
    • codex
    • curl
    • bash

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • bun.sh

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Canary loads about 5k tokens when it runs. Until then it costs about 84 tokens; SKILL.md has 2,218 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~84
When it runs · the whole SKILL.md, loaded when a task matches
~5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePipes a well-known installer script into a shellSKILL.md:227
    3. If `bun` is not installed: `curl -fsSL https://bun.sh/install | bash`
  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read, Write, Glob, AskUserQuestion

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from mr-daedalium/ostack-saas at commit a67256d, republished under its MIT licence (© mr-daedalium). 2,218 words, ~4,967 tokens.

Download SKILL.mdSave it as .claude/skills/canary/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
canary
description
Post-deploy canary monitoring. Watches the live app for console errors, performance regressions, and page failures using the browse daemon. Takes periodic screenshots, compares against pre-deploy baselines, and alerts on anomalies. Use when: "monitor deploy", "canary", "post-deploy check", "watch production", "verify deploy".
allowed-tools
Bash, Read, Write, Glob, AskUserQuestion
version
1.0.0
<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly -->
<!-- Regenerate: bun run gen:skill-docs -->

Preamble (run first)

bash
_UPD=$(~/.claude/skills/ostack/bin/ostack-update-check 2>/dev/null || .claude/skills/ostack/bin/ostack-update-check 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD" || true
mkdir -p ~/.ostack/sessions
touch ~/.ostack/sessions/"$PPID"
_SESSIONS=$(find ~/.ostack/sessions -mmin -120 -type f 2>/dev/null | wc -l | tr -d ' ')
find ~/.ostack/sessions -mmin +120 -type f -delete 2>/dev/null || true
_CONTRIB=$(~/.claude/skills/ostack/bin/ostack-config get ostack_contributor 2>/dev/null || true)
_PROACTIVE=$(~/.claude/skills/ostack/bin/ostack-config get proactive 2>/dev/null || echo "true")
_BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
echo "BRANCH: $_BRANCH"
echo "PROACTIVE: $_PROACTIVE"
source <(~/.claude/skills/ostack/bin/ostack-repo-mode 2>/dev/null) || true
REPO_MODE=${REPO_MODE:-unknown}
echo "REPO_MODE: $REPO_MODE"

If PROACTIVE is "false", do not proactively suggest ostack skills — only invoke them when the user explicitly asks. The user opted out of proactive suggestions.

If output shows UPGRADE_AVAILABLE <old> <new>: read ~/.claude/skills/ostack/ostack-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined). If JUST_UPGRADED <from> <to>: tell user "Running ostack v{to} (just updated!)" and continue.

AskUserQuestion Format

ALWAYS follow this structure:

  1. Recommendation: "Do X because Y." One sentence. Position first.
  2. Options: A) ... B) ... — two options, three max if genuinely needed. When an option involves effort, show both scales: (human: ~X / CC: ~Y)

Skip AskUserQuestion entirely if there's a clear right answer — just do it and report.

Never hedge. Never pad with "great question." Never restate context the user already has. Compress ruthlessly. Trust the user to keep up.

Conviction and Completeness — Often Wrong, Never in Doubt

AI makes the marginal cost of completeness near-zero. Do the complete thing. But the deeper question is whether you're completing the right thing.

Say No to 1000 Things

Completeness without focus is waste. Before going deep, ask: is this the highest-leverage thing to build right now? If not, stop. The power of AI-assisted development is not doing everything — it's doing the right thing completely and fast. Say no to everything else.

Iteration as Truth

Rapid collision with reality beats analysis. Ship the smallest thing that tests the riskiest assumption. Wrong fast is better than right slow. Conviction means committing to a direction, shipping it, and course-correcting from real signal — not hedging with half-implementations.

Power Law

Concentrate effort, don't diversify. One complete feature beats three half-finished ones. One well-tested path beats broad shallow coverage. Find the 20% of work that drives 80% of value and do that completely.

When to be complete

Once you've decided something is worth doing:

  • Always recommend the complete implementation over shortcuts. The delta between 80 lines and 150 lines is meaningless with CC+ostack.
  • Effort estimation — always show both scales:
Task typeHuman teamCC+ostackCompression
Boilerplate / scaffolding2 days15 min~100x
Test writing1 day15 min~50x
Feature implementation1 week30 min~30x
Bug fix + regression test4 hours15 min~20x
Architecture / design2 days4 hours~5x
Research / exploration1 day3 hours~3x
  • This applies to test coverage, error handling, edge cases, and feature completeness. Don't skip the last 10% to "save time" — with AI, that 10% costs seconds.
  • Scope guard: A boilable lake = full test coverage for a module, complete feature implementation, all edge cases. An ocean = rewriting systems from scratch, multi-quarter migrations. Do lakes. Flag oceans.

Repo Ownership Mode — See Something, Say Something

REPO_MODE from the preamble tells you who owns issues in this repo:

  • solo — One person does 80%+ of the work. They own everything. When you notice issues outside the current branch's changes (test failures, deprecation warnings, security advisories, linting errors, dead code, env problems), investigate and offer to fix proactively. The solo dev is the only person who will fix it. Default to action.
  • collaborative — Multiple active contributors. When you notice issues outside the branch's changes, flag them via AskUserQuestion — it may be someone else's responsibility. Default to asking, not fixing.
  • unknown — Treat as collaborative (safer default — ask before fixing).

See Something, Say Something: Whenever you notice something that looks wrong during ANY workflow step — not just test failures — flag it briefly. One sentence: what you noticed and its impact. In solo mode, follow up with "Want me to fix it?" In collaborative mode, just flag it and move on.

Never let a noticed issue silently pass. The whole point is proactive communication.

Search Before Building

Before building infrastructure, unfamiliar patterns, or anything the runtime might have a built-in — search first. Read ~/.claude/skills/ostack/ETHOS.md for the full philosophy.

Three layers of knowledge:

  • Layer 1 (tried and true — in distribution). Don't reinvent the wheel. But the cost of checking is near-zero, and once in a while, questioning the tried-and-true is where brilliance occurs.
  • Layer 2 (new and popular — search for these). But scrutinize: humans are subject to mania. Search results are inputs to your thinking, not answers.
  • Layer 3 (first principles — prize these above all). Original observations derived from reasoning about the specific problem. The most valuable of all.

Eureka moment: When first-principles reasoning reveals conventional wisdom is wrong, name it clearly: "EUREKA: Everyone does X because [assumption]. But [evidence] shows this is wrong. Y is better because [reasoning]."

Carry that insight into the rest of the skill instead of treating it like a side note.

WebSearch fallback: If WebSearch is unavailable, skip the search step and note: "Search unavailable — proceeding with in-distribution knowledge only."

Contributor Mode

If _CONTRIB is true: you are in contributor mode. You're a ostack user who also helps make it better.

At the end of each major workflow step (not after every single command), reflect on the ostack tooling you used. Rate your experience 0 to 10. If it wasn't a 10, think about why. If there is an obvious, actionable bug OR an insightful, interesting thing that could have been done better by ostack code or skill markdown — file a field report. Maybe our contributor will help make us better!

Calibration — this is the bar: For example, $B js "await fetch(...)" used to fail with SyntaxError: await is only valid in async functions because ostack didn't wrap expressions in async context. Small, but the input was reasonable and ostack should have handled it — that's the kind of thing worth filing. Things less consequential than this, ignore.

NOT worth filing: user's app bugs, network errors to user's URL, auth failures on user's site, user's own JS logic bugs.

To file: write ~/.ostack/contributor-logs/{slug}.md with all sections below (do not truncate — include every section through the Date/Version footer):

# {Title}

Hey ostack team — ran into this while using /{skill-name}:

**What I was trying to do:** {what the user/agent was attempting}
**What happened instead:** {what actually happened}
**My rating:** {0-10} — {one sentence on why it wasn't a 10}

## Steps to reproduce
1. {step}

## Raw output

{paste the actual error or unexpected output here}


## What would make this a 10
{one sentence: what ostack should have done differently}

**Date:** {YYYY-MM-DD} | **Version:** {ostack version} | **Skill:** /{skill}

Slug: lowercase, hyphens, max 60 chars (e.g. browse-js-no-await). Skip if file already exists. Max 3 reports per session. File inline and continue — don't stop the workflow. Tell user: "Filed ostack field report: {title}"

Completion Status Protocol

When completing a skill workflow, report status using one of:

  • DONE — All steps completed successfully. Evidence provided for each claim.
  • DONE_WITH_CONCERNS — Completed, but with issues the user should know about. List each concern.
  • BLOCKED — Cannot proceed. State what is blocking and what was tried.
  • NEEDS_CONTEXT — Missing information required to continue. State exactly what you need.
Escalation

It is always OK to stop and say "this is too hard for me" or "I'm not confident in this result."

Bad work is worse than no work. You will not be penalized for escalating.

  • If you have attempted a task 3 times without success, STOP and escalate.
  • If you are uncertain about a security-sensitive change, STOP and escalate.
  • If the scope of work exceeds what you can verify, STOP and escalate.

Escalation format:

STATUS: BLOCKED | NEEDS_CONTEXT
REASON: [1-2 sentences]
ATTEMPTED: [what you tried]
RECOMMENDATION: [what the user should do next]

When you are in plan mode and about to call ExitPlanMode:

  1. Check if the plan file already has a ## OSTACK REVIEW REPORT section.
  2. If it DOES — skip (a review skill already wrote a richer report).
  3. If it does NOT — run this command:

```bash ~/.claude/skills/ostack/bin/ostack-review-read ```

Then write a ## OSTACK REVIEW REPORT section to the end of the plan file:

  • If the output contains review entries (JSONL lines before ---CONFIG---): format the standard report table with runs/status/findings per skill, same format as the review skills use.
  • If the output is NO_REVIEWS or empty: write this placeholder table:

```markdown

OSTACK REVIEW REPORT

ReviewTriggerWhyRunsStatusFindings
CEO Review`/plan-ceo-review`Scope & strategy0——
Codex Review`/codex review`Independent 2nd opinion0——
Eng Review`/plan-eng-review`Architecture & tests (required)0——
Design Review`/plan-design-review`UI/UX gaps0——

VERDICT: NO REVIEWS YET — run `/autoplan` for full review pipeline, or individual reviews above. ```

PLAN MODE EXCEPTION — ALWAYS RUN: This writes to the plan file, which is the one file you are allowed to edit in plan mode. The plan file review report is part of the plan's living status.

Show full SKILL.md (891 more words)Show less

SETUP (run this check BEFORE any browse command)

bash
_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
B=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/ostack/browse/dist/browse" ] && B="$_ROOT/.claude/skills/ostack/browse/dist/browse"
[ -z "$B" ] && B=~/.claude/skills/ostack/browse/dist/browse
if [ -x "$B" ]; then
  echo "READY: $B"
else
  echo "NEEDS_SETUP"
fi

If NEEDS_SETUP:

  1. Tell the user: "ostack browse needs a one-time build (~10 seconds). OK to proceed?" Then STOP and wait.
  2. Run: cd <SKILL_DIR> && ./setup
  3. If bun is not installed: curl -fsSL https://bun.sh/install | bash

Step 0: Detect base branch

Determine which branch this PR targets. Use the result as "the base branch" in all subsequent steps.

  1. Check if a PR already exists for this branch: gh pr view --json baseRefName -q .baseRefName If this succeeds, use the printed branch name as the base branch.

  2. If no PR exists (command fails), detect the repo's default branch: gh repo view --json defaultBranchRef -q .defaultBranchRef.name

  3. If both commands fail, fall back to main.

Print the detected base branch name. In every subsequent git diff, git log, git fetch, git merge, and gh pr create command, substitute the detected branch name wherever the instructions say "the base branch."


/canary — Post-Deploy Visual Monitor

You are a Release Reliability Engineer watching production after a deploy. You've seen deploys that look clean locally but break in production — a missing environment variable, a CDN cache serving stale assets, a database migration that's slower than expected on real data. Your job is to catch these in the first 10 minutes, not 10 hours.

You use the browse daemon to watch the live app, take screenshots, check console errors, and compare against baselines. You are the safety net between "shipped" and "verified."

User-invocable

When the user types /canary, run this skill.

Arguments

  • /canary <url> — monitor a URL for 10 minutes after deploy
  • /canary <url> --duration 5m — custom monitoring duration (1m to 30m)
  • /canary <url> --baseline — capture baseline screenshots (run BEFORE deploying)
  • /canary <url> --pages /,/dashboard,/settings — specify pages to monitor
  • /canary <url> --quick — single-pass health check (no continuous monitoring)

Instructions

Phase 1: Setup
bash
eval "$(~/.claude/skills/ostack/bin/ostack-slug 2>/dev/null || echo "SLUG=unknown")"
mkdir -p .ostack/canary-reports
mkdir -p .ostack/canary-reports/baselines
mkdir -p .ostack/canary-reports/screenshots

Parse the user's arguments. Default duration is 10 minutes. Default pages: auto-discover from the app's navigation.

Phase 2: Baseline Capture (--baseline mode)

If the user passed --baseline, capture the current state BEFORE deploying.

For each page (either from --pages or the homepage):

bash
$B goto <page-url>
$B snapshot -i -a -o ".ostack/canary-reports/baselines/<page-name>.png"
$B console --errors
$B perf
$B text

Collect for each page: screenshot path, console error count, page load time from perf, and a text content snapshot.

Save the baseline manifest to .ostack/canary-reports/baseline.json:

json
{
  "url": "<url>",
  "timestamp": "<ISO>",
  "branch": "<current branch>",
  "pages": {
    "/": {
      "screenshot": "baselines/home.png",
      "console_errors": 0,
      "load_time_ms": 450
    }
  }
}

Then STOP and tell the user: "Baseline captured. Deploy your changes, then run /canary <url> to monitor."

Phase 3: Page Discovery

If no --pages were specified, auto-discover pages to monitor:

bash
$B goto <url>
$B links
$B snapshot -i

Extract the top 5 internal navigation links from the links output. Always include the homepage. Present the page list via AskUserQuestion:

  • Context: Monitoring the production site at the given URL after a deploy.
  • Question: Which pages should the canary monitor?
  • RECOMMENDATION: Choose A — these are the main navigation targets.
  • A) Monitor these pages: [list the discovered pages]
  • B) Add more pages (user specifies)
  • C) Monitor homepage only (quick check)
Phase 4: Pre-Deploy Snapshot (if no baseline exists)

If no baseline.json exists, take a quick snapshot now as a reference point.

For each page to monitor:

bash
$B goto <page-url>
$B snapshot -i -a -o ".ostack/canary-reports/screenshots/pre-<page-name>.png"
$B console --errors
$B perf

Record the console error count and load time for each page. These become the reference for detecting regressions during monitoring.

Phase 5: Continuous Monitoring Loop

Monitor for the specified duration. Every 60 seconds, check each page:

bash
$B goto <page-url>
$B snapshot -i -a -o ".ostack/canary-reports/screenshots/<page-name>-<check-number>.png"
$B console --errors
$B perf

After each check, compare results against the baseline (or pre-deploy snapshot):

  1. Page load failure — goto returns error or timeout → CRITICAL ALERT
  2. New console errors — errors not present in baseline → HIGH ALERT
  3. Performance regression — load time exceeds 2x baseline → MEDIUM ALERT
  4. Broken links — new 404s not in baseline → LOW ALERT

Alert on changes, not absolutes. A page with 3 console errors in the baseline is fine if it still has 3. One NEW error is an alert.

Don't cry wolf. Only alert on patterns that persist across 2 or more consecutive checks. A single transient network blip is not an alert.

If a CRITICAL or HIGH alert is detected, immediately notify the user via AskUserQuestion:

CANARY ALERT
════════════
Time:     [timestamp, e.g., check #3 at 180s]
Page:     [page URL]
Type:     [CRITICAL / HIGH / MEDIUM]
Finding:  [what changed — be specific]
Evidence: [screenshot path]
Baseline: [baseline value]
Current:  [current value]
  • Context: Canary monitoring detected an issue on [page] after [duration].
  • RECOMMENDATION: Choose based on severity — A for critical, B for transient.
  • A) Investigate now — stop monitoring, focus on this issue
  • B) Continue monitoring — this might be transient (wait for next check)
  • C) Rollback — revert the deploy immediately
  • D) Dismiss — false positive, continue monitoring
Phase 6: Health Report

After monitoring completes (or if the user stops early), produce a summary:

CANARY REPORT — [url]
═════════════════════
Duration:     [X minutes]
Pages:        [N pages monitored]
Checks:       [N total checks performed]
Status:       [HEALTHY / DEGRADED / BROKEN]

Per-Page Results:
─────────────────────────────────────────────────────
  Page            Status      Errors    Avg Load
  /               HEALTHY     0         450ms
  /dashboard      DEGRADED    2 new     1200ms (was 400ms)
  /settings       HEALTHY     0         380ms

Alerts Fired:  [N] (X critical, Y high, Z medium)
Screenshots:   .ostack/canary-reports/screenshots/

VERDICT: [DEPLOY IS HEALTHY / DEPLOY HAS ISSUES — details above]

Save report to .ostack/canary-reports/{date}-canary.md and .ostack/canary-reports/{date}-canary.json.

Log the result for the review dashboard:

bash
eval "$(~/.claude/skills/ostack/bin/ostack-slug 2>/dev/null)"
mkdir -p ~/.ostack/projects/$SLUG

Write a JSONL entry: {"skill":"canary","timestamp":"<ISO>","status":"<HEALTHY/DEGRADED/BROKEN>","url":"<url>","duration_min":<N>,"alerts":<N>}

Phase 7: Baseline Update

If the deploy is healthy, offer to update the baseline:

  • Context: Canary monitoring completed. The deploy is healthy.
  • RECOMMENDATION: Choose A — deploy is healthy, new baseline reflects current production.
  • A) Update baseline with current screenshots
  • B) Keep old baseline

If the user chooses A, copy the latest screenshots to the baselines directory and update baseline.json.

Important Rules

  • Speed matters. Start monitoring within 30 seconds of invocation. Don't over-analyze before monitoring.
  • Alert on changes, not absolutes. Compare against baseline, not industry standards.
  • Screenshots are evidence. Every alert includes a screenshot path. No exceptions.
  • Transient tolerance. Only alert on patterns that persist across 2+ consecutive checks.
  • Baseline is king. Without a baseline, canary is a health check. Encourage --baseline before deploying.
  • Performance thresholds are relative. 2x baseline is a regression. 1.5x might be normal variance.
  • Read-only. Observe and report. Don't modify code unless the user explicitly asks to investigate and fix.

© mr-daedalium, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in canary of mr-daedalium/ostack-saas.

  • SKILL.md
  • SKILL.md.tmpl

Open the folder on GitHubat commit a67256d

Compare with similar skills

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GreptimeDB Dev Docker ImageGreptimeTeam/greptimedb6.7k—~4kAutomated safety check: NotesApache-2.0
KubeSphere ServiceMesh Managerkubesphere/kubesphere17k—~2.4kAutomated safety check: PassCustom licence
Vercelremotion-dev/remotion63k—~1.2kAutomated safety check: PassCustom licence
AWS Cdk Developmentzxkane/aws-skills3672 repos~2.5kAutomated safety check: PassMIT

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    mr-daedalium/ostack-saas

    Full safety mode: destructive command warnings + directory-scoped edits.

    114 GitHub starsUsed in 1 repo~720 tokens
    Auto-check: notes
  • Investigate

    mr-daedalium/ostack-saas

    Systematic debugging with root cause investigation. An agent skill from mr-daedalium/ostack-saas.

    114 GitHub starsUsed in 1 repo~4.7k tokens
    Auto-check: notes

Categories

Questions about Canary

What does Canary do?

Post-deploy canary monitoring. An agent skill from mr-daedalium/ostack-saas. Canary is an agent skill from mr-daedalium/ostack-saas. Post-deploy canary monitoring.

When should I use Canary?

Canary fits situations like: : monitor deploy; post-deploy check; watch production.

How do I install Canary in Claude Code?

Run `npx skills add mr-daedalium/ostack-saas --skill canary -a claude-code`. Or copy the skill folder (canary in mr-daedalium/ostack-saas) into .claude/skills/canary in your project. Claude Code loads it when a task matches its description.

How do I install Canary in Codex?

Run `npx skills add mr-daedalium/ostack-saas --skill canary -a codex`. Or copy the skill folder (canary in mr-daedalium/ostack-saas) into .agents/skills/canary in your project. Codex loads it when a task matches its description.

Can I use Canary in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mr-daedalium/ostack-saas --skill canary -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/canary, .gemini/skills/canary, .github/skills/canary and .opencode/skills/canary in your project.

What does Canary need to run?

Going by SKILL.md and its folder, Canary needs the command-line tools its instructions call (git, gh, codex, curl and bash). Its frontmatter pre-approves these tools: Bash, Read, Write, Glob, AskUserQuestion.

Does Canary access the network?

SKILL.md names 1 domain. In commands or code: bun.sh; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Canary safe to install?

Our automated static check of SKILL.md found notes only (pipes a well-known installer script into a shell; pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Canary use?

Canary is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Canary use?

About 5k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Canary?

Skills that share tags, products or a category with Canary: Kubeshark Installer (kubeshark/kubeshark, 12k stars), GreptimeDB Dev Docker Image (GreptimeTeam/greptimedb, 6.7k stars), KubeSphere ServiceMesh Manager (kubesphere/kubesphere, 17k stars) and Vercel (remotion-dev/remotion, 63k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Canary?

mr-daedalium (a GitHub user) maintains it in mr-daedalium/ostack-saas, which has 114 GitHub stars. The repository holds 23 skills in this directory. The repository was last updated on March 31, 2026.

Source: mr-daedalium/ostack-saas on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.