Cherry Studio Regression Tests
CherryHQ/cherry-studio
Runs Cherry Studio's critical-path regression suite as deterministic Playwright E2E tests through a GitHub workflow on macOS and Windows runners.
Analyze static quality gate on-disk size changes, correlate with Confluence exception records and GitHub PRs by milestone
Install Quality Gate Size Analysis
$ npx skills add DataDog/datadog-agent --skill quality-gate-size-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install DataDog/datadog-agent quality-gate-size-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/DataDog/datadog-agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/quality-gate-size-analysis .claude/skills/quality-gate-size-analysis && rm -rf skills-srcUse ~/.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/
Install the "quality-gate-size-analysis" agent skill from https://github.com/DataDog/datadog-agent/tree/main/.agents/skills/quality-gate-size-analysis into .claude/skills/quality-gate-size-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quality-gate-size-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/DataDog/datadog-agent/tree/main/.agents/skills/quality-gate-size-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add DataDog/datadog-agent --skill quality-gate-size-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install DataDog/datadog-agent quality-gate-size-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/DataDog/datadog-agent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/quality-gate-size-analysis .agents/skills/quality-gate-size-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "quality-gate-size-analysis" agent skill from https://github.com/DataDog/datadog-agent/tree/main/.agents/skills/quality-gate-size-analysis into .agents/skills/quality-gate-size-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quality-gate-size-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add DataDog/datadog-agent --skill quality-gate-size-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install DataDog/datadog-agent quality-gate-size-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/DataDog/datadog-agent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/quality-gate-size-analysis .cursor/skills/quality-gate-size-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "quality-gate-size-analysis" agent skill from https://github.com/DataDog/datadog-agent/tree/main/.agents/skills/quality-gate-size-analysis into .cursor/skills/quality-gate-size-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quality-gate-size-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/DataDog/datadog-agent.git --path .agents/skills/quality-gate-size-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add DataDog/datadog-agent --skill quality-gate-size-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install DataDog/datadog-agent quality-gate-size-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/DataDog/datadog-agent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/quality-gate-size-analysis .gemini/skills/quality-gate-size-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "quality-gate-size-analysis" agent skill from https://github.com/DataDog/datadog-agent/tree/main/.agents/skills/quality-gate-size-analysis into .gemini/skills/quality-gate-size-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quality-gate-size-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install DataDog/datadog-agent quality-gate-size-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add DataDog/datadog-agent --skill quality-gate-size-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/DataDog/datadog-agent.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/quality-gate-size-analysis .github/skills/quality-gate-size-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "quality-gate-size-analysis" agent skill from https://github.com/DataDog/datadog-agent/tree/main/.agents/skills/quality-gate-size-analysis into .github/skills/quality-gate-size-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quality-gate-size-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add DataDog/datadog-agent --skill quality-gate-size-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install DataDog/datadog-agent quality-gate-size-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/DataDog/datadog-agent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/quality-gate-size-analysis .opencode/skills/quality-gate-size-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "quality-gate-size-analysis" agent skill from https://github.com/DataDog/datadog-agent/tree/main/.agents/skills/quality-gate-size-analysis into .opencode/skills/quality-gate-size-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "quality-gate-size-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
quality-gate-size-analysis- GitHub stars
- 3.8k
- Token cost
- ~1.5k tokens
- SKILL.md length
- 646 words
- Files
- 1
- Skills in repo
- 35
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Analyze static quality gate on-disk size changes, correlate with Confluence exception records and GitHub PRs by milestone
- Works in 5 steps: Query Datadog Metrics → Fetch Confluence Exception Records → Pull GitHub PR Data → …
- Tasks that involve Quality gates
- SKILL.md covers Step 1: Query Datadog Metrics, Step 2: Fetch Confluence…, Step 3: Pull GitHub PR Data and Step 4: Cross-Reference and…, plus 2 more sections
- Calls gh
What it does
Quality Gate Size Analysis is an agent skill from DataDog/datadog-agent, published by the product's own GitHub organization. Analyze static quality gate on-disk size changes, correlate with Confluence exception records and GitHub PRs by milestone
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Testing & QA, covering Quality gates and Project management. It works with Confluence, Datadog and GitHub. The repository describes itself as: Main repository for Datadog Agent. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Quality gates
- Tasks that involve Project management
Example prompts
- “/quality-gate-size-analysis”
Requirements
- Docker
Workflow steps
5 steps, taken from the step headings in SKILL.md.
What it can do on your machine
Read from SKILL.md and the folder at commit 20eff25. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
gh
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use gh, which can reach the network depending on how they are called.
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
Quality Gate Size Analysis loads about 1.5k tokens when it runs. Until then it costs about 37 tokens; SKILL.md has 646 words of instructions outside code blocks.
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 passed
The automated check found no risky patterns in SKILL.md.
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 DataDog/datadog-agent at commit 20eff25, republished under its Apache-2.0 licence (© DataDog). 646 words, ~1,544 tokens.
Download SKILL.mdSave it as
.claude/skills/quality-gate-size-analysis/SKILL.md (or your agent's skills folder).- name
- quality-gate-size-analysis
- description
- Analyze static quality gate on-disk size changes, correlate with Confluence exception records and GitHub PRs by milestone
- argument-hint
- <time-range e.g. 3mo, 6mo> [optional: specific release e.g. 7.77]
- model
- sonnet
Analyze the agent's static quality gate on-disk size metrics, pull approved exception records from Confluence, fetch PR data from GitHub with milestone-based release attribution, and produce a cross-referenced report.
Step 1: Query Datadog Metrics
1a. Relative on-disk size (per-commit deltas)
Query datadog.agent.static_quality_gate.relative_on_disk_size filtered to ci_commit_ref_slug:main, grouped by gate_name and arch:
max:datadog.agent.static_quality_gate.relative_on_disk_size{ci_commit_ref_slug:main} by {gate_name,arch}- Use
from=now-$TIME_RANGEandto=now - Request
raw_data=trueto get CSV with timestamps for spike identification - Identify the largest single-commit jumps per gate — these are the candidates for exception correlation
1b. Absolute package size (branch comparison)
Query datadog.agent.package.size for main and relevant release branches to measure inter-release deltas:
max:datadog.agent.package.size{git_ref:main,package:datadog-agent,os:debian,arch:amd64}
max:datadog.agent.package.size{git_ref:7-XX-x,package:datadog-agent,os:debian,arch:amd64}- Compare the stable average of each release branch to quantify the bump
- Include both the prior release and the current release branches
1c. Other useful metrics
datadog.agent.static_quality_gate.on_disk_size— absolute on-disk size per gatedatadog.agent.static_quality_gate.on_wire_size— compressed/network sizedatadog.agent.static_quality_gate.max_allowed_on_disk_size— configured thresholds
1d. Reference dashboard
The Agent Package size metrics dashboard contains all relevant widgets.
Step 2: Fetch Confluence Exception Records
Exception records live in the ABLD Confluence space under folder ID 5996904656.
2a. Enumerate all exception pages
Use CQL search:
ancestor = 5996904656 AND type = page ORDER BY created DESCcloudId:datadoghq.atlassian.net- Exclude the
[TEMPLATE]page from results
2b. Fetch each page body
For every page returned, call getConfluencePage with contentFormat=markdown to extract:
- Decision status: Approved / Pending / Declined
- Disk size increase: the number in the "Measures" or "Bounds Granted" row
- Scope: which platforms/packages are affected
- Linked PRs: PR numbers/URLs mentioned in the "Feature" or "PR" rows
- Requester: who filed the exception
- Expiry / Payback: any commitments to recover the size
2c. Build an exception table
Compile all exceptions into a structured table with columns: Title, Date, Decision, Disk Increase, Scope, PRs, Requester.
Step 3: Pull GitHub PR Data
3a. Find PRs linked from Confluence
Extract PR numbers from the Confluence pages (they appear as GitHub URLs in the exception text). For each PR:
gh pr view <NUMBER> --repo DataDog/datadog-agent --json number,title,mergedAt,milestone,labels,stateThe milestone field (e.g. 7.77.0) determines which release the PR belongs to. Do NOT use labels for release attribution.
3b. Search for additional size-impacting PRs
Search for PRs merged in the time window that may have size impact but no exception:
gh pr list --repo DataDog/datadog-agent --base main --state merged \
--search "merged:>=YYYY-MM-DD" --json number,title,mergedAt,milestone,labelsFilter for PRs with labels like qa/rc-required, component/system-probe, etc., and cross-check against the exception list.
3c. Search by feature name
For exceptions that don't directly link a PR, search by keyword:
gh pr list --repo DataDog/datadog-agent --base main --state merged \
--search "<feature-keyword> merged:>=YYYY-MM-DD" --json number,title,mergedAt,milestoneStep 4: Cross-Reference and Correlate
Show full SKILL.md (274 more words)Show less
4a. Match metric spikes to PRs
For each significant spike in relative_on_disk_size:
- Identify the approximate date from the metric timestamp
- Find PRs merged on or just before that date
- Check if those PRs are covered by a Confluence exception
4b. Match PRs to releases via milestone
Group all size-impacting PRs by their milestone (not by label or merge date):
milestone:7.75.0→ Release 7.75milestone:7.76.0→ Release 7.76- etc.
4c. Identify gaps
Flag:
- PRs with size impact but no Confluence exception
- Confluence exceptions still in Pending status
- Exceptions with empty "Bounds Granted" fields
- PRs with no milestone set
Step 5: Generate Report
Write a markdown report to the repository root (e.g. quality_gate_size_analysis_YYYYQN.md) with these sections:
- Executive Summary — one paragraph overview
- Metrics Overview — absolute sizes per release branch, largest jumps table
- Confluence Exceptions — full table split by Approved vs Pending
- Release Attribution — PRs grouped by milestone, each linked to its exception status
- Coverage Gaps — list of unmatched PRs or pending exceptions
- Methodology — brief description of data sources and correlation approach
Key Details and Pitfalls
- The
relative_on_disk_sizemetric usesci_commit_ref_slug(notgit_ref) for branch filtering. - The
package.sizemetric usesgit_reffor branch filtering — branch names use hyphens (e.g.7-77-x). - The Confluence folder
5996904656is a folder, not a page — use CQLancestor =to search, notgetConfluencePageDescendants. - PR milestones determine release attribution, not labels. Use
gh pr view --json milestone. - The
gate_nametag values look likestatic_quality_gate_docker_agent_amd64— use these to distinguish between agent variants (docker, MSI, DCA, dogstatsd, IoT, heroku, FIPS). - Some exceptions cover multiple PRs across multiple releases (e.g. PAR landed in 7.76, with follow-on work in 7.77 and 7.78).
© DataDog, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in .agents/skills/quality-gate-size-analysis of DataDog/datadog-agent.
Open the folder on GitHubat commit 20eff25
Compare with similar skills
Quality Gate Size Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Quality Gate Size Analysis this skillDataDog/datadog-agent | 3.8k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 | |
| Cherry Studio Regression TestsCherryHQ/cherry-studio | 52k | — | ~1.2k | Automated safety check: Pass | AGPL-3.0 | |
| Release Lambda LayerDataDog/datadog-lambda-js | 126 | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | |
| Tool ConnectorZhixiangLuo/10xProductivity | 478 | — | ~925 | Automated safety check: Pass | MIT | |
| lo2cin4bt Acceptance Reviewlo2cin4/lo2cin4bt | 288 | — | ~1.4k | Automated safety check: Pass | Custom licence | |
| Endgamemicrosoft/copilot-for-eclipse | 126 | — | ~1.4k | Automated safety check: Pass | MIT |
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Questions about Quality Gate Size Analysis
What does Quality Gate Size Analysis do?
Analyze static quality gate on-disk size changes, correlate with Confluence exception records and GitHub PRs by milestone. Quality Gate Size Analysis is an agent skill from DataDog/datadog-agent, published by the product's own GitHub organization.
When should I use Quality Gate Size Analysis?
Quality Gate Size Analysis fits situations like: tasks that involve Quality gates; tasks that involve Project management.
How do I install Quality Gate Size Analysis in Claude Code?
Run `npx skills add DataDog/datadog-agent --skill quality-gate-size-analysis -a claude-code`. Or copy the skill folder (.agents/skills/quality-gate-size-analysis in DataDog/datadog-agent) into .claude/skills/quality-gate-size-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Quality Gate Size Analysis in Codex?
Run `npx skills add DataDog/datadog-agent --skill quality-gate-size-analysis -a codex`. Or copy the skill folder (.agents/skills/quality-gate-size-analysis in DataDog/datadog-agent) into .agents/skills/quality-gate-size-analysis in your project. Codex loads it when a task matches its description.
Can I use Quality Gate Size Analysis 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 DataDog/datadog-agent --skill quality-gate-size-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/quality-gate-size-analysis, .gemini/skills/quality-gate-size-analysis, .github/skills/quality-gate-size-analysis and .opencode/skills/quality-gate-size-analysis in your project.
What does Quality Gate Size Analysis need to run?
Going by SKILL.md and its folder, Quality Gate Size Analysis needs the command-line tools its instructions call (gh). Our summary lists: Docker.
Does Quality Gate Size Analysis access the network?
SKILL.md contains no URLs. Its commands use gh, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is Quality Gate Size Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Quality Gate Size Analysis use?
Quality Gate Size Analysis is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Quality Gate Size Analysis use?
About 1.5k tokens (SKILL.md is roughly 6.2k 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 Quality Gate Size Analysis?
Skills that share tags, products or a category with Quality Gate Size Analysis: Cherry Studio Regression Tests (CherryHQ/cherry-studio, 52k stars), Release Lambda Layer (DataDog/datadog-lambda-js, 126 stars), Tool Connector (ZhixiangLuo/10xProductivity, 478 stars) and lo2cin4bt Acceptance Review (lo2cin4/lo2cin4bt, 288 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Quality Gate Size Analysis?
DataDog (a GitHub organization, an official publisher) maintains it in DataDog/datadog-agent, which has 3,757 GitHub stars. The repository holds 35 skills in this directory. The repository was last updated on October 8, 2026.
Source: DataDog/datadog-agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.