Content Freshness Signals
thedaviddias/Front-End-Checklist
Audits article pages for freshness signals, covering the Last-Modified header, Article JSON-LD dateModified and a visible last-updated date, and fixes mismatches.
Run one analytics task through several fresh trials to measure what repeats and what varies.
MITAuto-check passed
Install Reliability
$ npx skills add ai-analyst-lab/ai-analyst --skill reliability -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ai-analyst-lab/ai-analyst reliability --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/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/reliability .claude/skills/reliability && 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 "reliability" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/reliability into .claude/skills/reliability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reliability", 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/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/reliabilityType 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 ai-analyst-lab/ai-analyst --skill reliability -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ai-analyst-lab/ai-analyst reliability --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.claude/skills/reliability .agents/skills/reliability && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "reliability" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/reliability into .agents/skills/reliability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reliability", 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 ai-analyst-lab/ai-analyst --skill reliability -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ai-analyst-lab/ai-analyst reliability --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.claude/skills/reliability .cursor/skills/reliability && 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 "reliability" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/reliability into .cursor/skills/reliability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reliability", 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/ai-analyst-lab/ai-analyst.git --path .claude/skills/reliability--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 ai-analyst-lab/ai-analyst --skill reliability -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ai-analyst-lab/ai-analyst reliability --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.claude/skills/reliability .gemini/skills/reliability && 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 "reliability" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/reliability into .gemini/skills/reliability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reliability", 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 ai-analyst-lab/ai-analyst reliabilityInstalls 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 ai-analyst-lab/ai-analyst --skill reliability -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .github/skills && cp -r skills-src/.claude/skills/reliability .github/skills/reliability && 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 "reliability" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/reliability into .github/skills/reliability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reliability", 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 ai-analyst-lab/ai-analyst --skill reliability -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ai-analyst-lab/ai-analyst reliability --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ai-analyst-lab/ai-analyst.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.claude/skills/reliability .opencode/skills/reliability && 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 "reliability" agent skill from https://github.com/ai-analyst-lab/ai-analyst/tree/main/.claude/skills/reliability into .opencode/skills/reliability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "reliability", 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
reliability- GitHub stars
- 304
- Token cost
- ~929 tokens
- SKILL.md length
- 512 words
- Files
- 1
- Skills in repo
- 43
- Repo updated
- First seen
- Licence
- MIT
At a glance
Run one analytics task through several fresh trials to measure what repeats and what varies.
- Works in 7 steps: Record the task, model, active data,… → Use five fresh trials unless the user… → Preserve completed, failed, blocked,… → …
- Repeated-run requests
- SKILL.md covers What this answers, Run the evaluation and Report
- Calls python3
What it does
Reliability is an agent skill from ai-analyst-lab/ai-analyst. Run one analytics task through several fresh trials to measure what repeats and what varies. Use for reliability, repeatability, variance, or repeated-run requests. This measures stability, not correctness.
Its SKILL.md is about 930 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: AI Product Analyst — Claude Code-powered data analysis toolkit. The licence is MIT.
When your agent uses it
- Repeated-run requests
Example prompts
- “/reliability”
Requirements
- Python 3
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Record the task, model, active data, available tools, system fingerprint, and the tolerance that matters for the decision.
- Use five fresh trials unless the user chooses another count. The trials must not share answers.
- Preserve completed, failed, blocked, error, and unparseable trials separately.
- Save the raw output from every trial.
- Use the repository's deterministic reliability runner. It creates five independent workspaces, uses the active data source, preserves…
- Report exact agreement and agreement within the named tolerance separately.
- State what changed if this is a comparison with an earlier run.
What it can do on your machine
Read from SKILL.md and the folder at commit 52c0744. 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:
python3
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
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
Reliability loads about 929 tokens when it runs. Until then it costs about 55 tokens; SKILL.md has 512 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 ai-analyst-lab/ai-analyst at commit 52c0744, republished under its MIT licence (© ai-analyst-lab). 512 words, ~929 tokens.
Download SKILL.mdSave it as
.claude/skills/reliability/SKILL.md (or your agent's skills folder).- name
- reliability
- description
- Run one analytics task through several fresh trials to measure what repeats and what varies. Use for reliability, repeatability, variance, or repeated-run requests. This measures stability, not correctness.
Reliability
What this answers
Does this named system configuration behave consistently on this task?
It does not answer whether the result is correct. A wrong analysis can repeat perfectly.
Run the evaluation
- Record the task, model, active data, available tools, system fingerprint, and the tolerance that matters for the decision.
- Use five fresh trials unless the user chooses another count. The trials must not share answers.
- Preserve completed, failed, blocked, error, and unparseable trials separately.
- Save the raw output from every trial.
- Use the repository's deterministic reliability runner. It creates five independent workspaces, uses the active data source, preserves every result, and calculates the comparison.
- Report exact agreement and agreement within the named tolerance separately.
- State what changed if this is a comparison with an earlier run.
The deterministic CLI is available at python3 -m helpers.evals.cli run-reliability. Use it when the task can be executed noninteractively. For the standard run, explicitly pass --trials 5 --parallelism 5 --model claude-opus-4-6. Add --allow-code when the task requires a query. Do not lower parallelism preemptively or infer an account limit. Lower it only after the five-way run returns an actual concurrency or rate-limit error, and tell the user what failed before retrying.
Run the reliability command as one foreground task. Read its progress messages as trials finish. Do not create separate sleep commands or polling shells merely to wait for it.
The runner automatically gives each trial a clean view of the current analytical system. It excludes old outputs, test fixtures, future course examples, and inactive dataset packages. Connection credentials remain outside the workspace and are passed through the process environment. Do not ask the user to manage excluded paths or trial workspaces.
If the current system already contains a reviewed definition for the question, report that fact. Do not hide current context merely to manufacture variation.
Show full SKILL.md (202 more words)Show less
For a separate local context store, pass its path with --context-store. The runner saves a snapshot under the run's context-snapshot/ directory and installs the same contents in each trial. This does not change the project's active context configuration. Without an override, a configured source: path store is used automatically; legacy Git-cache mode must first be connected as a visible local path. Do not silently substitute local definitions if that source cannot be read.
Each trial is instructed to inspect the guide catalog and load relevant reviewed guides. Inspect trials/<number>/trace/context_loads_<analysis_id>.jsonl to see the full guide text loaded, and compare it with the query logs to check application. The snapshot proves which files were available, not that a guide was used. input-inventory.json records trial inputs and response.json preserves the response and captured tool events. Definition labels alone do not establish whether two attempts used the same calculation.
Report
Lead with:
- how many trials succeeded;
- every normalized result beside its raw form;
- exact agreement;
- tolerance-based agreement;
- what definitions or methods changed; and
- what the evidence does not establish.
If the trials vary, locate the source before proposing a fix. If one definition or context change is made, freeze everything else and rerun the same task.
© ai-analyst-lab, MIT. 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 .claude/skills/reliability of ai-analyst-lab/ai-analyst.
Open the folder on GitHubat commit 52c0744
Compare with similar skills
Reliability 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 |
|---|---|---|---|---|---|---|
| Reliability this skillai-analyst-lab/ai-analyst | 304 | — | ~929 | Automated safety check: Pass | MIT | |
| Content Freshness Signalsthedaviddias/Front-End-Checklist | 74k | — | ~741 | Automated safety check: Pass | MIT | |
| Google Cloud Waf Reliabilitydavila7/claude-code-templates | 32k | — | ~1.8k | Automated safety check: Pass | MIT | |
| Relsa Severity AssessmentK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~5.2k | Automated safety check: Notes | MIT | |
| Google Cloud Waf Reliabilitygoogle/skills | 21k | — | ~2k | Automated safety check: Pass | Apache-2.0 | |
| Gke Reliabilitygoogle/skills | 21k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 |
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Relsa Severity Assessment
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Questions about Reliability
What does Reliability do?
Run one analytics task through several fresh trials to measure what repeats and what varies. Reliability is an agent skill from ai-analyst-lab/ai-analyst. Run one analytics task through several fresh trials to measure what repeats and what varies.
When should I use Reliability?
Reliability fits situations like: repeated-run requests.
How do I install Reliability in Claude Code?
Run `npx skills add ai-analyst-lab/ai-analyst --skill reliability -a claude-code`. Or copy the skill folder (.claude/skills/reliability in ai-analyst-lab/ai-analyst) into .claude/skills/reliability in your project. Claude Code loads it when a task matches its description.
How do I install Reliability in Codex?
Run `npx skills add ai-analyst-lab/ai-analyst --skill reliability -a codex`. Or copy the skill folder (.claude/skills/reliability in ai-analyst-lab/ai-analyst) into .agents/skills/reliability in your project. Codex loads it when a task matches its description.
Can I use Reliability 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 ai-analyst-lab/ai-analyst --skill reliability -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/reliability, .gemini/skills/reliability, .github/skills/reliability and .opencode/skills/reliability in your project.
What does Reliability need to run?
Going by SKILL.md and its folder, Reliability needs the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Reliability access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Reliability 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 Reliability use?
Reliability 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 Reliability use?
About 929 tokens (SKILL.md is roughly 3.7k 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 Reliability?
Skills that share tags, products or a category with Reliability: Content Freshness Signals (thedaviddias/Front-End-Checklist, 74k stars), Google Cloud Waf Reliability (davila7/claude-code-templates, 32k stars), Relsa Severity Assessment (K-Dense-AI/scientific-agent-skills, 48k stars) and Google Cloud Waf Reliability (google/skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Reliability?
ai-analyst-lab (a GitHub organization) maintains it in ai-analyst-lab/ai-analyst, which has 304 GitHub stars. The repository holds 43 skills in this directory. The repository was last updated on September 30, 2026.
Source: ai-analyst-lab/ai-analyst on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.