LLM Benchmarking with lm-evaluation-harness
Orchestra-Research/AI-Research-SKILLs
Runs lm-evaluation-harness to benchmark language models on academic suites such as MMLU, GSM8K and HumanEval, compare models and track training checkpoints.
A skill your agent uses when you want guided bottom-up error analysis, structured failure taxonomy discovery, or comprehensive trace coding before documenting eval criteria.
Install Evals Specify
$ npx skills add tikalk/adlc-team-skills --skill evals-specify -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install tikalk/adlc-team-skills evals-specify --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/tikalk/adlc-team-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/evals/evals-specify .claude/skills/evals-specify && 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 "evals-specify" agent skill from https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-specify into .claude/skills/evals-specify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "evals-specify", 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/tikalk/adlc-team-skills/tree/main/skills/evals/evals-specifyType 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 tikalk/adlc-team-skills --skill evals-specify -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install tikalk/adlc-team-skills evals-specify --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tikalk/adlc-team-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/evals/evals-specify .agents/skills/evals-specify && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "evals-specify" agent skill from https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-specify into .agents/skills/evals-specify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "evals-specify", 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 tikalk/adlc-team-skills --skill evals-specify -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install tikalk/adlc-team-skills evals-specify --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tikalk/adlc-team-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/evals/evals-specify .cursor/skills/evals-specify && 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 "evals-specify" agent skill from https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-specify into .cursor/skills/evals-specify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "evals-specify", 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/tikalk/adlc-team-skills.git --path skills/evals/evals-specify--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 tikalk/adlc-team-skills --skill evals-specify -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install tikalk/adlc-team-skills evals-specify --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tikalk/adlc-team-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/evals/evals-specify .gemini/skills/evals-specify && 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 "evals-specify" agent skill from https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-specify into .gemini/skills/evals-specify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "evals-specify", 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 tikalk/adlc-team-skills evals-specifyInstalls 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 tikalk/adlc-team-skills --skill evals-specify -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/tikalk/adlc-team-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/evals/evals-specify .github/skills/evals-specify && 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 "evals-specify" agent skill from https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-specify into .github/skills/evals-specify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "evals-specify", 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 tikalk/adlc-team-skills --skill evals-specify -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install tikalk/adlc-team-skills evals-specify --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/tikalk/adlc-team-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/evals/evals-specify .opencode/skills/evals-specify && 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 "evals-specify" agent skill from https://github.com/tikalk/adlc-team-skills/tree/main/skills/evals/evals-specify into .opencode/skills/evals-specify/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "evals-specify", 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
evals-specify- GitHub stars
- 141
- Token cost
- ~915 tokens
- SKILL.md length
- 394 words
- Files
- 3 (incl. scripts)
- Skills in repo
- 44
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when you want guided bottom-up error analysis, structured failure taxonomy discovery, or comprehensive trace coding before documenting eval criteria.
- Works in 4 steps: Open Coding Analysis → Create Draft Criteria → Create Draft Files → …
- You want guided bottom-up error analysis
- SKILL.md covers What this skill does, When to use, When NOT to use and Process, plus 1 more section
- Runs Shell and PowerShell scripts from its folder
What it does
Evals Specify is an agent skill from tikalk/adlc-team-skills. Use when you want guided bottom-up error analysis, structured failure taxonomy discovery, or comprehensive trace coding before documenting eval criteria. Optional for routine capture — team-boot writes lightweight eval drafts directly.
Its SKILL.md is about 920 tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts (for example `scripts/bash/setup-evals-specify.sh`).
It sits in AI & LLM Engineering, covering LLM evaluation. The repository describes itself as: Agent skills for the Agentic SDLC: team lifecycle (team-boot, team-learn, team-init, team-repair), software factory, evals, CDR lifecycle with confidence scoring, and… The licence is MIT.
When your agent uses it
- You want guided bottom-up error analysis
- Structured failure taxonomy discovery
- Comprehensive trace coding before documenting eval criteria
Example prompts
- “/evals-specify”
Requirements
- A Bash shell
- PowerShell
Workflow steps
4 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 2dbed36. 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
Ships 2 files in scripts/ (Shell and PowerShell), which the agent can run.
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
Evals Specify loads about 915 tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 394 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); the scripts in this folder are not scanned.
SKILL.md
The full file from tikalk/adlc-team-skills at commit 2dbed36, republished under its MIT licence (© tikalk). 394 words, ~915 tokens.
Download SKILL.mdSave it as
.claude/skills/evals-specify/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- evals-specify
- description
- Use when you want guided bottom-up error analysis, structured failure taxonomy discovery, or comprehensive trace coding before documenting eval criteria. Optional for routine capture — team-boot writes lightweight eval drafts directly.
- disable-model-invocation
- true
evals-specify
What this skill does
Conducts bottom-up error analysis following EDD Principles III & IX (Error Analysis & Test Data as Code) to discover and document draft evaluation criteria from human observation of system failures.
Output:
- Draft Eval Records - Individual
EVAL-*.mdfiles in.adlc/drafts/evals/with open coding notes - Error Pattern Documentation - Bottom-up failure taxonomy from actual traces
- Pass/Fail Examples - Real examples that should pass/fail each criterion
- Auto-handoff to
/evals-clarifyfor axial coding and clustering
Key EDD Principles Applied:
- Principle III: Error Analysis & Pattern Discovery - Open coding → failure taxonomy
- Principle IX: Test Data as Code - Dataset planning and coverage analysis
- Principle II: Binary Pass/Fail - Maintain strict binary pass/fail conditions
- Principle V: Trajectory Observability - Track full multi-turn conversation traces
When to use
Note: Routine decision capture is handled by team-boot's continuous capture mechanism, which writes lightweight drafts directly to
.adlc/drafts/. This skill is for interactive deep-dive exploration — when you want guided trade-off analysis, multi-option comparison, or structured decision facilitation before documenting.
- Starting evaluation development: No existing criteria, need discovery from failure logs
- Production incident analysis: Recent failures require systematic analysis
- Quality assessment: Discovering and codifying boundary conditions from failures
When NOT to use
- No failure traces/specs: Generate synthetic traces first, or use
/evals-initto set up security baselines - Known criteria already exist: Use
/evals-clarifyto refine or/evals-implementto generate code
Process
Show full SKILL.md (172 more words)Show less
User Input
$ARGUMENTSTreat user input as specific failure areas or error patterns to analyze (e.g., "authentication bypass", "RAG irrelevant results").
--traces N— Number of traces to analyze (default: 20, min for theoretical saturation)--source SOURCE— Trace source location (e.g., logs, support tickets)
Execution Steps
Phase 1: Open Coding Analysis
- Reviews the user-provided failure logs or spec requirements.
- Conducts open coding of traces to discover recurring failure patterns (EDD Principle III).
- Identifies: core problem, causal conditions, and consequences.
Phase 2: Create Draft Criteria
Group patterns into draft criteria. For each:
- Define strict Pass Condition (observable, binary yes/no)
- Define strict Fail Condition (observable, binary yes/no)
- Document real pass/fail examples directly from traces
Phase 3: Create Draft Files
- Copy
skills/evals/evals-templates/eval-criterion-template.mdto.adlc/drafts/evals/EVAL-{NNN}.md. - Populate metadata and error analysis notes.
- Regenerate index at
.adlc/drafts/evals/evals.md.
Phase 4: Auto-Handoff
Trigger /evals-clarify for axial coding and clustering.
Verification
- Draft files created at
.adlc/drafts/evals/EVAL-*.md - Index file
.adlc/drafts/evals/evals.mdupdated with draft summaries - Each draft contains: status "draft", pass/fail conditions, trace sources, and concrete examples
- Auto-handoff context produced with list of created drafts
© tikalk, 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 2 other files (scripts) in skills/evals/evals-specify of tikalk/adlc-team-skills.
- SKILL.md
- scripts/bash/setup-evals-specify.sh
- scripts/powershell/setup-evals-specify.ps1
Open the folder on GitHubat commit 2dbed36
Compare with similar skills
Evals Specify 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 |
|---|---|---|---|---|---|---|
| Evals Specify this skilltikalk/adlc-team-skills | 141 | — | ~915 | Automated safety check: Pass | MIT | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| Azure AI Projects Python SDKmicrosoft/skills | 3.1k | 6 repos | ~2.8k | Automated safety check: Pass | MIT | |
| Fine-Tuning ExpertJeffallan/claude-skills | 12k | 1 repos | ~1.7k | Automated safety check: Pass | MIT | |
| Looperksimback/looper | 710 | — | ~2.7k | Automated safety check: Notes | MIT | |
| Hugging Face Local Model Evalshuggingface/skills | 11k | 2 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 |
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Guides LLM fine-tuning with LoRA and QLoRA through Hugging Face PEFT, from dataset validation and training checks to adapter merging, quantization and deployment.
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Categories
Questions about Evals Specify
What does Evals Specify do?
A skill your agent uses when you want guided bottom-up error analysis, structured failure taxonomy discovery, or comprehensive trace coding before documenting eval criteria. Evals Specify is an agent skill from tikalk/adlc-team-skills. Use when you want guided bottom-up error analysis, structured failure taxonomy discovery, or comprehensive trace coding before documenting eval criteria.
When should I use Evals Specify?
Evals Specify fits situations like: you want guided bottom-up error analysis; structured failure taxonomy discovery; comprehensive trace coding before documenting eval criteria.
How do I install Evals Specify in Claude Code?
Run `npx skills add tikalk/adlc-team-skills --skill evals-specify -a claude-code`. Or copy the skill folder (skills/evals/evals-specify in tikalk/adlc-team-skills) into .claude/skills/evals-specify in your project. Claude Code loads it when a task matches its description.
How do I install Evals Specify in Codex?
Run `npx skills add tikalk/adlc-team-skills --skill evals-specify -a codex`. Or copy the skill folder (skills/evals/evals-specify in tikalk/adlc-team-skills) into .agents/skills/evals-specify in your project. Codex loads it when a task matches its description.
Can I use Evals Specify 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 tikalk/adlc-team-skills --skill evals-specify -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/evals-specify, .gemini/skills/evals-specify, .github/skills/evals-specify and .opencode/skills/evals-specify in your project.
What does Evals Specify need to run?
Going by SKILL.md and its folder, Evals Specify needs a shell and PowerShell for the scripts in its folder. Our summary lists: A Bash shell; PowerShell.
Does Evals Specify 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 Evals Specify 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Evals Specify use?
Evals Specify 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 Evals Specify use?
About 915 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 Evals Specify?
Skills that share tags, products or a category with Evals Specify: LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), Azure AI Projects Python SDK (microsoft/skills, 3.1k stars), Fine-Tuning Expert (Jeffallan/claude-skills, 12k stars) and Looper (ksimback/looper, 710 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Evals Specify?
tikalk (a GitHub organization) maintains it in tikalk/adlc-team-skills, which has 141 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on October 6, 2026.
Source: tikalk/adlc-team-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.