Agent Builder
shareAI-lab/learn-claude-code
Design and build AI agents for any domain. An agent skill from shareAI-lab/learn-claude-code.
Prepare and run Overmind evaluations, author evaluators and eval sets, compare runs, and inspect sample-level failures.
Install Overmind Evaluations
$ npx skills add overmind-core/overmind --skill overmind-evaluations -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install overmind-core/overmind overmind-evaluations --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/overmind-core/overmind.git skills-src && mkdir -p .claude/skills && cp -r skills-src/overmind/skills/overmind-evaluations .claude/skills/overmind-evaluations && 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 "overmind-evaluations" agent skill from https://github.com/overmind-core/overmind/tree/main/overmind/skills/overmind-evaluations into .claude/skills/overmind-evaluations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "overmind-evaluations", 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/overmind-core/overmind/tree/main/overmind/skills/overmind-evaluationsType 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 overmind-core/overmind --skill overmind-evaluations -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install overmind-core/overmind overmind-evaluations --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/overmind-core/overmind.git skills-src && mkdir -p .agents/skills && cp -r skills-src/overmind/skills/overmind-evaluations .agents/skills/overmind-evaluations && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "overmind-evaluations" agent skill from https://github.com/overmind-core/overmind/tree/main/overmind/skills/overmind-evaluations into .agents/skills/overmind-evaluations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "overmind-evaluations", 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 overmind-core/overmind --skill overmind-evaluations -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install overmind-core/overmind overmind-evaluations --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/overmind-core/overmind.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/overmind/skills/overmind-evaluations .cursor/skills/overmind-evaluations && 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 "overmind-evaluations" agent skill from https://github.com/overmind-core/overmind/tree/main/overmind/skills/overmind-evaluations into .cursor/skills/overmind-evaluations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "overmind-evaluations", 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/overmind-core/overmind.git --path overmind/skills/overmind-evaluations--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 overmind-core/overmind --skill overmind-evaluations -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install overmind-core/overmind overmind-evaluations --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/overmind-core/overmind.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/overmind/skills/overmind-evaluations .gemini/skills/overmind-evaluations && 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 "overmind-evaluations" agent skill from https://github.com/overmind-core/overmind/tree/main/overmind/skills/overmind-evaluations into .gemini/skills/overmind-evaluations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "overmind-evaluations", 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 overmind-core/overmind overmind-evaluationsInstalls 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 overmind-core/overmind --skill overmind-evaluations -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/overmind-core/overmind.git skills-src && mkdir -p .github/skills && cp -r skills-src/overmind/skills/overmind-evaluations .github/skills/overmind-evaluations && 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 "overmind-evaluations" agent skill from https://github.com/overmind-core/overmind/tree/main/overmind/skills/overmind-evaluations into .github/skills/overmind-evaluations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "overmind-evaluations", 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 overmind-core/overmind --skill overmind-evaluations -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install overmind-core/overmind overmind-evaluations --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/overmind-core/overmind.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/overmind/skills/overmind-evaluations .opencode/skills/overmind-evaluations && 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 "overmind-evaluations" agent skill from https://github.com/overmind-core/overmind/tree/main/overmind/skills/overmind-evaluations into .opencode/skills/overmind-evaluations/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "overmind-evaluations", 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
overmind-evaluations- GitHub stars
- 597
- Token cost
- ~779 tokens
- SKILL.md length
- 378 words
- Files
- 3 (incl. assets)
- Skills in repo
- 20
- Repo updated
- First seen
- Licence
- AGPL-3.0
At a glance
Prepare and run Overmind evaluations, author evaluators and eval sets, compare runs, and inspect sample-level failures.
- Judging a change against a baseline
- SKILL.md covers Inspect or prepare and Run and compare
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Training and repository optimisation have separate workflows
What it does
Overmind Evaluations is an agent skill from overmind-core/overmind. Prepare and run Overmind evaluations, author evaluators and eval sets, compare runs, and inspect sample-level failures. Use for judging a change against a baseline; training and repository optimisation have separate workflows.
Its SKILL.md is about 780 tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including assets (for example `agents/openai.yaml`).
It sits in AI & LLM Engineering. The repository describes itself as: The platform for continuously improving AI agents. The licence is AGPL-3.0.
When your agent uses it
- Judging a change against a baseline
- Training and repository optimisation have separate workflows
Example prompts
- “/overmind-evaluations”
What it can do on your machine
Read from SKILL.md and the folder at commit 3dec73c. 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
No scripts in the folder and no shell commands in SKILL.md.
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
Overmind Evaluations loads about 779 tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 378 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 overmind-core/overmind at commit 3dec73c, republished under its AGPL-3.0 licence (© overmind-core). 378 words, ~779 tokens.
Download SKILL.mdSave it as
.claude/skills/overmind-evaluations/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- overmind-evaluations
- description
- Prepare and run Overmind evaluations, author evaluators and eval sets, compare runs, and inspect sample-level failures. Use for judging a change against a baseline; training and repository optimisation have separate workflows.
Overmind Evaluations
Start with list_projects and choose the intended accessible project. For an
account connection, pass its project_id on every project tool and resource
URI query; follow returned links. Project API keys retain their narrower access.
Determine whether a change improves the intended task and how trustworthy that comparison is. Use the chosen MCP project and its current tool schemas.
Inspect or prepare
For an existing run, read overmind://eval-runs/{eval_run} and its linked
resources. An inspection request does not require creating a new run.
For new work, resolve the dataset using list_datasets, inspect its selected
cell and verify relevant examples through query_dataset. Use an eval-intent
version. Report residual semantic findings as warnings, including missing
evidence or overlap; do not fabricate expected outputs to make the data fit.
Prefer the native prepare-evaluation prompt with dataset and eval set when
available. Use check_evaluation_readiness with the selected cell and proposed
variants. Resolve reported evaluator applicability, bindings, dataset and credit
requirements. Read overmind://eval-sets/{eval_set} for set details.
When evaluator changes are requested, collect the actual rubric and use
upsert_evaluator; group selected evaluator IDs with create_eval_set when
needed. Rubric judges default to generative. Preserve existing evaluation
semantics unless the user asks to change them.
Show full SKILL.md (181 more words)Show less
Run and compare
Before a paid run, make the dataset/cell, candidate variants, baseline and judge/cost choices concrete. Context estimates are advisory; present estimated overflows and available choices without automatically changing or excluding a model.
Use judge_model on readiness and run_evaluation for a run-only judge choice.
Omission preserves saved evaluators. The run freezes its judges; do not edit
saved evaluators or an existing run to implement this override.
For an authorized change evaluation, prefer evaluate-change with dataset and
baseline. Otherwise call run_evaluation after checking readiness, poll its
eval_run job and read the completed run. Use compare_evaluations for the
specified baseline. Keep pinned dataset, variants and judge identities visible
when assessing whether the runs are comparable.
Report overall and evaluator-level deltas, sample coverage and trust flags.
Separate failed generation, output exhaustion and judge errors from quality
scores; degraded or skipped samples must not disappear into a passing average.
Use annotate_evaluation_sample only to record an explicit human label.
Conclude improved, regressed, unchanged or insufficient evidence, with supporting
run/sample IDs. For a visual comparison open evaluations/runs/{id} under the
current project's Console base and preserve projectId.
© overmind-core, AGPL-3.0. 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 (assets) in overmind/skills/overmind-evaluations of overmind-core/overmind.
- SKILL.md
- agents/openai.yaml
- assets/icon.png
Open the folder on GitHubat commit 3dec73c
Compare with similar skills
Overmind Evaluations 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 |
|---|---|---|---|---|---|---|
| Overmind Evaluations this skillovermind-core/overmind | 597 | — | ~779 | Automated safety check: Pass | AGPL-3.0 | |
| Agent BuildershareAI-lab/learn-claude-code | 78k | 6 repos | ~1.2k | Automated safety check: Pass | MIT | |
| Add Uint Supportpytorch/pytorch | 104k | 2 repos | ~2.3k | Automated safety check: Pass | Custom licence | |
| Peft Fine TuningOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.1k | Automated safety check: Pass | MIT | |
| Segment Anything Model GuideOrchestra-Research/AI-Research-SKILLs | 13k | 9 repos | ~3.3k | Automated safety check: Pass | MIT | |
| 1passwordtrpc-group/trpc-agent-go | 1.8k | 15 repos | ~656 | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Overmind Evaluations
What does Overmind Evaluations do?
Prepare and run Overmind evaluations, author evaluators and eval sets, compare runs, and inspect sample-level failures. Overmind Evaluations is an agent skill from overmind-core/overmind. Prepare and run Overmind evaluations, author evaluators and eval sets, compare runs, and inspect sample-level failures.
When should I use Overmind Evaluations?
Overmind Evaluations fits situations like: judging a change against a baseline; training and repository optimisation have separate workflows.
How do I install Overmind Evaluations in Claude Code?
Run `npx skills add overmind-core/overmind --skill overmind-evaluations -a claude-code`. Or copy the skill folder (overmind/skills/overmind-evaluations in overmind-core/overmind) into .claude/skills/overmind-evaluations in your project. Claude Code loads it when a task matches its description.
How do I install Overmind Evaluations in Codex?
Run `npx skills add overmind-core/overmind --skill overmind-evaluations -a codex`. Or copy the skill folder (overmind/skills/overmind-evaluations in overmind-core/overmind) into .agents/skills/overmind-evaluations in your project. Codex loads it when a task matches its description.
Can I use Overmind Evaluations 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 overmind-core/overmind --skill overmind-evaluations -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/overmind-evaluations, .gemini/skills/overmind-evaluations, .github/skills/overmind-evaluations and .opencode/skills/overmind-evaluations in your project.
What does Overmind Evaluations need to run?
SKILL.md names no scripts, command-line tools or credentials: Overmind Evaluations is instructions for the agent only.
Does Overmind Evaluations 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 Overmind Evaluations 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 Overmind Evaluations use?
Overmind Evaluations is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Overmind Evaluations use?
About 779 tokens (SKILL.md is roughly 3.1k 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 Overmind Evaluations?
Skills that share tags, products or a category with Overmind Evaluations: Agent Builder (shareAI-lab/learn-claude-code, 78k stars), Add Uint Support (pytorch/pytorch, 104k stars), Peft Fine Tuning (Orchestra-Research/AI-Research-SKILLs, 13k stars) and Segment Anything Model Guide (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Overmind Evaluations?
overmind-core (a GitHub organization) maintains it in overmind-core/overmind, which has 597 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on October 8, 2026.
Source: overmind-core/overmind on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.