Supabase Postgres Best Practices
supabase/agent-skills
Gives the agent Postgres rules to consult before writing or changing tables, queries, indexes, RLS policies or migrations, and when diagnosing slow queries.
Consolidate FINISHED standard / lmeval (evalchemy) math-suite eval jobs — the Delphi 6279 MATH-500 / AIME24 / gsm8k grid launched via eval-standard-launch — into the SCORES.md tracker.
Apache-2.0Auto-check passed
Install Eval Standard Cleanup
$ npx skills add open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install open-thoughts/OpenThoughts-Agent eval-standard-cleanup --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/open-thoughts/OpenThoughts-Agent.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/eval-standard-cleanup .claude/skills/eval-standard-cleanup && 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 "eval-standard-cleanup" agent skill from https://github.com/open-thoughts/OpenThoughts-Agent/tree/main/.agents/skills/eval-standard-cleanup into .claude/skills/eval-standard-cleanup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-standard-cleanup", 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/open-thoughts/OpenThoughts-Agent/tree/main/.agents/skills/eval-standard-cleanupType 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 open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install open-thoughts/OpenThoughts-Agent eval-standard-cleanup --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/open-thoughts/OpenThoughts-Agent.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/eval-standard-cleanup .agents/skills/eval-standard-cleanup && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "eval-standard-cleanup" agent skill from https://github.com/open-thoughts/OpenThoughts-Agent/tree/main/.agents/skills/eval-standard-cleanup into .agents/skills/eval-standard-cleanup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-standard-cleanup", 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 open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install open-thoughts/OpenThoughts-Agent eval-standard-cleanup --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/open-thoughts/OpenThoughts-Agent.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/eval-standard-cleanup .cursor/skills/eval-standard-cleanup && 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 "eval-standard-cleanup" agent skill from https://github.com/open-thoughts/OpenThoughts-Agent/tree/main/.agents/skills/eval-standard-cleanup into .cursor/skills/eval-standard-cleanup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-standard-cleanup", 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/open-thoughts/OpenThoughts-Agent.git --path .agents/skills/eval-standard-cleanup--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 open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install open-thoughts/OpenThoughts-Agent eval-standard-cleanup --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/open-thoughts/OpenThoughts-Agent.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/eval-standard-cleanup .gemini/skills/eval-standard-cleanup && 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 "eval-standard-cleanup" agent skill from https://github.com/open-thoughts/OpenThoughts-Agent/tree/main/.agents/skills/eval-standard-cleanup into .gemini/skills/eval-standard-cleanup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-standard-cleanup", 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 open-thoughts/OpenThoughts-Agent eval-standard-cleanupInstalls 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 open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/open-thoughts/OpenThoughts-Agent.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/eval-standard-cleanup .github/skills/eval-standard-cleanup && 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 "eval-standard-cleanup" agent skill from https://github.com/open-thoughts/OpenThoughts-Agent/tree/main/.agents/skills/eval-standard-cleanup into .github/skills/eval-standard-cleanup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-standard-cleanup", 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 open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install open-thoughts/OpenThoughts-Agent eval-standard-cleanup --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/open-thoughts/OpenThoughts-Agent.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/eval-standard-cleanup .opencode/skills/eval-standard-cleanup && 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 "eval-standard-cleanup" agent skill from https://github.com/open-thoughts/OpenThoughts-Agent/tree/main/.agents/skills/eval-standard-cleanup into .opencode/skills/eval-standard-cleanup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-standard-cleanup", 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
eval-standard-cleanup- GitHub stars
- 301
- Token cost
- ~1.7k tokens
- SKILL.md length
- 684 words
- Files
- 1
- Skills in repo
- 44
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Consolidate FINISHED standard / lmeval (evalchemy) math-suite eval jobs — the Delphi 6279 MATH-500 / AIME24 / gsm8k grid launched via eval-standard-launch — into the SCORES.md tracker.
- Works in 7 steps: Reference files (source of truth —… → Per finished job — verify a real,… → Consolidate — rsync results into the… → …
- Asked to consolidate / harvest finished standard math-eval jobs
- SKILL.md covers 0. Reference files (source of…, 1. Per finished job — verify a…, 2. Consolidate — rsync results… and 3. Parse the scalars (the…, plus 3 more sections
- Calls rsync
What it does
Eval Standard Cleanup is an agent skill from open-thoughts/OpenThoughts-Agent. Consolidate FINISHED standard / lmeval (evalchemy) math-suite eval jobs — the Delphi 6279 MATH-500 / AIME24 / gsm8k grid launched via eval-standard-launch — into the SCORES.md tracker. Per job: confirm a NON-EMPTY seed42 result (a crash leaves it empty — don't record it as a score), rsync the results.json into the local per-model dir, write scalar partials, parse the scalars (MATH-500 acc×100 / AIME24 10-seed mean±sd / gsm8k strict+flex / Raw), and flip the SCORES.md row 🚀 eval submitted → ✅ done. The artifact…
Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It works with Supabase. The repository describes itself as: Data recipes and robust infrastructure for training AI agents. The licence is Apache-2.0.
When your agent uses it
- Asked to consolidate / harvest finished standard math-eval jobs
- Fill the scaling-laws score grid
Example prompts
- “/eval-standard-cleanup”
Workflow steps
7 steps, taken from the step headings in SKILL.md.
- Reference files (source of truth — derive the flow from these)
- Per finished job — verify a real, non-empty result (do NOT record a crash as a score)
- Consolidate — rsync results into the local per-model dir + write scalar partials
- Parse the scalars (the §5.2-E method — round to 1 decimal to match the table)
- Update the SCORES.md row — 🚀 eval submitted → ✅ done
- HF-upload only — NEVER DB
- Disk / hygiene
What it can do on your machine
Read from SKILL.md and the folder at commit 3bd1917. 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:
rsync
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use rsync, 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
Eval Standard Cleanup loads about 1.7k tokens when it runs. Until then it costs about 196 tokens; SKILL.md has 684 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 open-thoughts/OpenThoughts-Agent at commit 3bd1917, republished under its Apache-2.0 licence (© open-thoughts). 684 words, ~1,677 tokens.
Download SKILL.mdSave it as
.claude/skills/eval-standard-cleanup/SKILL.md (or your agent's skills folder).- name
- eval-standard-cleanup
- description
- Consolidate FINISHED standard / lm_eval (evalchemy) math-suite eval jobs — the Delphi #6279 MATH-500 / AIME24 / gsm8k grid launched via eval-standard-launch — into the SCORES.md tracker. Per job: confirm a NON-EMPTY seed42 result (a crash leaves it empty — don't record it as a score), rsync the results_*.json into the local per-model dir, write scalar partials, parse the scalars (MATH-500 acc×100 / AIME24 10-seed mean±sd / gsm8k strict+flex / Raw), and flip the SCORES.md row 🚀 eval submitted → ✅ done. The artifact is SCALAR SCORES IN A TRACKER — HF-upload-only, NEVER DB. Use when asked to consolidate / harvest finished standard math-eval jobs or fill the scaling-laws score grid. DISTINCT from eval-agentic-cleanup (the Harbor-trace + Supabase DB path).
eval-standard-cleanup
Post-run consolidation for STANDARD evals (lm_eval / evalchemy): the Delphi #6279 RL-scaling-laws
math suite — MATH-500 (1 seed) + AIME24 (10-seed mean±sd) + gsm8k (strict+flex) — launched by the
eval-standard-launch skill on Leonardo. The deliverable is scalar scores in a tracker: no HF
trace upload, no model upload, NEVER a DB registration (see §5). For the agentic Harbor-trace +
Supabase path, use eval-agentic-cleanup instead.
0. Reference files (source of truth — derive the flow from these)
Local notes dir: /Users/benjaminfeuer/Documents/experiments/active/delphi/rl-scaling-laws-6279/
eval-standard-launchskill — the launch +delphi_eval.sbatch+ the per-model output layout it produces (…/experiments/delphi-eval/<RUN_NAME>/seed{42..51}/). Read it for what's already on the cluster.main_sft_evals/SCORES.md— the master tracker for the 54-run main grid; its header describes the consolidation flow (per-model dirsmain_sft_evals/<basename>/, partialsmain_sft_evals/.partial/).EVAL_CONVENTION.md§3.4 / §5.2-E — the per-cluster naming, the idempotent-skipseed42dir, the exact scalar-parse method, and the "COMPLETED is NOT proof — verify numeric scores" rule.- The earlier cold-start grid is the same flow but a different tracker (
eval/SCORES.md, artifactseval/<RUN>/) — don't cross-file; the 54-run main grid lands inmain_sft_evals/.
1. Per finished job — verify a real, non-empty result (do NOT record a crash as a score)
A SLURM COMPLETED state is necessary but not sufficient: evalchemy catches engine errors, exits 0,
and writes an empty results: {} JSON (silent drop). For each job:
- Confirm terminal state via
sacct -j <jobid> --format=State -n -P | head -1(the source of truth, not log-tailing). - Confirm the job produced a NON-EMPTY
seed42result — the §3.4 idempotent-skip dir (…/delphi-eval/<RUN_NAME>/seed42/) must exist and itsresults_*.jsonmust carry numeric scores (a crashed/timed-out run leaves an empty or missingseed42). An empty/missing seed42 → leave the row pending and note it; do not fabricate a score. (If gsm8k failed after MATH-500 wrote seed42, seed42 exists but is partial — note it; deleting seed42 + re-running is a launcher action, not a cleanup one.)
2. Consolidate — rsync results into the local per-model dir + write scalar partials
Pull only the per-task results_*.json (the examples payloads live inside the JSON, ~1-2 MB each;
skip the multi-MB trace subdirs). For the main grid the destination is main_sft_evals/<basename>/:
RUN=delphi-9e19-p33m67-k0p20-lr83-a002-magpie_lr1e5-sft # = the SFT model basename, maps 1:1 to the row
DEST=/Users/benjaminfeuer/Documents/experiments/active/delphi/rl-scaling-laws-6279/main_sft_evals/$RUN
mkdir -p "$DEST"
rsync -avz --prune-empty-dirs --include='*/' --include='results_*.json' --exclude='*' \
Leonardo:/leonardo_work/AIFAC_5C0_290/bfeuer00/experiments/delphi-eval/$RUN/ "$DEST/"This pulls the MATH-500 seed42 JSON, the gsm8k seed42 JSON (written by the plain lm_eval step), and
the AIME24 seed42..seed51 JSONs. Write the extracted scalars to main_sft_evals/.partial/<basename>.json.
Keep the rsynced JSONs in <basename>/ as the archive. Parse by loading the JSON and reading only
numeric keys — never print the huge examples list.
Show full SKILL.md (296 more words)Show less
3. Parse the scalars (the §5.2-E method — round to 1 decimal to match the table)
- MATH-500 =
results["MATH500"]["accuracy"] × 100(it's a fraction; 0.018 → 1.8). Fromseed42. - AIME24 =
results["AIME24"]["accuracy_avg"] × 100, taken over the 10 seed dirs (seed42..seed51); report mean ± sample-stdev of the per-seed values (×100). (e.g.0.1±0.1.) - gsm8k (from the
lm_evaloutput under<basename>/seed42):exact_match,strict-match→ gsm8k-S andexact_match,flexible-extract→ gsm8k-F, each ×100. - Raw =
mean(MATH-500, AIME24, gsm8k-strict). - Note any format-fail cell (empty
\boxed{}/model_answer:"") — that's a real signal, not an eval bug.
The marin compiler marin:experiments/evals/evalchemy_results_compiler.py documents the exact JSON shape
(results[task]…) — reuse its extraction shape rather than rolling a new parse. (verify the precise key
names against the rsynced JSON on first use; evalchemy versions have drifted.)
4. Update the SCORES.md row — 🚀 eval submitted → ✅ done
Fill that row's MATH-500 | AIME24 (mean±se) | gsm8k-S | gsm8k-F | Raw cells from the partial and flip
status from 🚀 eval submitted to ✅ done (keep the eval job id in its column). Edit the single row
(rows are independent lines) and preserve the table format exactly. A crashed/empty-seed42 job stays
pending with a note (step 1) — never invent numbers.
5. HF-upload only — NEVER DB
These are scalar scores in a tracker, not a model/trace artifact. Do NOT call
manual_db_eval_push.py / touch Supabase — that is the eval-agentic-cleanup (agentic / Harbor-trace)
path. Results live in this experiment's docs + (optionally) as a training_logs/-style JSON on the model's
HF repo; there is no leaderboard row. (Per project_delphi_sft_hf_only_no_db.)
6. Disk / hygiene
The local artifacts are small (~1-2 MB JSONs); no large delete is needed. On the cluster, leave the
delphi-eval/<RUN_NAME>/ dirs in place — they back the §3.4 idempotent skip, so a re-harvest or re-submit
stays safe. No find / du / rglob on GPFS; use canonical paths.
Launcher: eval-standard-launch. Model-publishing cleanups: rl-agentic-job-cleanup /
sft-job-cleanup. Per-cluster particulars (ssh, the step-ca cert refresh for rsync, the
/leonardo_work/AIFAC_5C0_290/bfeuer00/… paths) → .agents/ops/<cluster>/.
© open-thoughts, 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/eval-standard-cleanup of open-thoughts/OpenThoughts-Agent.
Open the folder on GitHubat commit 3bd1917
Compare with similar skills
Eval Standard Cleanup 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 |
|---|---|---|---|---|---|---|
| Eval Standard Cleanup this skillopen-thoughts/OpenThoughts-Agent | 301 | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | |
| Supabase Postgres Best Practicessupabase/agent-skills | 2.7k | 24 repos | ~808 | Automated safety check: Pass | MIT | |
| Supabase Development and Debuggingsupabase/agent-skills | 2.7k | 3 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Clickhouse Logs Queriessupabase/supabase | 111k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Security Reviewjewbetcha/opentrace | 116 | 18 repos | ~3.1k | Automated safety check: Notes | MIT | |
| Review The Docssupabase/supabase | 111k | — | ~4.6k | Automated safety check: Pass | Apache-2.0 |
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Questions about Eval Standard Cleanup
What does Eval Standard Cleanup do?
Consolidate FINISHED standard / lmeval (evalchemy) math-suite eval jobs — the Delphi 6279 MATH-500 / AIME24 / gsm8k grid launched via eval-standard-launch — into the SCORES.md tracker. Eval Standard Cleanup is an agent skill from open-thoughts/OpenThoughts-Agent.md tracker.
When should I use Eval Standard Cleanup?
Eval Standard Cleanup fits situations like: asked to consolidate / harvest finished standard math-eval jobs; fill the scaling-laws score grid.
How do I install Eval Standard Cleanup in Claude Code?
Run `npx skills add open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a claude-code`. Or copy the skill folder (.agents/skills/eval-standard-cleanup in open-thoughts/OpenThoughts-Agent) into .claude/skills/eval-standard-cleanup in your project. Claude Code loads it when a task matches its description.
How do I install Eval Standard Cleanup in Codex?
Run `npx skills add open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a codex`. Or copy the skill folder (.agents/skills/eval-standard-cleanup in open-thoughts/OpenThoughts-Agent) into .agents/skills/eval-standard-cleanup in your project. Codex loads it when a task matches its description.
Can I use Eval Standard Cleanup 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 open-thoughts/OpenThoughts-Agent --skill eval-standard-cleanup -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/eval-standard-cleanup, .gemini/skills/eval-standard-cleanup, .github/skills/eval-standard-cleanup and .opencode/skills/eval-standard-cleanup in your project.
What does Eval Standard Cleanup need to run?
Going by SKILL.md and its folder, Eval Standard Cleanup needs the command-line tools its instructions call (rsync).
Does Eval Standard Cleanup 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 Eval Standard Cleanup 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 Eval Standard Cleanup use?
Eval Standard Cleanup 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 Eval Standard Cleanup use?
About 1.7k tokens (SKILL.md is roughly 6.7k 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 Eval Standard Cleanup?
Skills that share tags, products or a category with Eval Standard Cleanup: Supabase Postgres Best Practices (supabase/agent-skills, 2.7k stars), Supabase Development and Debugging (supabase/agent-skills, 2.7k stars), Clickhouse Logs Queries (supabase/supabase, 111k stars) and Security Review (jewbetcha/opentrace, 116 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Eval Standard Cleanup?
open-thoughts (a GitHub organization) maintains it in open-thoughts/OpenThoughts-Agent, which has 301 GitHub stars. The repository holds 44 skills in this directory. The repository was last updated on September 28, 2026.
Source: open-thoughts/OpenThoughts-Agent on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.