SQL Optimization
github/awesome-copilot
Universal SQL performance optimization assistant for comprehensive query tuning, indexing strategies, and database performance analysis across all SQL databases (MySQL, PostgreSQL, SQL Server…
Disciplined, validation-gated revision of an EXISTING skill so each edit is a measured improvement rather than a guess.
MITAuto-check passed
Install Optimizing Skills
$ npx skills add oaustegard/claude-skills --skill optimizing-skills -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install oaustegard/claude-skills optimizing-skills --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/oaustegard/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/optimizing-skills .claude/skills/optimizing-skills && 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 "optimizing-skills" agent skill from https://github.com/oaustegard/claude-skills/tree/main/optimizing-skills into .claude/skills/optimizing-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimizing-skills", 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/oaustegard/claude-skills/tree/main/optimizing-skillsType 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 oaustegard/claude-skills --skill optimizing-skills -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install oaustegard/claude-skills optimizing-skills --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/optimizing-skills .agents/skills/optimizing-skills && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "optimizing-skills" agent skill from https://github.com/oaustegard/claude-skills/tree/main/optimizing-skills into .agents/skills/optimizing-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimizing-skills", 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 oaustegard/claude-skills --skill optimizing-skills -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install oaustegard/claude-skills optimizing-skills --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/optimizing-skills .cursor/skills/optimizing-skills && 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 "optimizing-skills" agent skill from https://github.com/oaustegard/claude-skills/tree/main/optimizing-skills into .cursor/skills/optimizing-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimizing-skills", 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/oaustegard/claude-skills.git --path optimizing-skills--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 oaustegard/claude-skills --skill optimizing-skills -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install oaustegard/claude-skills optimizing-skills --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/optimizing-skills .gemini/skills/optimizing-skills && 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 "optimizing-skills" agent skill from https://github.com/oaustegard/claude-skills/tree/main/optimizing-skills into .gemini/skills/optimizing-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimizing-skills", 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 oaustegard/claude-skills optimizing-skillsInstalls 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 oaustegard/claude-skills --skill optimizing-skills -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/optimizing-skills .github/skills/optimizing-skills && 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 "optimizing-skills" agent skill from https://github.com/oaustegard/claude-skills/tree/main/optimizing-skills into .github/skills/optimizing-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimizing-skills", 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 oaustegard/claude-skills --skill optimizing-skills -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install oaustegard/claude-skills optimizing-skills --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/oaustegard/claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/optimizing-skills .opencode/skills/optimizing-skills && 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 "optimizing-skills" agent skill from https://github.com/oaustegard/claude-skills/tree/main/optimizing-skills into .opencode/skills/optimizing-skills/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "optimizing-skills", 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
optimizing-skills- GitHub stars
- 150
- Token cost
- ~2.3k tokens
- SKILL.md length
- 1,190 words
- Files
- 4 (incl. references)
- Skills in repo
- 66
- Repo updated
- First seen
- Licence
- MIT
At a glance
Disciplined, validation-gated revision of an EXISTING skill so each edit is a measured improvement rather than a guess.
- Works in 4 steps: Assemble a held-out check set. 3–8… → Hold two versions. best = what you… → Score both on the check set. "Run" here… → …
- Tuning a skill that already exists and there is evidence it underperforms (observed failures
- SKILL.md covers Core principle, The gate — run it every revision, Bounded edits (the "textual… and Reflect: failures first, then…, plus 7 more sections
- Calls python3
What it does
Optimizing Skills is an agent skill from oaustegard/claude-skills. Disciplined, validation-gated revision of an EXISTING skill so each edit is a measured improvement rather than a guess. Use when editing, revising, or tuning a skill that already exists and there is evidence it underperforms (observed failures, drift, complaints) — invoke by name, or have versioning-skills / creating-skill defer to it before applying edits. Not for authoring a brand-new skill from scratch (use creating-skill) or one-off prose.
Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `CHANGELOG.md`, `README.md` and `references/skillopt-provenance.md`).
The repository describes itself as: My collection of Claude skills. The licence is MIT.
When your agent uses it
- Tuning a skill that already exists and there is evidence it underperforms (observed failures
- Complaints) — invoke by name
- Have versioning-skills / creating-skill defer to it before applying edits
Example prompts
- “/optimizing-skills”
Requirements
- Python 3
Workflow steps
4 steps, taken from the first numbered list in SKILL.md.
- Assemble a held-out check set. 3–8 representative tasks/prompts the skill
- Hold two versions. best = what you currently ship (never let it
- Score both on the check set. "Run" here = dispatch each check task to the
- Accept only if candidate strictly beats best on the triggering-failure
What it can do on your machine
Read from SKILL.md and the folder at commit cf49d47. 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
Optimizing Skills loads about 2.3k tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 116 tokens; SKILL.md has 1,190 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 oaustegard/claude-skills at commit cf49d47, republished under its MIT licence (© oaustegard). 1,190 words, ~2,279 tokens.
Download SKILL.mdSave it as
.claude/skills/optimizing-skills/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.- name
- optimizing-skills
- description
- Disciplined, validation-gated revision of an EXISTING skill so each edit is a measured improvement rather than a guess. Use when editing, revising, or tuning a skill that already exists and there is evidence it underperforms (observed failures, drift, complaints) — invoke by name, or have versioning-skills / creating-skill defer to it before applying edits. Not for authoring a brand-new skill from scratch (use creating-skill) or one-off prose.
- metadata.version
- 0.3.0
Optimizing Skills
Treat the skill document as the parameter under optimization: change it only when the change demonstrably beats the version you already ship. This is the discipline distilled from SkillOpt (microsoft/SkillOpt, arXiv:2605.23904) — its training apparatus dropped, its reproducibility discipline kept. The point is to stop editing skills on intuition and start editing them on evidence.
Core principle
A skill edit is only worth shipping if it strictly improves measured behavior on a held-out check. Most edits that feel like improvements don't move the needle, and some quietly regress. The gate below is what separates a real improvement from a confident guess.
The gate — run it every revision
- Assemble a held-out check set. 3–8 representative tasks/prompts the skill should handle well, and it must include the failure(s) that prompted this revision. Keep the set fixed across the revision so before/after scores are comparable.
- Hold two versions.
best= what you currently ship (never let it silently degrade).candidate=best+ your proposed edits. - Score both on the check set. "Run" here = dispatch each check task to the
Agent tool (
subagent_type=general-purpose) with the skill version in context, or evaluate by hand for small sets. Give the scoring agent the skill version and the task, and nothing else. Never hand it the ledger, your revision notes, or the diagnosis that motivated the edit: it will solve the task from those instead of from the skill, and the score stops measuring the skill. WikiSkill (arXiv:2608.27454) ablated exactly this and lost 2.8 points of final quality, 7.8 on their hardest split, by letting the worker read the improver's knowledge store. Score per criterion, not one collapsed pass/fail. When a task carries several criteria, the criterion that decides accept/reject is the failure that prompted this revision; the others are regression guards that must not get worse. Collapsing criteria masks the win: in the down-skilling-v1.2.0 retro, the edit drove architectural hallucination 60%→0% while an unrelated length criterion stayed 0/5 in both arms — a single combined pass/fail scored that as a 0–0 tie and would have rejected a large, real improvement. - Accept only if
candidatestrictly beatsbeston the triggering-failure criterion, with no regression guard worse. Ties → reject, keepbest. An edit that doesn't move the needle does not ship.
When the skill's own output is compiled by an Agent (down-skilling and creating-skill produce a prompt an author writes from the SKILL), score ≥2 author samples per version, or fix one author across both arms. A single author sample per arm lets author capability dominate the edit effect: the same down-skilling edit measured 95%→0% with one author pair and 60%→0% with another — real either way, but n=1 cannot tell a real edit from a lucky author.
This two-tier best/candidate split is the heart of it: a working revision
can explore, but the shipped skill only ever ratchets upward.
Bounded edits (the "textual learning rate")
Cap edits per revision — default ~4 distinct add/replace/delete operations, fewer as the skill matures. Large speculative rewrites drift and destroy your ability to attribute a regression to a cause. If a revision wants more edits than the budget, rank and keep the top ones (below) and let the rest wait.
Reflect: failures first, then successes
Separate the evidence before proposing edits:
- Failure reflection. Across the failing cases, find the common, systematic pattern — not a one-off edge case. Propose edits that fix the pattern. Failures take priority in any merge.
- Success reflection. Across cases that already work, find generalizable patterns worth encoding so they survive future edits. Reinforce; don't duplicate.
For both: edits must generalize (never hardcode task-specific values), and must not duplicate content already in the skill — patch genuine gaps only.
Rank when over budget
When candidate edits exceed the budget, keep them in this priority order:
- Systematic impact — fixes a recurring failure across many cases, not one.
- Complementarity — fills a real gap rather than restating existing content.
- Generality — phrased as a durable principle, not tied to one task/entity.
- Actionability — concrete, followable guidance over vague advice.
Drop the rest. They can return next revision if still warranted.
Show full SKILL.md (509 more words)Show less
Protect the hard-won core
If a skill has a battle-tested core that routine edits keep eroding, fence it off and treat it as off-limits to fast edits. Revisit it only on a deliberate longitudinal review: compare the same check tasks across several versions to catch slow drift and regressions that single-edit review misses. (SkillOpt fences this region with HTML-comment markers and only rewrites it at epoch boundaries — the same idea, manual cadence.)
Recording rejected proposals
FIRST action of any revision, before you score anything:
python3 scripts/skill_ledger.py check --skill <name> --before best.md --after candidate.mdExit 1 means this exact edit was proposed before and failed the gate. Read the recorded criterion and score, then propose something else. Do not re-score it.
After the gate decides, record the outcome — accepted or rejected:
python3 scripts/skill_ledger.py record --skill <name> \
--before best.md --after candidate.md --outcome rejected \
--criterion "<the triggering failure>" --score-before 0.6 --score-after 0.6The ledger computes the diff itself and appends it. A rejected candidate is the artifact worth keeping. The edit reverts and the record stays. The next session cannot see this one, which is why the record has to live outside your context rather than in it.
This is WikiSkill's skill-impact.md (arXiv:2608.27454), whose outer loop
keeps a never-rolled-back record of every proposal and its fate while the skill
itself rolls back. Their proposer is told in prose not to repeat rejected
approaches. check makes that mechanical instead, so it no longer depends on
anyone having read the ledger. The script lives in claude-workspace at
scripts/skill_ledger.py.
Carry memory across revisions
The ledger above holds the artifacts: which diffs were tried and how they
scored. remember() holds the judgment the diffs cannot carry. After a
revision, record what you learned about editing this skill — which kinds of
edits helped, which were brittle, redundant, or harmful — via remember()
tagged with the skill name. Before the next revision, recall()
it. This is the compounding part: each revision starts smarter than the last,
the way SkillOpt's optimizer-side meta-skill conditions its future edits.
Edit mechanics
Edits are literal string operations (the Edit tool): the target text must
match exactly or the edit is a silent no-op. Keep targets unique and
verbatim. Prefer append / insert-after-heading / replace-exact / delete-exact,
and verify each edit landed before scoring.
When NOT to use this
- Authoring a brand-new skill from scratch → creating-skill.
- Tracking/rolling back versions during development → versioning-skills.
- One-off prose with no reuse → just write it.
Checklist
- Held-out check set assembled (includes the triggering failure), fixed for the revision
- Edits bounded (~4 max), each generalizable and non-duplicative
- Failure patterns addressed before success reinforcement
- Candidate scored per-criterion against
best; accept decided by the triggering-failure criterion, others as regression guards; shipped only if strictly better - For Agent-compiled artifacts (down-skilling, creating-skill): ≥2 author samples per version, or a fixed author across arms
- Hard-won core left untouched unless doing a deliberate longitudinal review
- Candidate run through
skill_ledger.py checkbefore scoring; a repeat was dropped, not re-scored - Scoring agent given the skill version and the task only, never the ledger or the diagnosis
- Gate outcome recorded via
skill_ledger.py record, rejections included - Lesson about editing this skill recorded via
remember()
For the deeper "dispatch reflection/scoring to the Agent tool" recipe and the
adapted reflection/ranking prompt templates, see
references/skillopt-provenance.md.
© oaustegard, 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 3 other files (references) in optimizing-skills of oaustegard/claude-skills.
- SKILL.md
- CHANGELOG.md
- README.md
- references/skillopt-provenance.md
Open the folder on GitHubat commit cf49d47
Compare with similar skills
Optimizing Skills 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 |
|---|---|---|---|---|---|---|
| Optimizing Skills this skilloaustegard/claude-skills | 150 | — | ~2.3k | Automated safety check: Pass | MIT | |
| SQL Optimizationgithub/awesome-copilot | 40k | 2 repos | ~2.3k | Automated safety check: Pass | MIT | |
| Agent Performance Optimizerruvnet/ruflo | 74k | 2 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Database Optimizerdavila7/claude-code-templates | 32k | 8 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Prompt Optimizeraffaan-m/ECC | 276k | 2 repos | ~2.4k | Automated safety check: Pass | MIT | |
| Cost Optimizeruvnet/ruflo | 74k | — | ~997 | Automated safety check: Notes | MIT |
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Questions about Optimizing Skills
What does Optimizing Skills do?
Disciplined, validation-gated revision of an EXISTING skill so each edit is a measured improvement rather than a guess. Optimizing Skills is an agent skill from oaustegard/claude-skills. Disciplined, validation-gated revision of an EXISTING skill so each edit is a measured improvement rather than a guess.
When should I use Optimizing Skills?
Optimizing Skills fits situations like: tuning a skill that already exists and there is evidence it underperforms (observed failures; complaints) — invoke by name; have versioning-skills / creating-skill defer to it before applying edits.
How do I install Optimizing Skills in Claude Code?
Run `npx skills add oaustegard/claude-skills --skill optimizing-skills -a claude-code`. Or copy the skill folder (optimizing-skills in oaustegard/claude-skills) into .claude/skills/optimizing-skills in your project. Claude Code loads it when a task matches its description.
How do I install Optimizing Skills in Codex?
Run `npx skills add oaustegard/claude-skills --skill optimizing-skills -a codex`. Or copy the skill folder (optimizing-skills in oaustegard/claude-skills) into .agents/skills/optimizing-skills in your project. Codex loads it when a task matches its description.
Can I use Optimizing Skills 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 oaustegard/claude-skills --skill optimizing-skills -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/optimizing-skills, .gemini/skills/optimizing-skills, .github/skills/optimizing-skills and .opencode/skills/optimizing-skills in your project.
What does Optimizing Skills need to run?
Going by SKILL.md and its folder, Optimizing Skills needs the command-line tools its instructions call (python3). Our summary lists: Python 3.
Does Optimizing Skills 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 Optimizing Skills 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 Optimizing Skills use?
Optimizing Skills 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 Optimizing Skills use?
About 2.3k tokens (SKILL.md is roughly 9.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 812 tokens, read only when the agent opens those files.
What are the alternatives to Optimizing Skills?
Skills that share tags, products or a category with Optimizing Skills: SQL Optimization (github/awesome-copilot, 40k stars), Agent Performance Optimizer (ruvnet/ruflo, 74k stars), Database Optimizer (davila7/claude-code-templates, 32k stars) and Prompt Optimizer (affaan-m/ECC, 276k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Optimizing Skills?
oaustegard (a GitHub user) maintains it in oaustegard/claude-skills, which has 150 GitHub stars. The repository holds 66 skills in this directory. The repository was last updated on October 8, 2026.
Source: oaustegard/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.