optimize
Speeds up a codebase as far as it will go in one session, against a hard target (every primary benchmark at least 1.2x faster than the base commit by default)…
Skill by fblissjr
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/fblissjr-optimize
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/optimize
Tools it pre-approves 3
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
Bash(python3${CLAUDE_PLUGIN_ROOT}/scripts/loop_state.py*)
What's inside
- Skill name
optimize- Description
- Speeds up a codebase as far as it will go in one session, against a hard target (every primary benchmark at least 1.2x faster than the base commit by default) without regressing correctness, output quality or safety. Works with the repo's AGENTS.md sections (North star, Measurement, Loop state); base and branch worktrees, exact counts proven against wall-clock time, read-only reviewers one lens each, a re-check of every headline result on the final commit. User-invoked only, because a run spends hours and many subagents.
- License
- Apache-2.0
- Allowed tools
- Bash(python3, ${CLAUDE_PLUGIN_ROOT}/scripts/loop_state.py, *)
- Instructions
- 42 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves some shell commands
Files (2)
- SKILL.md
- optimizer-loop.md · references/
SKILL.md (first lines)
# Optimize
<run>
This skill is a standing prompt. The campaign is in
`${CLAUDE_SKILL_DIR}/references/optimizer-loop.md`. Read `common.md`, then the loop file, and execute it
as written: it is the instruction set for this run, not background.
</run>
<paths>
- Plugin root: `${CLAUDE_PLUGIN_ROOT}`
- This session's id: `${CLAUDE_SESSION_ID}`
- Shared rules: `${CLAUDE_PLUGIN_ROOT}/references/common.md`. Read it before the loop file.
- Loop-state script: `python3 ${CLAUDE_PLUGIN_ROOT}/scripts/loop_state.py`
- AGENTS.md template: `${CLAUDE_PLUGIN_ROOT}/templates/AGENTS.md`
</paths>
<parameters>
Start from the campaign's `<parameters>` block and apply these overrides from
the invocation: $ARGUMENTS
Record the resolved block at the top of the run record with the baseline. An
override that names no parameter goes under "Needs from me" rather than being
guessed into one.
</parameters>
<prerequisites>
- The campaign cites sections of the repo's AGENTS.md by name, above all
Measurement (real path, primary benchmarks, instruments, hazards). If they
are missing, the template is at the path above;
propose the fill under "Needs from me" rather than writing it yourself.
- If the primary benchmarks are unnamed, or their guardrails and
counter-checks are, recommend `/design-scoreboard` first. A speed target with
no quality guardrail is a number the campaign can reach by breaking things.
</prerequisites>
<after_compaction>
Re-read the campaign file and the run record before the next action. The
campaign's instructions do not survive compaction on their own; the record
does.
</after_compaction>From fblissjr/fb-claude-skills, Apache-2.0.
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Signals
- Stars
- 2
- Forks
- 1
- Open issues
- 0
- Last commit (this folder)
- Sep 24, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- Apache-2.0
- Repository
- github.com/fblissjr/fb-claude-skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Show an interactive dashboard of all tracked skills, plugins, and repo hygiene in this project.
SkillAFreshness: A★ 2Claude Code +9 - 0.563score
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Design and implement Kimball-style star schemas in DuckDB for LLM agent state persistence.
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MECE decomposition methodology, scoring rubrics, and Agent SDK mapping for process analysis.
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Cite this page
optimize skill. Agent Mart. https://agentmart.dev/skills/fblissjr-optimize (last updated 2026-10-24)