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/luckenco-hillclimb
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What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
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Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/hillclimb
What's inside
- Skill name
hillclimb- Description
- Iteratively improve one measured metric against a target. Use for hillclimb, sustained performance optimization, or repeated experiments with keep/revert decisions.
- License
- MIT
- Instructions
- 16 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- opening-a-pr.md · references/
SKILL.md (first lines)
# Hillclimb **Own the metric and the experiment's integrity. Supervise and review; delegate attempts.** This is for sustained, iterative improvement of one measurable thing. A one-off fix is not a hillclimb. One change, one measurement, keep or revert. Never stack untested changes or claim a win from inspection alone. 1. **Ground.** Read and apply [`how`](../how/SKILL.md) to the target. Name realistic workload dimensions (data size, history, state, concurrency). Select a case that reproduces the user's complaint. If none does, fix the repro first. Choose one metric, its direction, and a stop predicate with a target **and a minimum number of attempts**. Use user-specified numbers; otherwise agree them before the loop. 2. **Freeze a sensitive harness.** Build one repeatable command that emits the metric. First show it separates contrasting realistic workloads, then freeze its workload and measurement method. Sample enough to clear noise (e.g. median of N runs). Record the baseline and a passing regression gate before changing code. 3. **Open the log.** Read and apply [`show-me-your-work`](../show-me-your-work/SKILL.md). Use its canonical `decisions.tsv` format and helper, one row per iteration. Put the attempt id, mechanism/hypothesis and change in `decision`/`why`; point `evidence` at a durable measurement artifact containing before, after, delta and gate result; record kept or reverted in `result`. Keep the log out of the repo by default and read it before each attempt. 4. **Hypothesize.** Each attempt must name a specific mechanism from the grounded architecture, not an unspecific tweak. 5. **Loop, one hypothesis per iteration.** Delegate the scoped change to a Pinnacle `subagent` task with explicit write tools (`read,grep,find,ls,bash,edit,write`). Review the actual diff. Parallel independent hypotheses require separately prepared Jujutsu workspaces or Git worktrees and separate baselines, not multiple writers in one tree. Measure before and after using the frozen harness; run the regression gate. Keep only a result past noise with the gate green. Otherwise revert that attempt in full, preserving unrelated changes. Commit each accepted fix separately with a conventional message, staging only changed files (in Git, `git add <paths>`, never `-A`; in Jujutsu, use a dedicated change and `jj new`). Log each attempt, kept or reverted. Verify one iteration before starting the next. 6. **Push past the first plateau.** After several rejects, pivot category, combine independently measured near-misses, re-read the source, or try a radical alternative. Correctness and simplicity outrank the number. Revert a win that breaks behavior; keep a simplification that holds the number. 7. **Stop honestly.** Stop at the agreed predicate, or when remaining ideas are marginal and not worth their cost. Do not relax the predicate or stop while cheap hypotheses remain. Surface a blocker rather than spinning. 8. **Prepare the PR.** Follow [`references/opening-a-pr.md`](references/opening-a-pr.md) with accepted commits in order. This is hillclimb's own PR path, not `visual-pr`. If pushing or PR creation was not explicitly authorized, prepare the description and ask before remote operations. **Reply:** metric and target, baseline → final with percent delta, iterations (kept/reverted), accepted fixes, `decisions.tsv` path, and the best remaining hypothesis. Include the measured command and regression gate.
From luckenco/pinnacle, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Oct 15, 2026 (13 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/luckenco/pinnacle
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
hillclimb skill. Agent Mart. https://agentmart.dev/skills/luckenco-hillclimb (last updated 2026-10-24)