Skip to content
Agentmart
Submit a tool

hillclimb

Iteratively improve one measured metric against a target.

Skill by luckenco

IndexedMIT
Write a review

Chalk Labs

Need help deploying hillclimb?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

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

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.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Iteratively improve one measured metric against a target. Use for hillclimb, sustained performance optimization, or repeated experiments with keep/revert decisions.

No 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/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.

Signals

Stars
0
Forks
0
Open issues
0
Last commit (this folder)
Oct 15, 2026 (16 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from luckenco

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get hillclimb running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying hillclimb?

CallGet help
Cite this page

hillclimb skill. Agent Mart. https://agentmart.dev/skills/luckenco-hillclimb (last updated 2026-10-24)