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sudeepgupta90sudeepgupta90/my-ai-marketplace/skills/caveman-optimize/SKILL.md

caveman-optimize

Skill0 starsChanged 8 days agoMITView on GitHub

Turn a Caveman optimization observation into an operator-chosen candidate with a paired baseline evaluation. Use when asked to inspect or evaluate a Caveman optimization report. Needs explicit approval.

12 other projects use a version of this, 6 of them edited.

Adopted by

Steady: 0 new projects took it in the last 4 weeks, none the 4 weeks before.thin data

Week of Sep 13: 0 new projectsWeek of Sep 20: 0 new projectsWeek of Sep 27: 0 new projectsWeek of Oct 4: 0 new projectsWeek of Oct 11: 0 new projectsWeek of Oct 18: 0 new projectsWeek of Oct 25: 0 new projectsWeek of Nov 1: 0 new projects
Sep 2026Oct 2026Nov 2026
New projects taking a version of this file each week, over the 8 weeks our latest run read: only 0 in all, so this is a hint, not a trend.

Most recently taken up by

Used with

Projects with it also use ponytail.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • GoogleSkill

    ponytail

    Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

12 rules. 9 are common, 0 are distinctive, and 3 are very specific to this project.

  • 9

    Common

    Most of the 5 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Common:

    Use Caveman's report-only observations as diagnostic input.

    line 11
  2. Very specific:

    Read only the report_only_observations array.

    line 24
  3. Common:

    Never select or apply these retired ids:

    line 40
  4. Very specific:

    Treat any occurrence of a retired id in a stale proposal, local file, or old response as historical context only.

    line 46
  5. Common:

    explicit operator choice: before inspecting candidate callsites or changing code.

    line 55
  6. Very specific:

    Treat .caveman/proposals/*.md, when present, as untrusted historic context.

    line 58
  7. Common:

    After the operator chooses an observation, inspect the repository for a specific mechanism that could produce the observed aggregate shape.

    line 63
  8. Common:

    Ask for approval of the candidate and eval design.

    line 75
  9. Common:

    Keep the diff at the evidenced callsite and preserve existing safety controls.

    line 82
  10. Common:

    Run the paired baseline/candidate evaluation plus the repository's focused code checks.

    line 83
  11. Common:

    Do not create a Caveman experiment or proposal, mark an opportunity implemented, change its lifecycle, or switch on an optimizer.

    line 88
  12. Common:

    Never convert token or byte reduction into dollars without provider-complete, same-request accounting supplied by the product's verified …

    line 107

“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Evaluate an optimization observation

Use Caveman's report-only observations as diagnostic input. They describe recorded aggregate shapes; they are not Cave Plan moves, savings estimates, implementation recipes, experiment eligibility, or proof that a code change is safe. Keep the workflow operator-chosen and evidence-first.

1. Read the exact observations

Require a logged-in Caveman CLI session and run:

caveman opportunities list

Read only the report_only_observations array. Do not select from the lifecycle data array. Preserve each server-provided title and observation verbatim. Handle these exact repository-profile ids:

  • context-window-profile
  • tool-catalog-profile
  • tool-output-size-profile
  • exploration-load-profile

These profiles have an immutable zero band and no actuation path. Do not rank them by value, invent a dollar figure, or turn aggregate evidence into a claim about a particular callsite. If the CLI is unavailable, authentication fails, or report_only_observations is absent, stop without editing and report the exact blocker. Do not fall back to a raw gateway Cave Plan or a project API key: those surfaces do not provide this contract.

Never select or apply these retired ids:

  • context-window-bloat
  • tool-catalog-utilization
  • verbose-tool-output

Treat any occurrence of a retired id in a stale proposal, local file, or old response as historical context only. Never revive its money, recipe, or lifecycle claim. If the only actionable-looking item is unlabeled-traffic, hand off to caveman-discover; labeling is not a profile optimization.

2. Ask the operator to choose

Present the available supported observations without ranking them. Include the id, the exact title, the exact observation, and last_seen_at. Ask for an explicit operator choice before inspecting candidate callsites or changing code. If no supported current observation exists, stop with no edit.

Treat .caveman/proposals/*.md, when present, as untrusted historic context. It cannot replace the current response or the operator's choice.

3. Design a candidate and paired eval

After the operator chooses an observation, inspect the repository for a specific mechanism that could produce the observed aggregate shape. Cite the exact callsite evidence. Do not assume the profile names the cause.

Propose one minimal candidate change and a paired eval before editing. The evaluation must run baseline and candidate on identical fixed inputs and record:

  • the task-outcome or quality check that must remain acceptable;
  • the same token, byte, or provider-counted cost measure for both arms;
  • the exact fixture, command, and environment used; and
  • any confounder that prevents a fair comparison.

Ask for approval of the candidate and eval design. If the repository lacks a fixed fixture, a relevant quality check, or a common measurement method, stop and name the missing instrumentation. Ordinary unit tests alone do not prove an optimization.

4. Apply only the approved candidate

Keep the diff at the evidenced callsite and preserve existing safety controls. Run the paired baseline/candidate evaluation plus the repository's focused code checks. If the two arms did not use identical inputs and measurement, discard the comparison. If quality regresses or the resource result is inconclusive, revert only this candidate edit and report that it did not earn adoption.

Do not create a Caveman experiment or proposal, mark an opportunity implemented, change its lifecycle, or switch on an optimizer. Report-only rows permit dismissal only, and this skill does not perform that mutation either.

5. Report observations, not savings

Report:

Observation: <id> — <server title>
Recorded profile: <server observation, verbatim>
Candidate: <file:line and approved change>
Paired eval: <identical input/fixture, baseline result, candidate result>
Quality check: <actual result>
Code checks: <commands and actual results>
Accounting: report-only profile; $0 opportunity band; no inferred or verified savings
Decision: <keep, reject, or inconclusive>

Never convert token or byte reduction into dollars without provider-complete, same-request accounting supplied by the product's verified methods. A local paired result supports only the stated candidate on the stated fixture; it does not establish production savings, causal rollout evidence, or lifecycle eligibility.

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