Agent skill

Cavekit Revision

by JuliusBrussee in JuliusBrussee/caveman-code

Trace bugs and manual fixes back to kits and prompts; fix at the source so the iteration loop can reproduce the fix autonomously.

MITAuto-check passedDevelopment

Install Cavekit Revision

skills CLI
$ npx skills add JuliusBrussee/caveman-code --skill cavekit-revision -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install JuliusBrussee/caveman-code cavekit-revision --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/JuliusBrussee/caveman-code.git skills-src && mkdir -p .claude/skills && cp -r skills-src/packages/coding-agent/skills/cavekit-revision .claude/skills/cavekit-revision && rm -rf skills-src

Use ~/.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/

Facts

Skill name
cavekit-revision
GitHub stars
942
Token cost
~3.6k tokens
SKILL.md length
1,328 words
Files
1
Skills in repo
6
Repo updated
First seen
Licence
MIT

At a glance

Trace bugs and manual fixes back to kits and prompts; fix at the source so the iteration loop can reproduce the fix autonomously.

  • Works in 7 steps: Why Revision Matters → The 6-Step Revision Process → Revision Analysis (Automated) → …
  • A manual hot-fix has been applied
  • SKILL.md covers 1. Why Revision Matters, 2. The 6-Step Revision Process, 3. Revision Analysis (Automated) and 4. Patterns and Anti-Patterns, plus 4 more sections
  • Calls git

What it does

Cavekit Revision is an agent skill from JuliusBrussee/caveman-code. Trace bugs and manual fixes back to kits and prompts; fix at the source so the iteration loop can reproduce the fix autonomously. Six-step revision process plus the single-failure backpropagation protocol. Use when a manual hot-fix has been applied, when convergence stalls, or when the same class of bug keeps reappearing.

Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Development. The repository describes itself as: Frozen — terminal coding agent measured at 1.93× fewer tokens than Codex CLI. Still works; active development moved to JuliusBrussee/caveman (caveman wrap). The licence is MIT.

When your agent uses it

  • A manual hot-fix has been applied
  • Convergence stalls
  • The same class of bug keeps reappearing

Example prompts

  • “/cavekit-revision”

Requirements

  • Pre-approved tools (allowed-tools): read, grep, bash

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Why Revision Matters
  2. The 6-Step Revision Process
  3. Revision Analysis (Automated)
  4. Patterns and Anti-Patterns
  5. When NOT to Revise
  6. Revision and Convergence
  7. Integration with Other Cavekit Skills

What it can do on your machine

Read from SKILL.md and the folder at commit 3a21be1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • read
    • grep
    • bash

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Cavekit Revision loads about 3.6k tokens when it runs. Until then it costs about 85 tokens; SKILL.md has 1,328 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~85
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k

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 JuliusBrussee/caveman-code at commit 3a21be1, republished under its MIT licence (© JuliusBrussee). 1,328 words, ~3,631 tokens.

Download SKILL.mdSave it as .claude/skills/cavekit-revision/SKILL.md (or your agent's skills folder).
name
cavekit-revision
description
Trace bugs and manual fixes back to kits and prompts; fix at the source so the iteration loop can reproduce the fix autonomously. Six-step revision process plus the single-failure backpropagation protocol. Use when a manual hot-fix has been applied, when convergence stalls, or when the same class of bug keeps reappearing.
allowed-tools
read, grep, bash
effort
medium

Revision: Tracing Bugs Back to Kits

In Cavekit, revision means tracing a production defect upstream through the cavekit chain until you find the gap that allowed it. In practice, when the built software has bugs or gaps, you trace the issue back to the kits and prompts and fix at the source -- not just in code.

Key insight: When a fix lives only in code with no corresponding cavekit update, the next iteration loop may reintroduce the same defect. The goal is that kits plus the iteration loop can reproduce any fix autonomously.


1. Why Revision Matters

Without revision, every bug fix is a one-off patch. The next time the iteration loop runs, it may reintroduce the bug because nothing in the kits or plans prevents it.

With revision:

  • Bug fixes become cavekit improvements that persist across all future iterations
  • The iteration loop becomes self-correcting -- it learns from every manual intervention
  • Kits become progressively more complete over time
  • The gap between "what kits describe" and "what works" shrinks monotonically
Without revision:
  Bug found -> Fix code -> Bug may return next iteration

With revision:
  Bug found -> Fix code -> Update cavekit -> Re-run iteration loop -> Fix emerges from kits alone

2. The 6-Step Revision Process

This is the complete process for tracing a bug back to its cavekit-level root cause and closing the loop.

Step 1: Identify and Fix the Defect

Locate the bug -- whether through manual testing, automated failures, user reports, or monitoring alerts -- and resolve it through normal debugging. This produces a working code change, but the job is far from done: until the underlying cavekit gap is closed, this fix is fragile.

bash
# The fix produces commits that we will analyze
git log --oneline -5
# a1b2c3d Fix: connection pool exhaustion under concurrent load
# e4f5g6h Fix: missing rate limit headers in API responses
Step 2: Analyze What the Cavekit Missed

This is the pivotal step. Ask: "Where in the cavekit chain did this requirement slip through?"

Break the analysis into five dimensions:

  • WHAT changed (files, functions, observable behavior)
  • WHY it was wrong (which assumption proved false)
  • VISUAL — does this fix change visual appearance (CSS, styling, layout)? If yes, check whether DESIGN.md covers the pattern. A missing design pattern is a design system gap that should be fixed alongside the cavekit gap.
  • The RULE (the invariant that should have been stated)
  • The LAYER (which cavekit, plan, or prompt should have contained this)

Example analysis:

markdown
## Revision Analysis: Database Connection Pooling

**WHAT changed:** Added pool size limits and idle timeout in `src/db/pool.ts`
**WHY:** The data layer cavekit assumed unlimited connections; under load the database
         rejected new connections once the server-side limit was reached
**RULE:** "The database module MUST configure a bounded connection pool with
          idle timeout and max-connection limits matching the deployment target"
**LAYER:** cavekit-data.md (no mention of pool configuration), plan-data.md (no task for pool tuning)
**Cavekit implications:** Add requirement R5 to cavekit-data.md covering connection pool settings
Step 3: Update the Cavekit

Add the missing requirement or constraint to the appropriate cavekit file. Focus on acceptance criteria that are concrete enough for the iteration loop to act on:

markdown
# In context/kits/cavekit-data.md, add:

### R5: Database Connection Pool Configuration
**Description:** The database module must use a bounded connection pool
with configurable limits to prevent resource exhaustion under load.
**Acceptance Criteria:**
- [ ] Maximum pool size is configurable and defaults to a sensible value
- [ ] Idle connections are reaped after a configurable timeout
- [ ] Pool exhaustion returns a clear error rather than hanging indefinitely
- [ ] Connection health checks run before returning a connection from the pool
**Dependencies:** R1 (database client setup), R2 (environment configuration)
Step 4: Propagate Changes to Plans and Tracking

Trace the cavekit update through every downstream context file:

  1. Identify affected plan files: Which plans govern the changed source paths?
  2. Update plans: Add or close tasks reflecting the new requirement.
  3. Update impl tracking: Record the revision event and its root cause.
  4. Annotate: Mark updated sections with revision metadata so future reviews can trace lineage.
markdown
# In context/plans/plan-data.md, add:

### T-DATA-005: Configure bounded connection pool
- **Status:** DONE (revised from manual fix a1b2c3d)
- **Cavekit:** R5 in cavekit-data.md
- **Files:** src/db/pool.ts
- **Acceptance criteria:**
  - [ ] Max pool size enforced
  - [ ] Idle timeout configured
  - [ ] Exhaustion handled gracefully
Step 5: Apply Systemic Prompt Improvements (If Pattern Detected)

When the defect represents a recurring class of problem rather than a one-off, elevate the fix to the prompt level so it applies across all domains:

Signs you are looking at a pattern:

  • The same category of bug has surfaced in more than one module
  • The gap is structural (e.g., no specs anywhere address resource limits)
  • A missing validation gate allowed the issue through

Example systemic fix:

markdown
# In prompt 003, add to the validation section:

## Resource Management Validation
For every external resource integration, verify:
- [ ] Connection or handle limits are bounded and configurable
- [ ] Idle resources are cleaned up on a timeout
- [ ] Exhaustion scenarios return actionable errors
- [ ] Resource lifecycle is covered by tests under load
Step 6: Verify and Lock In

Run the iteration loop against the updated kits to prove the fix emerges from kits alone, then generate regression tests to prevent future recurrence:

bash
# Proof step: remove the manual fix and re-run from specs
git stash  # temporarily remove the manual fix
iteration-loop context/prompts/003-generate-impl-from-plans.md -n 5 -t 1h
# Verify the fix appears in the generated implementation

# If it does NOT, the cavekit update is insufficient -- return to Step 3

Once verified, create regression tests:

bash
# Generate tests targeting the updated cavekit
{TEST_COMMAND} --cavekit context/kits/cavekit-data.md

# Or manually create a regression test
# tests/db/connection-pool-limits.test.ts

The regression tests should:

  • Map directly to the acceptance criteria from Step 3
  • Fail if the fix is reverted
  • Run as part of the standard test suite going forward

3. Revision Analysis (Automated)

The revision analysis automates Steps 2-4 by examining recent git history.

3.1 Classify Commits

Analyze recent commits and classify each as:

ClassificationMeaningAction
Manual fixHuman or interactive agent fixed a bugTrace back to cavekit -- this is a revision target
Iteration loopAutomated iteration loop made the changeNo action -- this is the system working as intended
InfrastructureBuild config, CI, tooling changesNo action -- not cavekit-related

How to classify:

  • Commits from iteration loop sessions have predictable patterns (automated commit messages, batch changes)
  • Manual fixes are typically single-issue, focused commits with descriptive messages
  • Infrastructure changes touch config files, build scripts, CI pipelines
3.2 Analyze Each Manual Fix

For each commit classified as a manual fix, determine:

markdown
## Commit: abc1234 "Fix: auth token not refreshing on 401"

### WHAT changed
- File: src/auth/client.ts
- Function: handleApiResponse()
- Behavior: Added 401 detection and token refresh logic

### WHY it was wrong
- The auth module did not handle 401 responses
- Tokens would expire and never refresh, causing cascading auth failures

### RULE (invariant that should have been specified)
- "Authentication tokens must be refreshed automatically on 401 responses"

### LAYER (which context file should have caught this)
- cavekit-auth.md: Missing requirement for error-based token refresh
- plan-auth.md: No task for 401 handling

### Cavekit Implications
- Add R7 to cavekit-auth.md: Token Refresh on Authentication Failure
- Add T-AUTH-007 to plan-auth.md: Implement token refresh on 401
3.3 Discover Affected Plan Files

Dynamically discover which plan files govern the changed source paths:

Changed file: src/auth/client.ts
  -> Matches pattern: src/auth/*
  -> Governed by: plan-auth.md
  -> Cavekit: cavekit-auth.md

Changed file: src/data/api.ts
  -> Matches pattern: src/data/*
  -> Governed by: plan-data.md
  -> Cavekit: cavekit-data.md

Use file ownership tables (from prompts) or directory conventions to map source files to plan/cavekit files.

3.4 Update Context Files

For each revision target, update:

  1. Cavekit file: Add missing requirement with acceptance criteria
  2. Plan file: Add task referencing the new requirement
  3. Impl tracking: Record the revision event
markdown
# In context/impl/impl-auth.md, add:

## Revision Log
| Date | Commit | Issue | Cavekit Update | Plan Update |
|------|--------|-------|-------------|-------------|
| 2026-03-14 | abc1234 | 401 not handled | R7 added to cavekit-auth.md | T-AUTH-007 added |
3.5 Run Tests

After updating context files, run the test suite to verify nothing broke:

bash
{BUILD_COMMAND}
{TEST_COMMAND}
Show full SKILL.md (545 more words)Show less
3.6 Generate Regression Tests

For each revision target, generate a regression test that:

  • Tests the specific acceptance criteria from the new cavekit requirement
  • Would fail if the fix were reverted
  • Is included in the standard test suite going forward

4. Patterns and Anti-Patterns

Signs the process is working
PatternWhat You Observe
Declining manual interventionEach iteration cycle requires fewer hand-applied fixes because kits capture more of the ground truth
Broader cavekit coverage per fixA single revision event adds constraints that block an entire family of related defects, not just one
Cross-domain preventionPrompt-level adjustments made after a bug in one module prevent analogous bugs from appearing in other modules
Autonomous reproducibilityAfter a cavekit update, the iteration loop independently produces the same correction that a human applied manually
Warning signs and remedies
Anti-PatternSymptomRemedy
Code-only patchesThe same category of defect resurfaces across iterationsFollow the full 6-step process; never stop after the code fix in Step 1
Overly specific cavekit additionsEach revision prevents only the exact bug encountered, while slight variations slip throughFormulate the RULE as a general invariant, not a narrow patch
Skipping verificationKits are updated but nobody confirms the iteration loop can reproduce the fix independentlyAlways execute Step 6; a cavekit that does not drive correct generation is incomplete
Brittle over-specificationKits dictate implementation minutiae, causing breakage on minor refactorsConstrain the WHAT and WHY; leave the HOW to the implementation
Accumulated revision debtA backlog of manual fixes sits un-traced, growing with each sprintSet a cadence (e.g., end of each iteration) to clear the backlog; debt compounds quickly

5. When NOT to Revise

Not every code fix needs revision:

  • One-off environment issues (wrong config, missing dependency) -- these are infrastructure, not cavekit gaps
  • Typos and formatting -- trivial fixes that do not reflect missing requirements
  • Exploratory changes during prototyping -- kits are still being formed
  • Performance optimizations that do not change behavior -- unless performance is a cavekit requirement

Rule of thumb: If the iteration loop could plausibly reintroduce the bug, revise. If not, skip it.


6. Revision and Convergence

Revision directly improves convergence:

Iteration 1: 350 lines changed, 8 manual fixes needed
  -> Revise all 8 fixes into kits
Iteration 2: 140 lines changed, 3 manual fixes needed
  -> Revise 3 fixes
Iteration 3: 30 lines changed, 1 manual fix needed
  -> Revise 1 fix
Iteration 4: 10 lines changed, 0 manual fixes needed
  -> Convergence achieved

Every revision cycle tightens the kits, so the iteration loop settles into a stable solution in fewer passes. If convergence is not improving, the most likely cause is that manual fixes are being applied without tracing them back to kits.

Stalled convergence paired with ongoing manual fixes is a clear sign of revision debt. The kits have not absorbed the lessons from past corrections, so the loop keeps regenerating flawed output that demands human repair.


7. Integration with Other Cavekit Skills

  • Convergence monitoring: Use ck:convergence-monitoring to detect when manual fixes are decreasing (good) or increasing (revision debt).
  • Prompt pipeline: Revision may trigger changes to prompts (Step 6), which affects the ck:prompt-pipeline design.
  • Validation-first design: Stronger validation gates catch issues earlier, reducing the need for revision.
  • Gap analysis: Systematic gap analysis (/ck:scan) identifies revision targets proactively, rather than waiting for bugs.

Cross-References

  • Convergence patterns: See references/convergence-patterns.md for how revision drives convergence.
  • Prompt pipeline: See ck:prompt-pipeline skill for how prompt 006 (rewrite pattern) implements automated revision.
  • Impl tracking: See ck:impl-tracking skill for the revision log format in implementation tracking documents.
  • Validation gates: See ck:validation-first skill for validation layers that catch issues before they require revision.

© JuliusBrussee, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in packages/coding-agent/skills/cavekit-revision of JuliusBrussee/caveman-code.

Open the folder on GitHubat commit 3a21be1

Compare with similar skills

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Categories

Questions about Cavekit Revision

What does Cavekit Revision do?

Trace bugs and manual fixes back to kits and prompts; fix at the source so the iteration loop can reproduce the fix autonomously. Cavekit Revision is an agent skill from JuliusBrussee/caveman-code. Trace bugs and manual fixes back to kits and prompts; fix at the source so the iteration loop can reproduce the fix autonomously.

When should I use Cavekit Revision?

Cavekit Revision fits situations like: A manual hot-fix has been applied; convergence stalls; the same class of bug keeps reappearing.

How do I install Cavekit Revision in Claude Code?

Run `npx skills add JuliusBrussee/caveman-code --skill cavekit-revision -a claude-code`. Or copy the skill folder (packages/coding-agent/skills/cavekit-revision in JuliusBrussee/caveman-code) into .claude/skills/cavekit-revision in your project. Claude Code loads it when a task matches its description.

How do I install Cavekit Revision in Codex?

Run `npx skills add JuliusBrussee/caveman-code --skill cavekit-revision -a codex`. Or copy the skill folder (packages/coding-agent/skills/cavekit-revision in JuliusBrussee/caveman-code) into .agents/skills/cavekit-revision in your project. Codex loads it when a task matches its description.

Can I use Cavekit Revision 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 JuliusBrussee/caveman-code --skill cavekit-revision -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cavekit-revision, .gemini/skills/cavekit-revision, .github/skills/cavekit-revision and .opencode/skills/cavekit-revision in your project.

What does Cavekit Revision need to run?

Going by SKILL.md and its folder, Cavekit Revision needs the command-line tools its instructions call (git). Its frontmatter pre-approves these tools: read, grep, bash.

Does Cavekit Revision access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Cavekit Revision 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 Cavekit Revision use?

Cavekit Revision 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 Cavekit Revision use?

About 3.6k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Cavekit Revision?

Skills that share tags, products or a category with Cavekit Revision: Vercel Composition Patterns (supabase/supabase, 111k stars), Finishing a Development Branch (obra/superpowers, 297k stars), Typescript Advanced Types (rolling-scopes/rsschool-app, 10k stars) and PR Babysitter (openinterpreter/openinterpreter, 69k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cavekit Revision?

JuliusBrussee (a GitHub user) maintains it in JuliusBrussee/caveman-code, which has 942 GitHub stars. The repository holds 6 skills in this directory. The repository was last updated on August 14, 2026.

Source: JuliusBrussee/caveman-code on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.