Cyclic shift execution engine. An agent skill from profbernardoj/everclaw-community-branches.

MITAuto-check passedProductivity & Automation

Install Three Shifts

skills CLI
$ npx skills add profbernardoj/everclaw-community-branches --skill three-shifts -a claude-code

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

GitHub CLI
$ gh skill install profbernardoj/everclaw-community-branches three-shifts --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/profbernardoj/everclaw-community-branches.git skills-src && mkdir -p .claude/skills && cp -r skills-src/three-shifts .claude/skills/three-shifts && 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
three-shifts
GitHub stars
112
Token cost
~4.2k tokens
SKILL.md length
1,161 words
Files
6 (incl. references)
Skills in repo
12
Repo updated
First seen
Licence
MIT

At a glance

Cyclic shift execution engine. An agent skill from profbernardoj/everclaw-community-branches.

  • Works in 3 steps: Planning (runs once per shift) → Cycle Execution (runs every 15 minutes) → Handoff (automatic when shift ends)
  • Tasks that involve Scheduled and recurring tasks
  • SKILL.md covers File Structure, Shifts, Phase 1: Planning (runs once… and Phase 2: Cycle Execution (runs…, plus 4 more sections
  • Calls git

What it does

Three Shifts is an agent skill from profbernardoj/everclaw-community-branches. Cyclic shift execution engine. Plans tasks 3x daily (6 AM, 2 PM, 10 PM), decomposes them into granular steps, then executes via 15-minute cron cycles. Each cycle reads state files, picks the next step, executes it, writes results back. Errors are logged and skipped — never fatal. Planning uses Claude 4.6; execution uses GLM-5.

Its SKILL.md is about 4.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including reference files (for example `references/config.md`, `templates/context.md` and `templates/handoff.md`).

It sits in Productivity & Automation, covering Scheduled and recurring tasks. It works with Zhipu GLM. The repository describes itself as: Decentralized AI inference for OpenClaw agents. Powered by Morpheus AI. Stake MOR, access Kimi K2.5 + 10 models, never run out of inference. The licence is MIT.

When your agent uses it

  • Tasks that involve Scheduled and recurring tasks

Example prompts

  • “/three-shifts”

Workflow steps

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

  1. Planning (runs once per shift)
  2. Cycle Execution (runs every 15 minutes)
  3. Handoff (automatic when shift ends)

What it can do on your machine

Read from SKILL.md and the folder at commit 0b30b36. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    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

Three Shifts loads about 4.2k tokens when it runs, and up to ~4.9k if it reads all its reference files. Until then it costs about 85 tokens; SKILL.md has 1,161 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
~4.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~4.9k

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 profbernardoj/everclaw-community-branches at commit 0b30b36, republished under its MIT licence (© profbernardoj). 1,161 words, ~4,178 tokens.

Download SKILL.mdSave it as .claude/skills/three-shifts/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
three-shifts
description
Cyclic shift execution engine. Plans tasks 3x daily (6 AM, 2 PM, 10 PM), decomposes them into granular steps, then executes via 15-minute cron cycles. Each cycle reads state files, picks the next step, executes it, writes results back. Errors are logged and skipped — never fatal. Planning uses Claude 4.6; execution uses GLM-5.
version
2.0.0

Three Shifts v2 — Cyclic Execution Engine

Architecture: Plan once → decompose → execute in 15-minute cycles → each cycle does ONE step → state persists in files between runs.

Why v2: V1 ran everything in one long session. One timeout killed the whole shift. V2 is a state machine — errors get logged, skipped, and retried. 32 cycles per shift, each learning from the last.


File Structure

All state lives in workspace/shifts/:

shifts/
├── tasks.md        # Current shift's step-by-step plan (the state machine)
├── context.md      # Stack, constraints, known pitfalls, learned lessons
├── handoff.md      # What the previous shift left behind
├── state.json      # Machine-readable shift metadata
└── history/        # Archived completed shifts
    └── YYYY-MM-DD-{shift}.md
tasks.md Format
markdown
# Afternoon Shift — 2026-02-22
Approved by: user | Approved at: 2:15 PM CST
Shift window: 2:00 PM – 10:00 PM CST
Cycles remaining: ~30

## Task 1: API migration plan [P1]
- [x] Step 1.1: Read current proxy-router config and session economics — DONE (cycle 1)
- [ ] Step 1.2: Research mor-[REDACTED] paid tier pricing and limits
- [!] Step 1.3: Compare cost of paid tier vs local-only — BLOCKED: need pricing from step 1.2
- [ ] Step 1.4: Draft transition recommendation in memory/projects/example/

## Task 2: Commit workspace changes [P1]
- [ ] Step 2.1: Run git status, identify logical commit groups
- [ ] Step 2.2: Stage and commit new skills (three-shifts, relationships)
- [ ] Step 2.3: Stage and commit memory reorganization files
- [ ] Step 2.4: Stage and commit scripts and config changes
- [ ] Step 2.5: Push to remote

## Summary
Total steps: 9 | Done: 1 | Blocked: 1 | Remaining: 7
Last cycle: 2026-02-22 14:15 CST — completed step 1.1
Next target: Step 1.2

Step markers:

  • [ ] — Not started (available for next cycle)
  • [x] — Completed (with cycle number and brief result)
  • [!] — Blocked (with reason — will be retried after dependencies clear)
  • [~] — In progress (claimed by current cycle, prevents double-execution)
  • [-] — Skipped (manually removed or deprioritized)
context.md Format
markdown
# Shift Context — Living Document

## Stack & Environment
- macOS arm64, OpenClaw 2026.2.21-2
- Git repos: ~/.openclaw/workspace
- 1Password for secrets (never store raw keys)
- Primary messaging channel for user comms

## Constraints
- Never force push or delete branches
- trash > rm (recoverable beats gone)
- Space Brave searches by 2+ seconds (rate limit)
- MiniMax-M2.5: DO NOT USE (broken streaming)
- Llama 3.3 70B: DO NOT USE

## Known Pitfalls (learned from experience)
- API-specific gotchas go here
- Check messaging connectivity if deliveries fail
- Check provider billing cooldown policies
- Always check git status before committing — avoid partial commits

## Rules for This Shift
- Night shift: no external comms, no financial txns, no destructive ops
- If blocked on user input, skip and note in handoff
- Max 1 web search per cycle (Brave rate limit)
state.json Format
json
{
  "shift": "afternoon",
  "date": "2026-02-22",
  "status": "executing",
  "startedAt": "2026-02-22T20:00:00Z",
  "approvedAt": "2026-02-22T20:15:00Z",
  "approvedBy": "user",
  "planModel": "your-heavy-model (e.g. Claude, GPT-4)",
  "execModel": "your-light-model (e.g. GLM-5, GPT-4o-mini)",
  "totalSteps": 9,
  "completed": 1,
  "blocked": 1,
  "skipped": 0,
  "cyclesRun": 1,
  "lastCycleAt": "2026-02-22T20:15:00Z",
  "nightAutoApproved": false,
  "carryoverFromShift": null
}

Shifts

ShiftPlan CronCycle CronsWindowCharacter
Morning6:00 AM6:15 AM – 1:45 PM (every 15 min)6 AM – 2 PMComms, decisions, user-facing
Afternoon2:00 PM2:15 PM – 9:45 PM (every 15 min)2 PM – 10 PMDeep work, building, coding
Night10:00 PM10:15 PM – 5:45 AM (every 15 min)10 PM – 6 AMAutonomous, research, maintenance

Phase 1: Planning (runs once per shift)

Model: your-heavy-model (e.g. Claude, GPT-4) (heavy model for quality planning)

When the planning cron fires:

1. Gather Context

Read these sources:

  • shifts/handoff.md — what last shift left behind
  • shifts/context.md — rules, constraints, pitfalls
  • shifts/state.json — previous shift stats
  • memory/daily/YYYY-MM-DD.md — today's activity
  • MEMORY.md — active projects, priorities, deadlines
  • Calendar (if available) — meetings in shift window
  • Email (if available) — urgent unreads
  • Git status of active repos
2. Check for Carryover

If shifts/tasks.md has incomplete [ ] or [!] steps from a previous shift:

  • Carry them forward into the new plan automatically
  • Mark them as [carryover] in the new plan
  • Night shift: if ALL remaining items were approved in morning/afternoon, auto-approve (no user ping needed)
3. Generate Shift Plan

Present to user in this format:

☀️/🌤️/🌙 [SHIFT] SHIFT PLAN
Date: [DATE] | Window: [START]–[END] [TZ]
Exec model: GLM-5 | Cycles: ~32

P1 (Must do):
1. [Task] — [Est. time] — [Why now]
2. ...

P2 (Should do):
3. ...

P3 (Could do):
5. ...

Blocked/Waiting:
- [Item] — [Blocker]

Carryover from last shift:
- [Item] — [Status]

Reply: "Approve" / "Approve all" / "Approve 1,3" / "Add: [task]" / "Skip"
4. On Approval — Auto-Decompose

This is the critical v2 step. After approval, before any execution begins:

  1. Take each approved task and break it into atomic steps that GLM-5 can execute in a single cycle (~10-12 minutes of work max per step)
  2. Each step must be:
    • Self-contained: Can be done without remembering previous cycles
    • Verifiable: Has a clear "done" condition
    • Small: One file edit, one command, one search, one commit — not five things
    • Context-light: The step description + context.md should be enough; no conversation history needed
  3. Write the decomposed plan to shifts/tasks.md
  4. Initialize shifts/state.json
  5. Start the cycle cron (or let the existing every-15-min cron pick it up)

Decomposition guidelines for GLM-5:

  • Prefer explicit commands over abstract instructions ("Run git status in your project dir" not "check the repo")
  • Include file paths, command snippets, expected outputs where possible
  • If a step requires a decision, split it: "Research X" → "Write recommendation to file" → separate step for user to review
  • Max 3 tool calls per step (keeps GLM-5 focused)
  • If a task has >8 steps, split it into two tasks
5. Night Shift Auto-Approve

If it's 10 PM and:

  • shifts/tasks.md has incomplete steps from today's morning or afternoon shifts
  • Those steps were already approved by the user earlier today
  • No new tasks need approval

Then:

  • Auto-approve the carryover items
  • Skip the user ping
  • Write "nightAutoApproved": true to state.json
  • Begin cycling immediately
  • Do NOT add new P1/P2 tasks without user approval (P3 autonomous tasks like cleanup/memory are OK)
User Approval Flow

When the user responds to a shift plan:

"Approve" / "Approve all":

  1. Read shifts/state.json — confirm status is awaiting_approval
  2. Set status to "executing", approvedAt to current ISO timestamp, approvedBy to the user's name`
  3. Write updated state.json
  4. The next cycle executor cron (every 15 min) will pick it up automatically

"Add: [task]":

  1. Decompose the new task into atomic steps (same rules as planning phase)
  2. Append the new steps to shifts/tasks.md
  3. Update totalSteps in state.json
  4. Then approve (set status to "executing")

"Skip":

  1. Set status to "cancelled" in state.json
  2. Write a note in shifts/handoff.md that the shift was skipped

No response after 30 minutes (morning/afternoon):

  • The planning cron already delivered the plan. If no approval comes, cycles will no-op (status stays awaiting_approval)
  • Next shift's planner will carry forward any planned tasks

Phase 2: Cycle Execution (runs every 15 minutes)

Model: your-light-model (e.g. GLM-5, GPT-4o-mini) (light model, cost-efficient)

Each cycle is an isolated session — no memory of previous cycles except what's in the files.

Show full SKILL.md (450 more words)Show less
Cycle Algorithm
1. READ shifts/state.json
   → If status is "completed", "cancelled", "idle", or "awaiting_approval": reply HEARTBEAT_OK (no-op)
   → If status is "executing": continue

2. READ shifts/tasks.md
   → Find first step marked [ ] (not started)
   → If none found, check for [!] (blocked) steps — retry if dependency cleared
   → If all steps are [x], [-], or still [!]: shift is DONE → go to Handoff

3. READ shifts/context.md
   → Load rules, constraints, pitfalls

4. CHECK FOR STALE CLAIMS
   → If any step is marked [~] (claimed by a previous cycle that crashed/timed out):
     - Change it back to [ ] — the previous cycle didn't finish
     - This step becomes the next available step to claim

5. CLAIM the step
   → Mark it [~] (in progress) in tasks.md
   → Write current timestamp to state.json

6. EXECUTE the step
   → Do the work (one focused action)
   → Stay within the step's scope — do NOT drift to other tasks

7. WRITE RESULTS back to tasks.md
   → Success: [x] Step N.N: description — DONE (cycle X): brief result
   → Blocked: [!] Step N.N: description — BLOCKED (cycle X): reason why
   → If blocked, check if next [ ] step has no dependency on this one → continue to it

8. UPDATE state.json
   → Increment cyclesRun, update completed/blocked counts, lastCycleAt

9. UPDATE shifts/context.md (if learned something new)
   → New pitfall discovered? Add it.
   → Found a useful command? Note it.
   → This is how cycles teach future cycles.

10. IF time permits in this cycle, take the NEXT available [ ] step
   → But only if the current step took <5 minutes
   → Never take more than 2 steps per cycle
Cycle Rules
  • One step at a time. Don't try to be clever and batch.
  • Errors are data, not failures. Log the error, mark blocked, move on.
  • Never ask the user mid-cycle. If you need user input, mark blocked and note what's needed.
  • Stay in scope. The step says "commit skill files" — don't also refactor the README.
  • Update context.md with lessons. This is how you teach the next cycle.
  • Respect quiet hours. Night cycles: no messages, no external comms.
  • Max 2 steps per cycle. Leave time for the next cycle to start clean.
Handling Blocks

When a step is blocked:

  1. Mark it [!] with a clear reason
  2. Check if the block is:
    • Dependency block (step 3 needs step 2's output): Skip, will retry when step 2 clears
    • User block (needs user input): Note in handoff, skip
    • External block (API down, service unavailable): Retry next cycle automatically
    • Error block (command failed): Log error in context.md, retry with different approach next cycle
  3. Move to the next available [ ] step
  4. Blocked steps get re-evaluated each cycle — if the blocker resolves, they become available again
Handling Retries

If a [!] step has been blocked for 3+ cycles:

  1. Write a note in context.md about the persistent failure
  2. Check if there's an alternative approach
  3. If the step has failed 5+ times, mark it [-] (skipped) and note in handoff for user review

Phase 3: Handoff (automatic when shift ends)

When all steps are [x], [-], or [!], OR when the shift window expires:

  1. Archive the shift:

    • Copy shifts/tasks.md → shifts/history/YYYY-MM-DD-{shift}.md
    • Include final state.json data as YAML frontmatter
  2. Write handoff.md:

markdown
# Handoff: Afternoon → Night | 2026-02-22

## Completed
- Task 1: API migration plan — recommendation written to memory/projects/example/
- Task 2 steps 1-3: Workspace commits (skills, memory reorg)

## Still In Progress
- Task 2 steps 4-5: Script commits and push (2 steps remaining)

## Blocked (needs user)
- Task 1 step 3: Need pricing confirmation for mor-[REDACTED] paid tier

## Lessons Learned This Shift
- GLM-5 handles git operations well but struggles with multi-file diffs
- Brave search rate limit hit on cycle 4 — added 3-second delay to context.md

## Recommendations for Next Shift
- Finish Task 2 push (quick, 1 cycle)
- Review migration recommendation in memory/projects/example/transition.md
  1. Update state.json: Set status to "completed"

  2. Update daily log: Append shift summary to memory/daily/YYYY-MM-DD.md

  3. Notify user (morning/afternoon only): Brief summary via messaging channel

    • Night shift: write summary but don't ping until morning planning cron

Cron Setup

Planning Crons (3 jobs — Claude 4.6)
Name: three-shifts-plan-morning
Schedule: cron 0 6 * * * (America/Chicago)
Model: your-heavy-model (e.g. Claude, GPT-4)
Session: isolated
Message: >
  Read the three-shifts skill at skills/three-shifts/SKILL.md.
  Execute Phase 1 (Planning) for the MORNING shift (6 AM – 2 PM CST).
  Read shifts/handoff.md, shifts/context.md, shifts/state.json, and recent memory files.
  Generate the shift plan and present for user approval.
  If carryover items exist from last night that were already approved, note them.
  After approval, decompose all tasks into atomic GLM-5-sized steps and write to shifts/tasks.md.

Name: three-shifts-plan-afternoon
Schedule: cron 0 14 * * * (America/Chicago)
Model: your-heavy-model (e.g. Claude, GPT-4)
Session: isolated
Message: >
  Read the three-shifts skill at skills/three-shifts/SKILL.md.
  Execute Phase 1 (Planning) for the AFTERNOON shift (2 PM – 10 PM CST).
  Read shifts/handoff.md, shifts/context.md, shifts/state.json, and recent memory files.
  Generate the shift plan and present for user approval.
  After approval, decompose all tasks into atomic GLM-5-sized steps and write to shifts/tasks.md.

Name: three-shifts-plan-night
Schedule: cron 0 22 * * * (America/Chicago)
Model: your-heavy-model (e.g. Claude, GPT-4)
Session: isolated
Message: >
  Read the three-shifts skill at skills/three-shifts/SKILL.md.
  Execute Phase 1 (Planning) for the NIGHT shift (10 PM – 6 AM CST).
  Read shifts/handoff.md, shifts/context.md, shifts/state.json, and recent memory files.
  IMPORTANT: If shifts/tasks.md has carryover items already approved today, auto-approve them
  and set state.json nightAutoApproved=true. Do NOT ping the user for already-approved carryover.
  Only present new tasks for approval.
  After approval (or auto-approve), decompose into atomic steps and write to shifts/tasks.md.
Execution Crons (1 job — GLM-5, runs every 15 min)
Name: three-shifts-cycle
Schedule: cron */15 * * * * (America/Chicago)
Model: your-light-model (e.g. GLM-5, GPT-4o-mini)
Session: isolated
Message: >
  You are a cycle executor for the three-shifts system.
  Read skills/three-shifts/SKILL.md Phase 2 (Cycle Execution) for your algorithm.
  Then read shifts/state.json — if status is not "executing", reply HEARTBEAT_OK.
  If executing: read shifts/tasks.md and shifts/context.md.
  Find the first [ ] step, claim it [~], execute it, write result back.
  If blocked, mark [!] with reason, move to next [ ] step.
  Update state.json and context.md as needed.
  Stay focused. One step. Write results. Done.

Configuration

See references/config.md for:

  • Customizing shift times
  • Weekend behavior
  • Quiet hours
  • Task categories and safety rules

Safety Rules

Always OK (any shift, any cycle)
  • Reading files, git status, web search
  • Writing to workspace files (tasks.md, context.md, memory/)
  • Running non-destructive commands
Requires Approval (via shift plan, not mid-cycle)
  • Sending emails, messages, social posts
  • Creating PRs, pushing code
  • Financial transactions
Never During Night Shift Cycles
  • External communications (messaging, email, social)
  • Financial transactions
  • Destructive operations (rm, force push, branch delete)
  • Security changes (key rotation, permissions)
  • New tasks not already approved
Cycle-Specific Safety
  • Never take more than 2 steps per cycle
  • Never exceed 12 minutes of execution per step
  • If a step seems dangerous, mark it [!] NEEDS_REVIEW instead of executing
  • Never modify context.md to remove safety rules
  • Never modify this SKILL.md during a cycle

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

Files

SKILL.md and 5 other files (references) in three-shifts of profbernardoj/everclaw-community-branches.

  • SKILL.md
  • references/config.md
  • templates/context.md
  • templates/handoff.md
  • templates/state.json
  • templates/tasks.md

Open the folder on GitHubat commit 0b30b36

Compare with similar skills

Three Shifts next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Three Shifts compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Three Shifts this skillprofbernardoj/everclaw-community-branches112—~4.2kAutomated safety check: PassMIT
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Cron Opsczl9707/build-your-own-openclaw1.9k—~593Automated safety check: PassMIT
Wp Wpcli And OpsAutomattic/agent-skills2112 repos~988Automated safety check: PassNone
Web Searchjjyaoao/HelloAgents3.2k1 repos~5.6kAutomated safety check: PassMIT
Superset Automatesuperset-sh/superset15k—~1.4kAutomated safety check: PassCustom licence

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Works with

Questions about Three Shifts

What does Three Shifts do?

Cyclic shift execution engine. An agent skill from profbernardoj/everclaw-community-branches. Three Shifts is an agent skill from profbernardoj/everclaw-community-branches. Cyclic shift execution engine.

When should I use Three Shifts?

Three Shifts fits situations like: tasks that involve Scheduled and recurring tasks.

How do I install Three Shifts in Claude Code?

Run `npx skills add profbernardoj/everclaw-community-branches --skill three-shifts -a claude-code`. Or copy the skill folder (three-shifts in profbernardoj/everclaw-community-branches) into .claude/skills/three-shifts in your project. Claude Code loads it when a task matches its description.

How do I install Three Shifts in Codex?

Run `npx skills add profbernardoj/everclaw-community-branches --skill three-shifts -a codex`. Or copy the skill folder (three-shifts in profbernardoj/everclaw-community-branches) into .agents/skills/three-shifts in your project. Codex loads it when a task matches its description.

Can I use Three Shifts 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 profbernardoj/everclaw-community-branches --skill three-shifts -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/three-shifts, .gemini/skills/three-shifts, .github/skills/three-shifts and .opencode/skills/three-shifts in your project.

What does Three Shifts need to run?

Going by SKILL.md and its folder, Three Shifts needs the command-line tools its instructions call (git).

Does Three Shifts 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 Three Shifts 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 Three Shifts use?

Three Shifts 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 Three Shifts use?

About 4.2k tokens (SKILL.md is roughly 17k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 719 tokens, read only when the agent opens those files.

What are the alternatives to Three Shifts?

Skills that share tags, products or a category with Three Shifts: Gh Issues (trpc-group/trpc-agent-go, 1.9k stars), Cron Ops (czl9707/build-your-own-openclaw, 1.9k stars), Wp Wpcli And Ops (Automattic/agent-skills, 211 stars) and Web Search (jjyaoao/HelloAgents, 3.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Three Shifts?

profbernardoj (a GitHub user) maintains it in profbernardoj/everclaw-community-branches, which has 112 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on September 2, 2026.

Source: profbernardoj/everclaw-community-branches on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.