Evaluate-Loop Step 3: EXECUTE. An agent skill from Ibrahim-3d/orchestrator-supaconductor.

AGPL-3.0Auto-check passedTesting & QA

Install Loop Executor

skills CLI
$ npx skills add Ibrahim-3d/orchestrator-supaconductor --skill loop-executor -a claude-code

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

GitHub CLI
$ gh skill install Ibrahim-3d/orchestrator-supaconductor loop-executor --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/Ibrahim-3d/orchestrator-supaconductor.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/loop-executor .claude/skills/loop-executor && 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
loop-executor
GitHub stars
380
Token cost
~1.5k tokens
SKILL.md length
387 words
Files
1
Skills in repo
27
Repo updated
First seen
Licence
AGPL-3.0

At a glance

Evaluate-Loop Step 3: EXECUTE. An agent skill from Ibrahim-3d/orchestrator-supaconductor.

  • Works in 3 steps: read_file plan.md — find first [ ] task… → Confirm plan was evaluated (check for… → If no evaluation found → STOP → request…
  • Tasks that involve Test-driven development
  • SKILL.md covers Pre-Execution Checklist, Execution Protocol, Execution Summary and Metadata Checkpoint Updates, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Loop Executor is an agent skill from Ibrahim-3d/orchestrator-supaconductor. Evaluate-Loop Step 3: EXECUTE. Use this agent to implement tasks from a verified plan. Works through plan.md tasks sequentially, writes code, updates plan.md after every task, and commits at checkpoints. Uses TDD where applicable. Triggered by: 'execute plan', 'implement track', 'build feature', '/conductor implement' (execution phase). Only runs after plan has passed evaluation.

Its SKILL.md is about 1.5k 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 Testing & QA, covering Test-driven development and Planning. The repository describes itself as: Multi-agent orchestration system for Claude Code with parallel execution, automated quality gates, Board of Directors, and bundled Superpowers skills. The licence is AGPL-3.0.

When your agent uses it

  • Tasks that involve Test-driven development
  • Tasks that involve Planning

Example prompts

  • “execute plan”
  • “implement track”
  • “build feature”
  • “/loop-executor”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. read_file plan.md — find first [ ] task (skip all [x] tasks)
  2. Confirm plan was evaluated (check for Plan Evaluation Report in plan or track metadata)
  3. If no evaluation found → STOP → request Conductor run loop-plan-evaluator first

What it can do on your machine

Read from SKILL.md and the folder at commit 76c9b10. 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

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown and json).

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

  • Network

    No URLs in SKILL.md.

    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

Loop Executor loads about 1.5k tokens when it runs. Until then it costs about 99 tokens; SKILL.md has 387 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~1.5k

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 Ibrahim-3d/orchestrator-supaconductor at commit 76c9b10, republished under its AGPL-3.0 licence (© Ibrahim-3d). 387 words, ~1,489 tokens.

Download SKILL.mdSave it as .claude/skills/loop-executor/SKILL.md (or your agent's skills folder).
name
loop-executor
description
Evaluate-Loop Step 3: EXECUTE. Use this agent to implement tasks from a verified plan. Works through plan.md tasks sequentially, writes code, updates plan.md after every task, and commits at checkpoints. Uses TDD where applicable. Triggered by: 'execute plan', 'implement track', 'build feature', '/conductor implement' (execution phase). Only runs after plan has passed evaluation.

Loop Executor Agent — Step 3: EXECUTE

Implements the tasks defined in a verified plan.md. This agent writes code, creates files, and updates plan.md after every completed task.

Pre-Execution Checklist

Before writing any code:

  1. read_file plan.md — find first [ ] task (skip all [x] tasks)
  2. Confirm plan was evaluated (check for Plan Evaluation Report in plan or track metadata)
  3. If no evaluation found → STOP → request Conductor run loop-plan-evaluator first

Execution Protocol

For Each Task
1. Mark task [~] in plan.md (in progress)
2. read_file acceptance criteria
3. Implement the task
4. Verify acceptance criteria met
5. Update plan.md immediately:
   - Mark [x]
   - Add commit SHA
   - Add summary of what was done
6. Commit code changes
7. Move to next [ ] task
plan.md Update Format (MANDATORY after every task)
markdown
- [x] Task 3: Build signup form component <!-- abc1234 -->
  - Created src/components/auth/signup-form.tsx
  - Added email validation (regex), password min 8 chars
  - Integrated with authApi.signUp() from mock API client
  - Acceptance: ✅ Form renders, validates, submits
TDD Integration

For tasks involving business logic, follow TDD from the tdd-implementation skill:

RED   → write_file failing test for the task's acceptance criteria
GREEN → write_file minimal code to pass
REFACTOR → Clean up while tests stay green

Apply TDD to:

  • Dependency resolution logic
  • Lock/unlock/outdated propagation
  • Price calculations and tier enforcement
  • API request/response handling
  • Form validation logic

Skip TDD for:

  • CSS/styling tasks
  • Static content
  • Third-party library wrappers
Commit Protocol

Commit at these checkpoints:

  • After each completed task (with plan.md update in same commit)
  • After each completed phase
  • Message format: feat([scope]): [what was done]
Scope Discipline During Execution

While executing, if you discover work not in the plan:

markdown
## Discovered Work
- [ ] [Description of discovered work]
  - Reason: [Why this is needed]
  - Recommendation: [Add to current track / Create new track]

Add to plan.md under "Discovered Work" section. Do NOT silently implement it.

Business Doc Sync Awareness

While executing, if a task makes any of these changes, flag it for Step 5.5 (Business Doc Sync):

  • Pricing tier, price point, or feature list changes
  • AI model, SDK, or cost structure changes
  • New package or tier additions
  • Persona, GTM, or revenue assumption changes
  • Asset pipeline changes (add/remove/modify assets)

Add a note in the execution summary:

markdown
**Business Doc Sync Required**: Yes/No
**Reason**: [e.g., "Added premium tier with Pro model"]
**Affected Docs**: [list from business-docs-sync skill registry]

See ${CLAUDE_PLUGIN_ROOT}/skills/business-docs-sync/SKILL.md for the full sync registry and protocol.

Show full SKILL.md (143 more words)Show less
Error Handling During Execution

If a task cannot be completed:

  1. Mark task [!] with explanation
  2. Document the blocker in plan.md
  3. Continue with non-blocked tasks if possible
  4. Report blockers in execution summary

Execution Summary

After completing all tasks (or hitting a blocker):

markdown
## Execution Summary

**Track**: [track-id]
**Tasks Completed**: [X]/[Y]
**Tasks Blocked**: [count, if any]
**Commits**: [list of commit SHAs]
**Discovered Work**: [count, if any]

**Ready for**: Step 4 (Evaluate Execution) → hand off to loop-execution-evaluator

Metadata Checkpoint Updates

The executor MUST update the track's metadata.json at key points:

On Start
json
{
  "loop_state": {
    "current_step": "EXECUTE",
    "step_status": "IN_PROGRESS",
    "step_started_at": "[ISO timestamp]",
    "checkpoints": {
      "EXECUTE": {
        "status": "IN_PROGRESS",
        "started_at": "[ISO timestamp]",
        "agent": "loop-executor",
        "tasks_completed": 0,
        "tasks_total": "[count from plan.md]",
        "commits": []
      }
    }
  }
}
After Each Task (Critical for Resumption)
json
{
  "loop_state": {
    "checkpoints": {
      "EXECUTE": {
        "status": "IN_PROGRESS",
        "tasks_completed": 3,
        "tasks_total": 10,
        "last_task": "Task 1.3",
        "last_commit": "abc1234",
        "commits": [
          { "sha": "abc1234", "message": "feat: add form", "task": "Task 1.3" }
        ]
      }
    }
  }
}
On Completion
json
{
  "loop_state": {
    "current_step": "EVALUATE_EXECUTION",
    "step_status": "NOT_STARTED",
    "checkpoints": {
      "EXECUTE": {
        "status": "PASSED",
        "completed_at": "[ISO timestamp]",
        "tasks_completed": 10,
        "tasks_total": 10,
        "last_task": "Task 3.2",
        "last_commit": "def5678",
        "commits": [...]
      },
      "EVALUATE_EXECUTION": {
        "status": "NOT_STARTED"
      }
    }
  }
}
Update Protocol
  1. read_file current metadata.json at start
  2. Update tasks_completed, last_task, last_commit after EACH task
  3. On completion: Advance current_step to EVALUATE_EXECUTION
  4. write_file back to metadata.json
Resumption Support

If executor is restarted mid-execution:

  1. read_file metadata.json.checkpoints.EXECUTE.last_task
  2. Find that task in plan.md
  3. Continue from the NEXT [ ] task after the last completed one
  4. Do NOT re-execute [x] tasks

Handoff

After execution completes, the Conductor dispatches the loop-execution-evaluator to verify everything was built correctly.

© Ibrahim-3d, AGPL-3.0. 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 skills/loop-executor of Ibrahim-3d/orchestrator-supaconductor.

Open the folder on GitHubat commit 76c9b10

Compare with similar skills

Loop Executor 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.

Loop Executor compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Loop Executor this skillIbrahim-3d/orchestrator-supaconductor380—~1.5kAutomated safety check: PassAGPL-3.0
Conductor Implementaiskillstore/marketplace4306 repos~2.1kAutomated safety check: PassNone
Deep Planpiercelamb/deep-plan101—~4.8kAutomated safety check: PassMIT
Plan Py4vaspvasp-dev/py4vasp100—~2.2kAutomated safety check: PassApache-2.0
Test-First Implementation Plangittower/git-flow-next458—~1.3kAutomated safety check: NotesCustom licence
Writing PlansProgrammerAnthony/Expert-Coding-Harness235—~876Automated safety check: PassMIT

Similar skills

  • Conductor Implement

    aiskillstore/marketplace

    Execute tasks from a track's implementation plan following TDD workflow

    430 GitHub starsUsed in 6 repos~2.1k tokens
    Testing & QAAuto-check passed
  • Deep Plan

    piercelamb/deep-plan

    Creates detailed, sectionized, TDD-oriented implementation plans through research, stakeholder interviews, and multi-LLM review.

    101 GitHub stars~4.8k tokensUpdated 3 mo ago
    Agent WorkflowsAuto-check passed
  • Plan Py4vasp

    vasp-dev/py4vasp

    Plan a py4vasp change as an ordered list of test-first chunks — that chunk list is the plan.

    100 GitHub stars~2.2k tokensUpdated yesterday
    Agent WorkflowsAuto-check passed
  • Test-First Implementation Plan

    gittower/git-flow-next

    Builds a two-phase implementation plan from a spec issue, analysis or concept, writing a detailed test plan first and the implementation outline second.

    458 GitHub stars~1.3k tokensUpdated 29 days ago
    Agent WorkflowsAuto-check: notes
  • Writing Plans

    ProgrammerAnthony/Expert-Coding-Harness

    A skill your agent uses when 已有经批准的设计/规格说明、多步骤实施任务,在动代码之前需要可执行任务清单时。触发场景:写实施计划、拆解开发任务、implementation plan、执行计划文档、任务拆分、按 TDD 步骤写计划。

    235 GitHub stars~876 tokensUpdated 4 mo ago
    Agent WorkflowsAuto-check passed
  • Solo Build

    LeoYeAI/openclaw-master-skills

    Execute implementation plan tasks with TDD workflow, auto-commit, and phase gates.

    2.2k GitHub stars~4.6k tokensUpdated 2 mo ago
    Agent WorkflowsAuto-check: notes

More from Ibrahim-3d/orchestrator-supaconductor

All 27 skills in this repo
  • Cto Advisor

    Ibrahim-3d/orchestrator-supaconductor

    Technical leadership guidance for engineering teams, architecture decisions, and technology strategy.

    380 GitHub starsUsed in 4 repos~2.4k tokens
    Auto-check passed
  • Context Driven Development

    Ibrahim-3d/orchestrator-supaconductor

    A skill your agent uses when working with Conductor's context-driven development methodology, managing project context artifacts, or understanding the relationship between product.md, tech-stack.md…

    380 GitHub starsUsed in 8 repos~2.9k tokens
    Auto-check passed
  • Agent Factory

    Ibrahim-3d/orchestrator-supaconductor

    Creates specialized worker agents dynamically from templates.

    380 GitHub stars~2.9k tokensUpdated 10 days ago
    Auto-check passed
  • Board Of Directors

    Ibrahim-3d/orchestrator-supaconductor

    Simulate a 5-member expert board deliberation for major decisions.

    380 GitHub stars~1.9k tokensUpdated 10 days ago
    Auto-check passed
  • Business Docs Sync

    Ibrahim-3d/orchestrator-supaconductor

    A skill your agent uses when completing a track that changes pricing, AI models, product features, or asset pipelines — syncs business context documents across all tiers.

    380 GitHub stars~2.1k tokensUpdated 10 days ago
    Auto-check passed
  • Context Loader

    Ibrahim-3d/orchestrator-supaconductor

    Load project context efficiently for Conductor workflows. An agent skill from Ibrahim-3d/orchestrator-supaconductor.

    380 GitHub stars~830 tokensUpdated 10 days ago
    Auto-check passed

Categories

Questions about Loop Executor

What does Loop Executor do?

Evaluate-Loop Step 3: EXECUTE. An agent skill from Ibrahim-3d/orchestrator-supaconductor. Loop Executor is an agent skill from Ibrahim-3d/orchestrator-supaconductor. Evaluate-Loop Step 3: EXECUTE.

When should I use Loop Executor?

Loop Executor fits situations like: tasks that involve Test-driven development; tasks that involve Planning.

How do I install Loop Executor in Claude Code?

Run `npx skills add Ibrahim-3d/orchestrator-supaconductor --skill loop-executor -a claude-code`. Or copy the skill folder (skills/loop-executor in Ibrahim-3d/orchestrator-supaconductor) into .claude/skills/loop-executor in your project. Claude Code loads it when a task matches its description.

How do I install Loop Executor in Codex?

Run `npx skills add Ibrahim-3d/orchestrator-supaconductor --skill loop-executor -a codex`. Or copy the skill folder (skills/loop-executor in Ibrahim-3d/orchestrator-supaconductor) into .agents/skills/loop-executor in your project. Codex loads it when a task matches its description.

Can I use Loop Executor 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 Ibrahim-3d/orchestrator-supaconductor --skill loop-executor -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/loop-executor, .gemini/skills/loop-executor, .github/skills/loop-executor and .opencode/skills/loop-executor in your project.

What does Loop Executor need to run?

SKILL.md names no scripts, command-line tools or credentials: Loop Executor is instructions for the agent only.

Does Loop Executor access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Loop Executor 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 Loop Executor use?

Loop Executor is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Loop Executor use?

About 1.5k tokens (SKILL.md is roughly 6k 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 Loop Executor?

Skills that share tags, products or a category with Loop Executor: Conductor Implement (aiskillstore/marketplace, 430 stars), Deep Plan (piercelamb/deep-plan, 101 stars), Plan Py4vasp (vasp-dev/py4vasp, 100 stars) and Test-First Implementation Plan (gittower/git-flow-next, 458 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Loop Executor?

Ibrahim-3d (a GitHub user) maintains it in Ibrahim-3d/orchestrator-supaconductor, which has 380 GitHub stars. The repository holds 27 skills in this directory. The repository was last updated on September 27, 2026.

Source: Ibrahim-3d/orchestrator-supaconductor on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.