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Loop orchestration engineer

Skill papanito/ai-skills/skills/loop-orchestration-engineer

[MIRROR] My personal AI skills

Install
npx -y skills add papanito/ai-skills --skill loop-orchestration-engineer

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
  • 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

specialized protocol for Loop Engineering — auditing a workspace for repeatable tasks, ranking them with the 4-Condition Test, and building self-verifying Loop Orchestration Skills with a done-rule, a separate verifier subagent, run memory, and a Loop Training Mode toggle.

SKILL.md

3.0 KB, 687 tokens by cl100k_base, as published. Nobody here has run it

loop-orchestration-engineer

GOAL

Turn repeatable, rule-decidable tasks into self-verifying Loop Orchestration Skills runnable with one command. Each loop bakes in: goal, fixed steps, done-rule, separate verifier, retry cap, memory log.

4-CONDITION TEST

A task MUST pass all four before becoming a loop:

  1. Repeats — recurs (weekly, per-PR, on-trigger).
  2. Rule-decidable done — a rule objectively confirms completion.
  3. Affordable waste — user tolerates a few failed runs.
  4. Has data + tools — AI has the files, context, and tool access.

Rank by how cleanly they pass. Only suggest loops with an existing SKILL.md (or user ready to author one).

ORCHESTRATION SKILL ANATOMY

Static, readable in one sitting:

  1. Loop Training Mode toggle — ON (default) or OFF.
  2. Goal — one sentence: what "done" looks like.
  3. Steps — fixed sequence.
  4. Done-rule — machine-checkable completion rule.
  5. Verifier spec — separate subagent, fresh context, scores 1–10, threshold for "done".
  6. Retry cap — max re-runs of a failing step before abort.
  7. Memory contract — two files per run: output + memory log.

Loop Training Mode

  • ON (default): pause at every step for approval. Skip passing steps. Only re-run failures. Respect retry cap.
  • OFF: run autonomously, keep done-rule checks and retry cap.
  • Promote to OFF after N consecutive successful runs.

PROTOCOLS

  1. Audit & rank: Read workspace, history, tools, saved skills. Run 4-Condition Test per candidate. Output ranked table, name the strongest.
  2. Build: Interview for task, goal, done-rule. Emit one Orchestration Skill with all 7 elements pre-baked. Keep it static.
  3. Verify: Final verification runs in a separate subagent (fresh context). Scores 1–10, done only above threshold.
  4. Memory: Write output file + memory file (what happened, worked, failed, remember next run).
  5. Promote: After N successful runs with ON, flip to OFF. Keep done-rule and retry cap.

OUTPUT SCHEMA

  1. TL;DR — one-line summary.
  2. 4-Condition Test results — pass/fail per condition, ranked table.
  3. Orchestration Skill — complete file with all 7 elements.
  4. Verification spec — scoring and threshold.
  5. Next action — single concrete step.

GUARDRAILS

  • One loop, one skill. No bundling unrelated tasks.
  • No done-rule, no loop. Machine-checkable or rejected.
  • Retry cap non-negotiable. Never loop forever.
  • Producer ≠ verifier. Never score own output.
  • Static skill. Readable artifact, not per-run prose.
  • Honesty. Failing any condition = "not a loop candidate."

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most agent orchestration skills give in 687 tokens

Counted across 742 of the 995 authors here whose files we hold, read 2026-08-07

  • reference existing artifacts by path or URLin 53 of 742, across 25 files
  • run the full test suite after integrating changesin 51 of 742, across 19 files
  • dispatch one agent per independent problem domainin 50 of 742, across 17 files
  • verify fixes do not conflictin 45 of 742, across 13 files
  • include a suggested skills section in the documentin 45 of 742, across 17 files
  • redact sensitive informationin 41 of 742, across 11 files
  • save to the temporary directory of the operating systemin 39 of 742, across 10 files
  • tailor the document to user-provided focus argumentsin 39 of 742, across 9 files
  • spot check agent changes for systematic errorsin 34 of 742, across 7 files
  • write a handoff document summarising the current conversationin 31 of 742, across 6 files
  • Assign each agent a specific scopein 23 of 742, across 8 files
  • provide specific scope and clear goalin 23 of 742, across 5 files

Said here and by no other author read

  • require a separate verifier subagent with fresh context
  • score verifier output 1 to 10
  • confirm task passes all four conditions before looping
  • rank candidate tasks by how cleanly they pass
  • bake all seven elements into the skill
  • keep the skill static

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.