loop-engineering
Skill1 starsChanged 5 months agoMITView on GitHub
Use when a software or repository development task requires multiple actions, repeated verification, recovery from failed attempts, or explicit completion, blocking, or user-decision criteria.
33 other projects use a version of this.
Adopted by
Most recently taken up by
- vpeetla-ai/venkat-ai-platformtheir own version, first seen Nov 8, 2026
- Mark393295827/graph-engineering-architecturestheir own version, first seen Nov 8, 2026
- victor-hac-work/loop-engineering-skillstheir own version, first seen Nov 8, 2026
- jggomez/expert-ai-developer-skillstheir own version, first seen Nov 6, 2026
- Hakkadaikon/hymmetheir own version, first seen Oct 26, 2026
- vpeetla-ai/swarm-agent-patterntheir own version, first seen Oct 20, 2026
Used with
Projects with it also use aegis-gateway, deploy-vercel-render and 10 more.
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.
vpeetla-aiSkillaegis-gateway
Integrate AegisAI gateway before tool side effects (notify, publish, deploy). Use when adding Slack/Telegram/WhatsApp notify, content publish, or any irreversible external action in VAP, AegisLoop, or ai-content-factory.
Also in 6 projects that use this
vpeetla-aiSkilldeploy-vercel-render
Deploy vpeetla-ai demos: Vercel static/Next.js frontends, Render FastAPI backends, env vars, free tier gotchas. Use when shipping demos, fixing deploy failures, or adding render.yaml / vercel.json.
Also in 6 projects that use this
HermeticOrmusSkilllanggraph-orchestration
LangGraph stateful multi-agent graphs with categorical coordination patterns and cyclic workflows. Use when building stateful AI agent systems, implementing multi-agent orchestration with conditional routing, creating cyclic workflows with persistence, or designing graph-based AI pipelines with checkpointing and human-in-the-loop patterns.
Also in 6 projects that use this
junimnjwSkillagentic-engineering
Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing.
Also in 7 projects that use this
- +8 more from vpeetla-ai
Other versions33 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 33
- bojieli/ai-agent-book-projects★ 53ksame name
- bojieli/ai-agent-book★ 53ksame name
- huytieu/COG-second-brain★ 1.3ksame name
- akitaonrails/my-skills★ 283same name
- jggomez/expert-ai-developer-skills★ 31same name
- aiconnai/agentshield★ 21same name
- sxivansx/loop-engineering★ 10same name
- victor-hac-work/loop-engineering-skills★ 5same name
- Mark393295827/graph-engineering-architectures★ 4same name
- aiconnai/engram★ 3same name
23 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository14 other files it gives its agents.
- design-md-to-shadcnSkill
- figma-icons-iconifySkill
- figma-logos-svglSkill
- graph-engineeringSkill
- intro-videoSkill
- ko-naturalSkill
- langfuse-laravel-aiSkill
- onboarding-designSkill
- public-sector-rfp-authoringSkill
- release-showcaseSkill
- token-auditSkill
- ux-writing-koreanSkill
- writing-project-readmeSkill
- template-skillSkill
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 5 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 27 edited versions we read keep these.
5
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 10
Use a bounded control loop where each iteration reduces uncertainty or advances an observable result.
- Very specific: line 26
trivial: run goal → action → verification once.
- Distinctive: line 27
local: run the full loop with local evidence.
- Distinctive: line 28
cross-cutting: run the full loop and apply Graph Escalation.
- Distinctive: line 30
Read loop-protocol.md before iterating and stop-conditions.md before declaring an outcome.
- Distinctive: line 38
Verify: run the planned check and compare expected with actual evidence.
- Very specific: line 52
When graph-engineering is installed, it is a REQUIRED SUB-SKILL for those cross-cutting cases.
“Common” is measured: kept by at least 6 in 10 of the 27 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.
Files
Loop Engineering
Overview
Use a bounded control loop where each iteration reduces uncertainty or advances an observable result.
Entry Contract
Before acting, establish:
- one objective and its boundaries;
- observable completion evidence;
- safety, authority, and compatibility constraints;
- an iteration, time, or tool budget;
- the smallest verification command or observation that can test the next action.
Infer only reversible, low-risk defaults. If missing information would materially change public behavior, cost, scope, or an irreversible action, return needs-user-decision.
Classify the task before acting:
- trivial: run
goal → action → verificationonce; - local: run the full loop with local evidence;
- cross-cutting: run the full loop and apply Graph Escalation.
Read loop-protocol.md before iterating and stop-conditions.md before declaring an outcome.
Run the Loop
Repeat plan → act → verify → decide:
- Plan: choose one falsifiable hypothesis, one bounded action, and its expected evidence.
- Act: perform the smallest authorized action that tests the hypothesis or advances the objective.
- Verify: run the planned check and compare expected with actual evidence.
- Decide: complete, retry with new evidence, replan, block, or request user direction.
Track the protocol state in task memory or temporary scratch space. Never add loop transcripts, chain-of-thought, or speculative reasoning to durable project documentation.
Graph Escalation
Broaden local evidence into a map when:
- a public interface, shared schema, global configuration, or deployment boundary changes;
- failures appear in multiple components or layers;
- the same dependency knowledge is repeatedly rediscovered;
- impact or rollout order cannot be established from the local module.
When graph-engineering is installed, it is a REQUIRED SUB-SKILL for those cross-cutting cases. If unavailable, build a compact evidence-backed impact map inline and continue; do not fail only because the companion skill is absent.
graph-engineering never needs to invoke this skill.
Progress and Final Output
During long tool work, report evidence, the decision, and next action at least every 60 seconds without exposing private reasoning.
Finish with exactly one outcome:
| Outcome | Required report |
complete | acceptance evidence, verification commands or observations, test limitations, and intentional changes |
blocked | blocking condition, attempts made, recoverable workspace state, and next action |
needs-user-decision | decision required, evidence, and materially different options |
Common Mistakes
| Mistake | Correction |
| Repeating the same action | Require new evidence or replan. |
| Treating a passing check as sufficient | Match it to every completion criterion. |
| Expanding scope after each failure | Expand only across an observed dependency boundary. |
| Calling ambiguity a technical blocker | Use needs-user-decision when user intent must govern. |
| Persisting execution history as architecture | Persist only stable, evidence-backed project knowledge. |
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