What is system-deep-loop?

A routing hub for four kinds of iterative work: research, code review, AI-council planning, and agent improvement.

Use it to start deep research, deep review, AI-council planning, or bounded agent-improvement workflows through one entry point.

It directs a request to the matching workflow and its saved instructions instead of making each workflow manage routing separately.

system-deep-loop — Skill for Claude Code and OpenCode by MichelKerkmee

Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo

git clone --depth 1 https://github.com/MichelKerkmeester/skilled-agent-harness_spec-driven-loops

agentmods

npx agentmods add skills/michelkerkmeester/skilled-agent-harness_spec-driven-loops/system-deep-loop

Made for: Claude Code, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/skills/michelkerkmeester/skilled-agent-harness_spec-driven-loops/system-deep-loop/github.svg)](https://agentmods.dev/skills/michelkerkmeester/skilled-agent-harness_spec-driven-loops/system-deep-loop)

Your own site

<a href="https://agentmods.dev/skills/michelkerkmeester/skilled-agent-harness_spec-driven-loops/system-deep-loop"><img src="https://agentmods.dev/badge/skills/michelkerkmeester/skilled-agent-harness_spec-driven-loops/system-deep-loop/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/skills/michelkerkmeester/skilled-agent-harness_spec-driven-loops/system-deep-loop"><img src="https://agentmods.dev/badge/skills/michelkerkmeester/skilled-agent-harness_spec-driven-loops/system-deep-loop.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 4,114 The whole file, excluding the scripts and references it only reads on demand.

Security scan C 1 finding. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00021	$0.04114
Opus 5	$0.00010	$0.02057
Sonnet 5	$0.00004	$0.00823
Haiku 4.5	$0.00002	$0.00411

Measured 6d ago against content hash df615c991eaf, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade C, and why

system-deep-loop scanned grade C with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Hidden instructionshighPrompt injection

Directives inside HTML comments, invisible characters or bidirectional overrides are read by the model and not by the person reviewing the file.

<!-- Keywords: system-deep-loop, deep-loop, deep-research, deep-review, deep-ai-council, deep-improvement, conformance, standard-authority, conformance-review, read-only-default, context-gathering, reuse-catalog, autores

.opencode/skills/system-deep-loop/SKILL.md · 175 lines

How it starts

The opening of the file, as written. The whole thing — 175 lines — stays where its author put it; the contents beside it link to each section on GitHub.

System Deep Loop

One skill, four active workflow families, one nested runtime layer. system-deep-loop is the public, advisor-routable home for active deep-loop personas; runtime/ is the frozen, MCP-free infrastructure layer it consumes (formerly the separate deep-loop-runtime skill, merged into this hub 2026-07-08). This hub holds NO per-mode convergence, state, or synthesis logic — each active mode keeps its own contract in its packet, and the hub only routes by workflowMode through mode-registry.json.

Use @context for one-shot retrieval, /deep:research for iterative investigation with a bounded context snapshot, /deep:review for iterative audit with a bounded review snapshot, or /speckit:plan for implementation planning.

1. WHEN TO USE

Use this skill (through the hub) for any active deep-loop workflow. Invoke it as Skill(system-deep-loop) (optionally with a mode hint such as research: <request>); the hub classifies the request, resolves a workflowMode, and loads the matching nested mode packet. Active /deep:* commands and native agent types remain as complementary surfaces over the same packets.

Mode	Use it for	Packet	Command	Agent
research	Outward, web + code iterative investigation → `research/research.md`	`system-deep-loop/deep-research/`	`/deep:research`	`deep-research`
review	Iterative review loop → P0/P1/P2 findings + verdict	`system-deep-loop/deep-review/`	`/deep:review`	`deep-review`
ai-council	Multi-seat planning deliberation → `ai-council/**` artifacts	`system-deep-loop/deep-ai-council/`	`/deep:ai-council`	`ai-council`
improvement (3 lanes)	Evaluator-first improvement: `agent-improvement`, `model-benchmark`, `skill-benchmark`	`system-deep-loop/deep-improvement/`	`/deep:agent-improvement` · `/deep:model-benchmark` · `/deep:skill-benchmark`	`deep-improvement`

Read the full file on GitHub · 175 lines

Files

What ships with it

60 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

6d ago Changed · +1 lines df615c991eaf
8d ago First seen · 174 lines · 21 tokens per session scan C 38a263848cb7

Subscribe to this mod's changes

system-deep-loop is a skill published in the GitHub repository MichelKerkmeester/skilled-agent-harness_spec-driven-loops (35 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 4,114 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it C with 1 finding (hidden instructions). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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