Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Oriolshhh/runware-image-mcp --skill loop-solution-councilgit clone --depth 1 https://github.com/Oriolshhh/runware-image-mcpWrote 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.
[](https://agentmods.dev/skills/oriolshhh/runware-image-mcp/loop-solution-council)<a href="https://agentmods.dev/skills/oriolshhh/runware-image-mcp/loop-solution-council"><img src="https://agentmods.dev/badge/skills/oriolshhh/runware-image-mcp/loop-solution-council/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.
<a href="https://agentmods.dev/skills/oriolshhh/runware-image-mcp/loop-solution-council"><img src="https://agentmods.dev/badge/skills/oriolshhh/runware-image-mcp/loop-solution-council.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00020 | $0.00781 |
| Opus 5 | $0.00010 | $0.00391 |
| Sonnet 5 | $0.00004 | $0.00156 |
| Haiku 4.5 | $0.00002 | $0.00078 |
Grade A, and why
loop-solution-council scanned grade A with 0 findings 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 8d 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
77% identical to loop-context-compression — 95 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Loop: solution-council
Follow the ordered workflow below. Respect every human-approval gate, iteration bound, and stop condition.
# `mode: parallel-when-supported` means: run independently in parallel only if the
# platform provides isolated subagents; otherwise run sequentially or as simulated
# role passes, and never claim independence the target cannot guarantee.
name: solution-council
description: Produce an evidence-backed implementation recommendation through bounded specialist review.
max_iterations: 1
steps:
- id: discovery
name: discovery
agent: product-discovery
output: decision-brief
instruction: >-
Reuse .agent/context/ via context-discovery, inspect repository evidence,
and produce a decision brief (facts, assumptions, preferences, blockers).
Build one task context capsule for every specialist delegation.
Ask at most 3 (max 5) grouped, decision-changing questions; otherwise state
defaults and continue.
- id: route
name: route
agent: council-router
input: decision-brief
output: selected-specialists
instruction: >-
Select the smallest relevant specialist set (always architecture and
product; add others only on evidence), select each role's model tier via
model-routing, and justify both choices. Skip the full council for trivial,
low-risk changes. Keep chair synthesis heavy/high.
- id: independent-review
name: independent-review
mode: parallel-when-supported
agents_from: selected-specialists
input: decision-brief
output: specialist-reports
instruction: >-
Each selected specialist produces a first-pass report from the brief without
seeing the others' reports. Use the strongest isolation the platform supports
(parallel subagents, else sequential subagents, else simulated role passes)
and record which mode was used.
- id: challenge
name: challenge
mode: parallel-when-supported
agents_from: selected-specialists
input:
- decision-brief
- specialist-reports
max_rounds: 1
output: rebuttals
instruction: >-
Exactly one bounded round. The devil's advocate and selected specialists
challenge the leading proposal with evidence-based objections, unsupported
assumptions, and premature-consensus checks. No further rounds.
- id: synthesis
name: synthesis
agent: council-chair
input:
- decision-brief
- specialist-reports
- rebuttals
output: decision-record
instruction: >-
Synthesize (do not vote) into one decision record: recommended path,
confidence with deliberation mode, rejected alternatives, risks, preserved
dissent, and unresolved questions. Cite only evidence present in the reports.
- id: approve
name: approve
gate: human-approval
instruction: >-
Stop and present the decision record for explicit human approval. Do not
implement production code.
- id: handoff
name: handoff
command: /spec
instruction: >-
Only after approval, hand off to /spec to enter spec-to-implementation.
Apply
context-discoverybefore broad scanning: use a supplied context capsule first; otherwise check context frontmatter freshness, read.agent/context/routing.md, load only relevant summaries, and verify critical claims against source.
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.
- 8d ago First seen · 96 lines · 20 tokens per session scan A 671a0774b9c6
loop-solution-council is a skill published in the GitHub repository Oriolshhh/runware-image-mcp (0 stars, last pushed 2mo ago), licensed MIT. It adds 20 tokens to every session and 781 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 77% identical to loop-context-compression, differing in 95 lines, and is treated as a copy.
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