repair-orchestrator

repair-orchestrator is a skill for Claude Code from XuanRanL/loamwright-SEO-Skill. It costs 66 tokens per session (1,495 once invoked), scanned A, original, Apache-2.0.

A repair workflow for articles that fail quality checks or are rejected in review. It escalates from small edits to section rewrites, full-stage rewrites, or a complete regeneration, with a four-round limit.

In plain words
What is it for?
Use it when quality or review results identify issues in an article draft.
Why use it?
It provides a defined way to fix different levels of problems before deciding that an article cannot be salvaged.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: positional $N argument.

Part of the xuanran-seo-blog-writer plugin — 68 skills, 34 agents, 4 hooks shipped together

Good fit Use it when quality or review results identify issues in an article draft.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xuanranl/loamwright-seo-skill/repair-orchestrator
Install

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.

Any agent
npx skills add XuanRanL/loamwright-SEO-Skill --skill repair-orchestrator
Clone the repo
git clone --depth 1 https://github.com/XuanRanL/loamwright-SEO-Skill

Made for: Claude Code.

Or install xuanran-seo-blog-writer, the plugin that ships this one along with the rest of its 68 skills, 34 agents, 4 hooks.

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.

agentmods badge for repair-orchestrator

README.md
[![agentmods](https://agentmods.dev/badge/skills/xuanranl/loamwright-seo-skill/repair-orchestrator/github.svg)](https://agentmods.dev/skills/xuanranl/loamwright-seo-skill/repair-orchestrator)
Your own site
<a href="https://agentmods.dev/skills/xuanranl/loamwright-seo-skill/repair-orchestrator"><img src="https://agentmods.dev/badge/skills/xuanranl/loamwright-seo-skill/repair-orchestrator/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.

agentmods 80×15 button for repair-orchestrator

Your own site · 80×15
<a href="https://agentmods.dev/skills/xuanranl/loamwright-seo-skill/repair-orchestrator"><img src="https://agentmods.dev/badge/skills/xuanranl/loamwright-seo-skill/repair-orchestrator.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 66 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,495 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00066 $0.01495
Opus 5 $0.00033 $0.00747
Sonnet 5 $0.00013 $0.00299
Haiku 4.5 $0.00007 $0.00150

Measured 12d ago against content hash 1e4610cffbca, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

repair-orchestrator 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 12d 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.

subskills/cross-cutting/repair-orchestrator/SKILL.md · 184 lines

How it starts

The opening of the file, as written. The whole thing — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Repair Orchestrator

The escalating repair pipeline. Driven by quality.json findings.

Inputs

  • workspace/{task_id}/quality.json (one or more gates failed)
  • workspace/{task_id}/review.json (if independent-reviewer ran)
  • state.repair_iteration (current attempt count; cap = 4)

5 escalation levels

Level 1 — SURGICAL (cheapest, fastest)
  Edit specific lines indicated by quality.json.repairs[].instruction
  Use Edit tool only (preserve everything else)
  If quality improves ≥3 score → progress; loop back at Level 1 again
  If improvement <3 → escalate to Level 2

Level 2 — SECTION-REWRITE
  Identify which section(s) most contribute to failures
  Spawn writer agent for that section with:
    - original section spec
    - failures list as "things to fix"
    - stronger constraints
  Re-run quality gates
  If still failing → escalate to Level 3

Level 3 — STAGE-REWRITE
  Rerun one whole stage of build phase:
    - If structural issues: outline-architect (revise outline)
    - If reference issues: fact-check-and-citation (verify everything again)
    - If voice issues: humanizer (with stricter settings)
  Re-run quality gates
  If still failing → escalate to Level 4

Level 4 — FULL-REGEN
  Rerun all of Phase Build (preserve research.json + angle.json + outline.json)
  Re-run quality gates
  If still failing → escalate to Level 5

Level 5 — FROM-SCRATCH
  Rerun from Plan phase:
    - Pick alternative title from angle.alternative_titles_considered
    - New outline from scratch
    - New writer agents
  Re-run quality gates
  If still failing → HALT, return best-of-N to user

Hard cap: 4 total rounds across all levels. After round 4, return whatever artifact had highest quality.json score with a documented "could not converge" message.

Decision tree

Read quality.json.repairs[] and quality.gates:

def pick_level(quality, prior_iterations, prior_level):
    # First iteration after gate fail
    if prior_iterations == 0:
        return 1  # Always start surgical
    
    # Surgical didn't improve enough
    if prior_level == 1:
        # Was improvement small?
        delta = current_score - prior_score
        if delta < 3:
            return 2  # Escalate
        return 1  # Continue surgical
    
    # Section rewrite didn't help
    if prior_level == 2:
        # How many sections needed rewrite?
        problem_sections = [s for s in sections if has_issues(s)]
        if len(problem_sections) > 3:
            return 3  # Stage-level fix
        return 2  # Try again
    
    # Stage rewrite didn't help → full regen
    if prior_level == 3:
        return 4
    
    # Full regen didn't help → from scratch
    if prior_level == 4:
        return 5

Read the full file on GitHub · 184 lines

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.

  1. 12d ago First seen · 184 lines · 66 tokens per session scan A 1e4610cffbca

Subscribe to this mod's changes

repair-orchestrator is a skill published in the GitHub repository XuanRanL/loamwright-SEO-Skill (49 stars, last pushed 25d ago), licensed Apache-2.0. It adds 66 tokens to every session and 1,495 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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