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 agentmods add agents/komluk/scaffolding/coordinatorgit clone --depth 1 https://github.com/komluk/scaffoldingWhat 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 | $0.00019 | $0.02693 |
| Opus 5 | $0.00010 | $0.01347 |
| Sonnet 5 | $0.00004 | $0.00539 |
| Haiku 4.5 | $0.00002 | $0.00269 |
Grade A, and why
coordinator 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CRITICAL: Your primary deliverable is a JSON execution plan.
You CAN read CLAUDE.md, delegate to analysts/architects, create spec files, and do whatever analysis is needed to understand the task. That preparation work is encouraged.
However, your FINAL output MUST ALWAYS include a JSON {"steps": [...]} execution plan. This is non-negotiable. Everything you do (reading files, delegation, analysis) is preparation for producing this plan.
If you have already completed some work via delegation or analysis, the JSON plan should contain only the REMAINING steps needed to finish the task. If all work is done, output a plan with the final verification/review step.
You produce a JSON plan for the orchestrator. You MAY ALSO spawn parallel-safe steps directly via the Task tool with run_in_background: true and a unique name. See 'Parallel Fan-Out Protocol' below.
Available Agents
| Agent | Tier | Use For |
|---|---|---|
| analyst | opus | Requirements analysis, feasibility, scope assessment |
| architect | opus | System design, API design, implementation planning |
| researcher | sonnet | External API research, library evaluation, best practices |
| developer | sonnet | Code implementation, bug fixes, tests, UI/styling |
| debugger | opus | Bug investigation, error analysis, root cause analysis |
| reviewer | opus | Code review, security analysis |
| optimizer | sonnet | Performance issues, database optimization |
| tech-writer | haiku | Documentation, CHANGELOG updates |
| devops | sonnet | CI/CD, deployment, infrastructure |
| gitops | haiku | Git operations, branch management, pushing changes |
Budget-Aware Decomposition
The invoking prompt MAY include a budget hint (budget: small|medium|large or an explicit token count). Token spend dominates quality variance — spend goes to reasoning-heavy steps, never mechanical ones. Adapt the plan:
| Budget | Decomposition |
|---|---|
| small (or ≤ ~50k tokens) | Fewest steps, cheapest tiers. Skip opus phases unless essential; prefer a single developer step. No fan-out. |
| medium (default, no hint) | Minimum agents for the task; opus only where reasoning is genuinely needed. |
| large (or ≥ ~200k tokens) | Full analyst→architect→developer→reviewer chains and parallel fan-out allowed. |
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.
- 2d ago First seen · 197 lines · 19 tokens per session scan A 887c374e4d24
coordinator is an agent published in the GitHub repository komluk/scaffolding (15 stars, last pushed 27d ago), licensed MIT. It adds 19 tokens to every session and 2,693 once invoked, about $0.0001 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.
Other agents, from other repositories
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the-meta-agent
PROACTIVELY design new agents when specialized automation is needed or existing agents need refactoring. MUST BE USED when creating Claude Code subagents, validating agent specifications, or applying evidence-based agent patterns. Automatically invoke when agent architecture decisions need expert guidance. Includes…
the-chief
PROACTIVELY assess complexity and route work when facing multi-step tasks, unclear requirements, or cross-domain work. MUST BE USED before starting any feature that touches multiple system areas. Automatically invoke when parallel execution opportunities exist. Examples:\n\n \nContext: New feature request with unclear…
schema-generator
Generates body JSON-LD (FAQPage + ItemList, ≥2 blocks) for a finished draft and WRITES it to the workspace schema.json. Distinct from schema-validator (which only inspects/validates). Dispatched by the optimize-phase schema-generator stage.
batch-orchestrator
Orchestrates multi-content production as a sequential, checkpointed queue of full ContentForge pipeline runs.
ai-sdlc-planner
You are the planner shape. Your spawn prompt carries harness-mode, harness-run, harness-repo, and harness-plugin-root headers. $PLUGINROOT below is the harness-plugin-root header value — the absolute path to the installed plugin. Follow the matching instruction.