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 SoliEstre/EstreGenesis --skill subscalergit clone --depth 1 https://github.com/SoliEstre/EstreGenesisWrote 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/soliestre/estregenesis/subscaler)<a href="https://agentmods.dev/skills/soliestre/estregenesis/subscaler"><img src="https://agentmods.dev/badge/skills/soliestre/estregenesis/subscaler/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/soliestre/estregenesis/subscaler"><img src="https://agentmods.dev/badge/skills/soliestre/estregenesis/subscaler.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 | $0.00145 | $0.02925 |
| Opus 5 | $0.00072 | $0.01463 |
| Sonnet 5 | $0.00029 | $0.00585 |
| Haiku 4.5 | $0.00015 | $0.00293 |
Grade A, and why
subscaler 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 3d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/subscaler — tiered model composition
/superscalar decides how eagerly to fan out. This skill decides what each lane runs on — tier and effort. The two are orthogonal; set them independently.
The mechanism that makes a tier drop safe is spec completion before offload: a fully-specified lane loses little from one tier down, an underspecified one loses a lot. Spec completeness is the quality moderator, not model size.
Toggle contract
- State = one marker file:
.agent/subscaler.json—{"on": true, "family": "<vendor>", "effort": "<level>"}. Read at invocation time; never mirror the state into other settings surfaces (duplicated per-role model bindings have shipped state-convergence bugs). /subscaler onwrites it ·/subscaler offremoves it (or sets"on": false) ·/subscaler statusreads it back and reports where it would apply next.- Default OFF. ON is recommended where fan-out has already forfeited the shared prompt cache. A delegated subagent starts cache-cold on its own model, so a small, cache-hot, deep-context edit loses money on delegation.
Step 0 — frontier-main cost gate (when the orchestrator itself is T1)
If the main conversation runs on a T1 model (a Fable-class flagship), inheritance is the failure mode: the Agent tool resolves a subagent's model as per-invocation model → frontmatter model → CLAUDE_CODE_SUBAGENT_MODEL (a default, not a pin, since v2.1.251 — before that the env var came first) → the main model, and a Workflow agent() that omits opts.model inherits the same way. Nothing in that chain says "frontier" — it just is. Two env facts sit outside the chain: CLAUDE_CODE_SUBAGENT_MODEL_FORCE=1 (v2.1.257+) overrides every binding including the ones you wrote, and on the Claude API the built-in Explore agent inherits with an Opus cap (a Fable main runs Explore on Opus 5) — neither is visible from the spawn request, so verify with /tasks (v2.1.242+), which names each running subagent's model and effort. And ultracode sends xhigh to the model as a session setting, which every unbound lane inherits too. So, before any fan-out on a T1 main:
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.
- 3d ago Changed · +11 lines 34db975f70a1
- 9d ago First seen · 87 lines · 145 tokens per session scan A 2c6974553528
subscaler is a skill published in the GitHub repository SoliEstre/EstreGenesis (8 stars, last pushed 2d ago), licensed Apache-2.0. It adds 145 tokens to every session and 2,925 once invoked, about $0.0007 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 2026-08-31.
Other skills, from other repositories
update-agent-context
This skill should be used to keep CLAUDE.md, AGENTS.md, and the skill files themselves compact, current, and internally consistent. It runs in three phases: Phase 1 performs a one-time structural refactor of CLAUDE.md using a Karpathy-inspired behavioral scaffold and derives AGENTS.md from it by stripping Claude…
watercooler-onboarding
Bootstrap Watercooler memory for a repository by inspecting local code, docs, CI, git history, and existing Watercooler threads, then writing a small set of durable, provenance-backed seed threads that future agents can query and extend. Use when entering a repo for the first time, seeding a repo with Watercooler…
search-threads
Search threads with filters. Supports filters like role:planner, type:Decision, after:2024-01, thread:topic-name, status:OPEN.
ppgp
Portable Persistent Goal Protocol for long-running coding-agent work. Use when starting, resuming, handing off, distilling, or closing a substantial software goal across long sessions, context compaction, agent replacement, or other Agent Skills-compatible coding-agent environments.
watercooler-health
Check watercooler system health — MCP server, baseline graph (T1), git auth, GitHub rate limit, and daemons. Use when syncs break or anything in the watercooler stack behaves unexpectedly.
recall
Recall project context or answer questions about history and decisions. Use before starting work, when investigating unfamiliar code, or asking "What was decided about X?" / "Why did we choose Y?".