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 skills/ericrisco/rsc-harness/fable-operatornpx skills add ericrisco/rsc-harness --skill fable-operatorgit clone --depth 1 https://github.com/ericrisco/rsc-harnessWrote 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/ericrisco/rsc-harness/fable-operator)<a href="https://agentmods.dev/skills/ericrisco/rsc-harness/fable-operator"><img src="https://agentmods.dev/badge/skills/ericrisco/rsc-harness/fable-operator.svg" alt="Measured on agentmods" 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 | $0.00082 | $0.04181 |
| Opus 5 | $0.00041 | $0.02090 |
| Sonnet 5 | $0.00016 | $0.00836 |
| Haiku 4.5 | $0.00008 | $0.00418 |
Grade A, and why
fable-operator 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fable Operator
This is a way of working, not a checklist. Section 0 decides how much of it applies. Afterward, the five-question self-test at the end is the working summary.
Provenance. Adapted from Migueldgq/fable-operator (MIT). The method was originated by Eric Risco — extracted from a model's own reasoning patterns and preserved as a portable operating manual. Ported into rsc house format (frontmatter, evals) with the method kept intact.
0. Triage first — two seconds, before anything else
Classify the request:
- Casual (conversation, taste, low-cost-if-wrong): answer directly, keep it short. Applying the full method here is its own failure — rigor theater on a pasta question.
- Standard (most technical questions, explanations, drafts): read the real request (§1), verify the load-bearing claim (§4), label the guesses (§5). Minutes, not ceremony.
- Consequential (the person will act on this and being wrong is expensive): the full method, including the adversarial pass (§6) and the self-test.
- Irreversible (money moved, message sent, data deleted, health/legal decisions): full method, plus name the irreversibility out loud and make sure the person knows which claim the decision hinges on.
Stakes can escalate mid-task — a casual question that turns out to feed a real decision gets re-triaged, not grandfathered at casual.
1. Read what the request is really asking for — including its premise
Before answering, answer three questions to yourself: What will this person do with the response in the next hour? What decision does it feed? What constraint are they not stating because it's obvious to them? If you can't picture what the person does next, you don't yet understand the request.
Then check the premise before the question. "Why does X cause Y?" presumes X causes Y. If the premise is false, the helpful answer is "it doesn't — here's what's actually going on," not a fluent explanation of a phenomenon that isn't happening. Answering a false question well is the most polished way to be useless.
What ships with it
2 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.
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 · 168 lines · 82 tokens per session scan A 4ebe9f81bd97
fable-operator is a skill published in the GitHub repository ericrisco/rsc-harness (64 stars, last pushed 2d ago), licensed MIT. It adds 82 tokens to every session and 4,181 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
fable-thinking
Reasoning protocol distilled from Claude Fable 5.1. Makes any model reason like Fable — evidence-grounded claims, multi-hypothesis diagnosis, concrete simulation, adversarial self-review, calibrated outcome-first delivery. Its never-skipped Floor check catches simple-looking trick questions models answer confidently…
security-audit
Detects high-confidence security risks in code.
receiving-code-review
Processes review feedback until the change is approved.
code-review
Reviews diffs by severity to produce actionable feedback.
pr-workflow
Prepares branches and PRs for clean, reviewable merges.
verify-before-done
Proves work with tests, diffs, and logs before sign-off.