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/sahir619/fable-method/fable-loopnpx skills add Sahir619/fable-method --skill fable-loopgit clone --depth 1 https://github.com/Sahir619/fable-methodWhat 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 | $0.00111 | $0.01229 |
| Opus 5 | $0.00056 | $0.00615 |
| Sonnet 5 | $0.00022 | $0.00246 |
| Haiku 4.5 | $0.00011 | $0.00123 |
Grade A, and why
fable-loop 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
The Fable Loop
This skill orchestrates the fable-method: read its SKILL.md first; its rules govern every stage. It is installed alongside this skill (in this plugin's skills/fable-method/ directory, or ~/.claude/skills/fable-method/ for manual installs). The method says WHAT to check; this loop says WHO does the work: what runs in the main thread, what fans out to subagents, and what gets attacked before delivery.
Gate first. Trivial per the method's triviality gate: just do it, verify with the one obvious check, report in two sentences. No stages, no subagents. Everything else runs the four stages below in order.
Stage 1 - PLAN (the first bookend)
- Apply method Steps 0-3: classify the ask, define done with a named verification, state load-bearing assumptions.
- Evidence fan-out. Spawn the evidence gatherers as parallel subagents in ONE message, never sequentially:
- codebase questions: an Explore agent per distinct area ("how does X work", "what depends on Y");
- library or fact questions: a research agent that fetches current docs or searches the web;
- each subagent returns distilled findings with citations, never raw file dumps. One batch plus one follow-up batch is the budget; a third needs a stated reason.
- Produce the plan artifact in this shape: classification; definition of done plus its verification; evidence found (cited); ONE recommended approach (alternatives dismissed in a line each); the scope (the exact files or surfaces the work will touch); risks and assumptions; and the execution checklist.
- Decision gate. Task-shaped and reversible: proceed to Stage 2 without asking. Plan-first shape (ambiguous scope, irreversible or outward-facing actions, or the user asked for a plan): present the plan artifact and STOP for approval.
Stage 2 - EXECUTE
- Work the checklist in the main thread (use the todo tool if the harness has one; tick items as they complete). Deciding and editing stay in the main thread; only searching and verifying fan out.
- Every edit follows method Step 4: intent gate before behavior changes, recall gate before first use of anything unopened, smallest correct change, precise edits, never destroy without looking.
- Independent mechanical items (same change across many files, isolated file generation) may fan out to parallel subagents, in one message, with worktree isolation if they could touch the same files.
- A surprise mid-execution re-routes per method Step 2 rule 7: say it, then update the plan or go back to Stage 1. Never force the plan through a surprise.
- Mid-item ignorance is a pause, not a guess: the moment an edit would carry a fact from memory (a signature, a key, a figure), stop that item, fan out one research subagent per the method's recall gate, and resume when it returns.
- Outward-facing checklist items obey the method's authorization gate: no quoted user authorization, no action; the item converts to a proposed next step in the report.
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 · 52 lines · 111 tokens per session scan A 9a317740231b
fable-loop is a skill published in the GitHub repository Sahir619/fable-method (2,267 stars, last pushed 1mo ago), licensed MIT. It adds 111 tokens to every session and 1,229 once invoked, about $0.0006 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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