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/rhein1/fable5-codex/fable-understandnpx skills add rhein1/fable5-codex --skill fable-understandgit clone --depth 1 https://github.com/rhein1/fable5-codexWrote 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/rhein1/fable5-codex/fable-understand)<a href="https://agentmods.dev/skills/rhein1/fable5-codex/fable-understand"><img src="https://agentmods.dev/badge/skills/rhein1/fable5-codex/fable-understand.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 | $0.00064 | $0.00551 |
| Opus 5 | $0.00032 | $0.00275 |
| Sonnet 5 | $0.00013 | $0.00110 |
| Haiku 4.5 | $0.00006 | $0.00055 |
Grade A, and why
fable-understand 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 4d 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 — 47 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fable Understand
Answer from implementation evidence, not memory or stale docs.
For ECF-style governed runs, use ../../references/ecf-run-contract.md. For large or high-risk understanding tasks, use real Codex subagents when the runtime exposes a subagent tool and the user has not opted out; treat cross-module architecture, boot flow, data flow, integration wiring, security/privacy/money/data/API, or many-file mapping questions as large by default. Otherwise run single-agent multi-lens and say why no subagents were used when workflow trace is requested.
For large or high-risk Fable tasks, recommend running the parent task on gpt-5.6-sol with Ultra (model_reasoning_effort = "ultra") when available. Ultra may delegate proactively, but still explicitly request parallel delegation for disjoint Fable lenses when the runtime supports subagents; otherwise use single-agent multi-lens and report the reason.
Workflow
- Restate the question and scope.
- Restate authority boundaries and declare the ECF run mode when the user asks for ECF, subagents, or a receipt.
- Read repo instructions and the most direct source files.
- Trace from entrypoint to effects:
- route/command/UI entry
- service/module boundaries
- data reads/writes
- external calls
- errors, retries, and fallbacks
- tests and docs that confirm or contradict behavior
- Inspect callers and importers before answering behavior questions.
- Use a small diagram or ordered flow when it improves clarity.
- Include unknowns, assumptions, and stale-doc risks.
Evidence Safety
Never print raw secrets, tokens, private keys, wallet keys, credential files, or .env values. Redact secret-like values and cite only the file/path/key name needed to explain the issue.
Output
Prefer this shape:
- direct answer
- source-backed flow
- important edge cases
- unknowns or verification gaps
- useful next probe, only if needed
Every non-obvious claim should have a file, line, command, artifact, or runtime citation.
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.
- 4d ago First seen · 47 lines · 64 tokens per session scan A ee46d2ffd40a
fable-understand is a skill published in the GitHub repository rhein1/fable5-codex (4 stars, last pushed 14d ago), licensed MIT. It adds 64 tokens to every session and 551 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 2026-08-31.
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