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 hawkongz/concept-fable --skill concept-fablegit clone --depth 1 https://github.com/hawkongz/concept-fableWrote 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/hawkongz/concept-fable/concept-fable)<a href="https://agentmods.dev/skills/hawkongz/concept-fable/concept-fable"><img src="https://agentmods.dev/badge/skills/hawkongz/concept-fable/concept-fable/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/hawkongz/concept-fable/concept-fable"><img src="https://agentmods.dev/badge/skills/hawkongz/concept-fable/concept-fable.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 | $0.00067 | $0.03711 |
| Opus 5.5 | $0.00027 | $0.01484 |
| Sonnet 5.5 | $0.00013 | $0.00742 |
| Haiku 4.5 | $0.00007 | $0.00371 |
Grade A, and why
concept-fable 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 1mo 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 — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Concept Fable Explainer
Overview
When a user wants to understand an abstract concept, don't throw a textbook definition at them. Instead, craft a carefully designed fable. The reader becomes immersed, only realizing near the end what it's about — then receives a clear explanation.
Core principle: Let them realize through story, not remember through definition.
Workflow
Follow these 8 steps:
Step 1 — Understand the Concept
- If you fully grasp the concept, proceed directly to the next step.
- If anything is unclear, search or consult authoritative sources.
- Distill 2–3 core elements: the central tension, the key mechanism, and why it matters.
- Map out the concept's causal chain — a step-by-step breakdown of how the concept actually works: what triggers what, in what order, leading to what outcome. This is the plot-level blueprint: your story must reproduce this exact sequence, not just graze the theme.
Relationship between core elements and metaphor points: Every core element must have a corresponding metaphor point that maps to it (this is the minimum). Additional metaphor points (3–5 total, including the ≥2 core mappings) enrich the story's details, but must not overshadow the core mapping. In short: Core elements: ≥2 must be mapped. Total metaphor points: 3–5.
Step 2 — Confirm Scope & Scene (As Needed)
Check with the user when:
- The concept has multiple branches or schools of thought (e.g., "consistency" means different things in different contexts)
- The concept has different interpretations across domains
- The user's phrasing is vague and could mean several things
Confirm understanding: "So this concept is essentially about ______, and the key insight is ______ — is that right?"
Confirm scene preference — assess the concept first, then decide whether to ask:
- Everyday scenes can precisely map the core process → Don't interrupt; use everyday scenes directly.
- The concept is abstract and far from daily experience → Ask briefly: "This concept is fairly abstract — what kind of work do you do or what did you study? I'll pick a scene you're familiar with, which makes it easier to grasp."
- The concept is familiar, but the user's profession could provide a sharper metaphor → Same as above, ask briefly.
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.
- 1mo ago First seen · 228 lines · 67 tokens per session scan A c001db1c746a
concept-fable is a skill published in the GitHub repository hawkongz/concept-fable (6 stars, last pushed 4mo ago), licensed MIT. It adds 67 tokens to every session and 3,711 once invoked, about $0.0003 per session on Opus 5.5. 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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