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/5kahoisaac/skillless/fablednpx skills add 5kahoisaac/skillless --skill fabledgit clone --depth 1 https://github.com/5kahoisaac/skilllessWrote 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/5kahoisaac/skillless/fabled)<a href="https://agentmods.dev/skills/5kahoisaac/skillless/fabled"><img src="https://agentmods.dev/badge/skills/5kahoisaac/skillless/fabled.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 | $0.00171 | $0.03984 |
| Opus 5 | $0.00086 | $0.01992 |
| Sonnet 5 | $0.00034 | $0.00797 |
| Haiku 4.5 | $0.00017 | $0.00398 |
Grade A, and why
fabled scanned grade A with 1 finding 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 5d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
tracker, e.g. `curl -s https://www.demandsphere.com/research/demandsphere-radar/ai-frontier-model-tracker/api.json`, How it starts
The opening of the file, as written. The whole thing — 264 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fabled
Fabled makes the invisible working process of a frontier model explicit, so it can be followed step by step. It cannot transfer raw intelligence — it transfers process discipline: reconstructing intent, deciding scope, designing before building, refusing placeholders, and verifying against the original request before finishing. Most one-shot failures come from skipping that work, not from inability to write any given function. Follow every phase in order; each rule states its reason, and the reason is why the step is not optional.
Hard rules — non-negotiable
- Complete files only. Every file is written in full, top to bottom. (Why: a fragment that doesn't run fails the user completely; "mostly done" is not done.)
- Banned strings. The final output must contain zero of:
TODOused as a deferral marker (# TODO,// TODO, or bare uppercaseTODO), "rest of the code", "rest of code here", "you can implement", "for brevity", "left as an exercise", and function bodies that are empty or contain onlypass,..., or a not-implemented error. (Why: these are lexically checkable, so the ban is enforceable — unlike a vague "be complete".) Ordinary domain words are fine — a todo-list app may containtodoitems; the ban is on the deferral marker. - Never ask. Assume and record. Where the prompt is ambiguous, pick the most reasonable default, write it under
## Assumptions, and move on. (Why: in a single-prompt setting there is no second turn; a question back is a non-answer.) - Verify before responding. Re-check every numbered requirement from Phase 0 against the actual output, quoting evidence, before finishing. (Why: the most common failure is shipping something that silently ignores part of the request.)
- Fill the output template below, in order. (Why: the structure forces the phases to actually happen.)
Calibrate rigor — objective signals only
The process below is the correct behavior at every capability level; calibration only tunes how much extra discipline to add. Two strict limits: adjustments are keyed to objective signals only, and no tier ever skips a gate or a hard rule.
What ships with it
6 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.
- 5d ago First seen · 264 lines · 171 tokens per session scan A 155e6bd4d7be
fabled is a skill published in the GitHub repository 5kahoisaac/skillless (4 stars, last pushed 1mo ago), licensed MIT. It adds 171 tokens to every session and 3,984 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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