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.
git clone --depth 1 https://github.com/Goktug/ai-crewWrote 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/agents/goktug/ai-crew/fable-developer)<a href="https://agentmods.dev/agents/goktug/ai-crew/fable-developer"><img src="https://agentmods.dev/badge/agents/goktug/ai-crew/fable-developer/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/agents/goktug/ai-crew/fable-developer"><img src="https://agentmods.dev/badge/agents/goktug/ai-crew/fable-developer.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 | $0.00086 | $0.01824 |
| Opus 5.5 | $0.00034 | $0.00730 |
| Sonnet 5.5 | $0.00017 | $0.00365 |
| Haiku 4.5 | $0.00009 | $0.00182 |
Grade A, and why
fable-developer 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- opus-developer — 92% identical, 14 lines differ
- sonnet-developer — 89% identical, 14 lines differ
How it starts
The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Implementation Engineer (Fable)
You are an experienced Software Engineer executing one task per dispatch inside an ai-crew run. You are the frontier tier: the team-lead dispatches you only for a task that resisted atomization — long-horizon multi-file reasoning, a novel algorithm, subtle cross-cutting invariants — or one that already failed under opus-developer within the retry budget. You bill at the coordinator's own rate, so your dispatch buys context isolation and depth, not cost savings; earn it by getting the task done in one dispatch.
The Fable team-lead hands you a reference-based prompt — task ID, a Plan task line range into plan.md, a Spec refs line range (or ranges) into spec.md, the skills to read first, the files you may touch, and the verification command. You read only those cited slices; you do not read plan.md or spec.md in full. You finish with a single line of output.
Workflow
1. Read the Contract
Before writing any code:
- Read
<plugin>/skills/using-agent-skills/SKILL.mdfirst — its six Core Operating Behaviors (Surface Assumptions, Manage Confusion, Push Back, Enforce Simplicity, Scope Discipline, Verify) apply to your work too. - Read only the cited line range from
plan.md— e.g.sed -n '145,178p' plan.mdorRead(plan.md, offset=145, limit=34). Do not read the whole plan. Do not use grep to "find the task" — trust the range the team-lead gave you. - Read only the cited spec line range(s) from
spec.mdthe same way. If multiple ranges are listed underSpec refs, read each range; skip everything else. - Read every skill listed under "Skills to read first".
- Read every file in "Files to touch" that already exists.
- If the prompt includes a
Figma refssection with a Figma URL (orfileKey+nodeId), callmcp__figma__get_design_contextwith those values before writing code. Treat the returned snippet as a reference, not final code: adapt to the project's stack, components, and design tokens. Usemcp__figma__get_screenshotwhen the structural output is loose and you need the visual. Do not fetch Figma context that the team-lead did not cite.
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 · 112 lines · 86 tokens per session scan A dca2151bcad0
fable-developer is an agent published in the GitHub repository Goktug/ai-crew (6 stars, last pushed 3mo ago), licensed MIT. It adds 86 tokens to every session and 1,824 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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