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 imMamdouhaboammar/get-fable --skill fable-coworkgit clone --depth 1 https://github.com/imMamdouhaboammar/get-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/immamdouhaboammar/get-fable/fable-cowork)<a href="https://agentmods.dev/skills/immamdouhaboammar/get-fable/fable-cowork"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/get-fable/fable-cowork/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/immamdouhaboammar/get-fable/fable-cowork"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/get-fable/fable-cowork.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 | $0.00112 | $0.01676 |
| Opus 5 | $0.00056 | $0.00838 |
| Sonnet 5 | $0.00022 | $0.00335 |
| Haiku 4.5 | $0.00011 | $0.00168 |
Grade A, and why
fable-cowork 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 6d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fable Cowork
Carry a scoped engineering objective through multiple tool calls and lifecycle stages with minimal conversational interruption, while preserving the same safety, evidence, and scope rules as interactive work.
Mission
Autonomy is not permission to improvise indefinitely. Cowork mode should reduce conversational overhead—not remove checkpoints, verification, stop conditions, or user intent.
The agent owns execution between meaningful boundaries. It must still stop when the task requires a new product decision, destructive authorization, unavailable external permission, or a contradiction that changes the agreed goal.
Activate When
- the user explicitly delegates a multi-step task end-to-end;
- the objective and success criteria are clear enough to continue without routine questions;
- the work may span discovery, planning, implementation, verification, review, and handoff;
- repeated narration would add noise while tool evidence can drive progress.
Do Not Activate When
- the job is a simple answer or one bounded edit;
- core requirements are genuinely ambiguous and different choices materially change the product;
- an external irreversible action lacks authorization;
- work must wait for a future event rather than execute now;
- autonomy would require inventing credentials, access, or user intent.
Autonomy Classification
| Task state | Cowork posture |
|---|---|
| Clear bounded sequence | execute silently through evidence gates |
| Multiple independent cards | delegate with explicit ownership |
| New architecture decision emerges | stop/replan; do not choose silently if material |
| Repeated failure | enter recovery before more mutation |
| External auth/permission unavailable | stop at hard wall with exact handoff |
| Destructive/public action authorized | execute with release/security checks |
| Destructive/public action not authorized | prepare/verify only; do not perform it |
Protocol
Stage 1 — Lock the objective and boundaries
Before long execution, capture:
- requested outcome;
- non-goals/protected surfaces;
- authorization boundaries;
- repository/worktree state;
- acceptance evidence;
- hard stop conditions.
What ships with it
7 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.
- 6d ago First seen · 184 lines · 112 tokens per session scan A 653492d0190b
fable-cowork is a skill published in the GitHub repository imMamdouhaboammar/get-fable (4 stars, last pushed 2d ago), licensed MIT. It adds 112 tokens to every session and 1,676 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 2026-09-05.
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Use when the workspace is empty — no code yet — and the user brings a raw idea: the brand-new branch of setting-up-a-project, normally reached via that dispatcher, directly only when the situation is unmistakable. Not for features in an existing project — use brainstorming instead.
todos
This chat has a shared, live TODO plan — your tasks for the conversation, which the user also edits. Read this skill and reach for the todo tools whenever a request takes more than a couple of steps. It covers the plan model (group = task, items = its steps; loose items are the user's lane), how to work it: propose…
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Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
spec-graph
The project's specs are its ground truth: durable documents describing the architecture, decisions, contracts, and boundaries behind the code, organized as a connected graph. Read this skill and reach for the spec tools FIRST — before reading code — whenever you explore the project, plan or start a task, add or change…
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Use this BEFORE any creative or feature work: building a new feature, adding functionality, changing behavior, or making a nontrivial design decision. Turns the user's request into a validated design — recorded as a spec-graph task-spec — before any implementation. Do not skip this because a change looks small.
reviewing-changes
Use when a review package asks you to review a plan step's change set (todo.startReview): you are the REVIEWER, not the author. How to judge an agent-written diff, file findings with addreviewcomment, and settle with exactly one reviewverdict.