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-reviewgit 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-review)<a href="https://agentmods.dev/skills/immamdouhaboammar/get-fable/fable-review"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/get-fable/fable-review/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-review"><img src="https://agentmods.dev/badge/skills/immamdouhaboammar/get-fable/fable-review.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 | $0.00122 | $0.01741 |
| Opus 5 | $0.00061 | $0.00870 |
| Sonnet 5 | $0.00024 | $0.00348 |
| Haiku 4.5 | $0.00012 | $0.00174 |
Grade A, and why
fable-review 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 — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Fable Review
Review the change as an independent engineer trying to find plausible defects, not as the implementer explaining why the patch is probably fine.
Mission
A useful review connects a concrete line/change to a concrete failure mode. It prioritizes correctness, invariants, compatibility, lifecycle behavior, and test adequacy before style preference.
The reviewer should be skeptical without manufacturing noise.
Activate When
- a diff/PR/implementation is ready for independent inspection;
- verification is green but human/semantic risks remain;
- repository conventions or public contracts may have been violated;
- a release/merge needs grounded review evidence.
Do Not Activate When
- no diff or concrete change exists;
- the main task is automated execution evidence (
fable-verify); - the requested work is threat modeling/security specialization (
fable-security); - blocking behavior is already known and needs implementation (
fable-execute).
Review Classification
Classify the change because different diffs deserve different review depth.
| Change | Primary review focus |
|---|---|
| Bug fix | root cause, regression test, adjacent paths |
| New feature | contract, error states, lifecycle, compatibility |
| Refactor | invariant preservation, accidental behavior delta |
| Concurrency | ordering, shared state, cleanup, race/deadlock |
| Persistence/migration | partial failure, transactions, compatibility, rollback |
| Public API/CLI | callers, defaults, error/exit behavior, versioning |
| Dependency upgrade | changed semantics, transitive behavior, config |
| Packaging/build | exports, artifact contents, generated files, runtime entrypoints |
Review Protocol
Stage 1 — Reconstruct intent independently
Read:
- user/issue/card acceptance;
- diff against the correct base;
- relevant existing contracts/tests/instructions.
State the intended behavior in your own words before judging the implementation.
Stage 2 — Read the whole diff, then trace risky changes
Do not review isolated snippets only. Identify:
- public/observable behavior delta;
- state/data-flow delta;
- control-flow/error delta;
- lifecycle/resource delta;
- concurrency delta;
- config/generated/package delta.
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 · 203 lines · 122 tokens per session scan A 84c7f7278563
fable-review is a skill published in the GitHub repository imMamdouhaboammar/get-fable (4 stars, last pushed 2d ago), licensed MIT. It adds 122 tokens to every session and 1,741 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.
Other skills, from other repositories
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.
reflecting-findings
Use when a reflection package hands you another agent's review findings to verify (before they become a fix request): you are the REFLECTOR, an independent skeptic. Judge each finding against the real code and settle it with reflectfinding — kept or refuted.
reviewing
Claude-on-Claude code review protocol — reviews implementation against spec requirements and code quality standards.
code
Use BEFORE generating, refactoring, reviewing, or debugging code. Trigger phrases include "write a function/script/class for X", "review this code/diff/PR", "refactor this", "debug this error", "is this implementation correct", "what's wrong with this code", "improve this code", "translate from X to Y", or any prompt…
improve-codebase-architecture
Find deepening opportunities in a codebase, informed by the domain language in CONTEXT.md and the decisions in docs/adr/. Use when the user wants to improve architecture, find refactoring opportunities, consolidate tightly-coupled modules, or make a codebase more testable and AI-navigable.
learn-from-sage
Detection-gap (miss) analysis for Code Review Sage. Learn from shipped fixes, acted-on human comments, and design outcomes to close reviewer blind spots. Inline during review stages a candidate; a human triggers a one-shot AI consolidation into the live ruleset.